An introduction to relational complexity: …An introduction to relational complexity: background,...

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An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento Workshop on the Model Theory of Finite and Pseudofinite Structures Joshua Wiscons Relational complexity

Transcript of An introduction to relational complexity: …An introduction to relational complexity: background,...

Page 1: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An introduction to relational complexity: background,questions, and a few answers

Joshua Wiscons

California State University, Sacramento

Workshop on the Model Theory of Finite and PseudofiniteStructures

Joshua Wiscons Relational complexity

Page 2: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 3: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 4: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 5: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 6: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 7: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 8: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

Let L(X) be the language obtained by naming the definable subsets of allfinite powers of X.

Let Lk(X) be the language obtained by considering only the definablesubsets of Xi for i ≤ k.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

Definition (via Homogeneity)The relational complexity of X is the least k such that X is equivalent to ahomogeneous structure (X, S1, . . . , Sn) with every Si of arity at most k.

Joshua Wiscons Relational complexity

Page 9: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

1 rc(X) is really an invariant of X, hence of Aut(X) = Aut(X).2 The definable subsets of Xk are unions of orbits of Aut(X) (acting

diagonally) on Xk.

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Joshua Wiscons Relational complexity

Page 10: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

1 rc(X) is really an invariant of X, hence of Aut(X) = Aut(X).

2 The definable subsets of Xk are unions of orbits of Aut(X) (actingdiagonally) on Xk.

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Joshua Wiscons Relational complexity

Page 11: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

1 rc(X) is really an invariant of X, hence of Aut(X) = Aut(X).2 The definable subsets of Xk are unions of orbits of Aut(X) (acting

diagonally) on Xk.

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Joshua Wiscons Relational complexity

Page 12: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

1 rc(X) is really an invariant of X, hence of Aut(X) = Aut(X).2 The definable subsets of Xk are unions of orbits of Aut(X) (acting

diagonally) on Xk.

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Joshua Wiscons Relational complexity

Page 13: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Let X = (X,R1, . . . ,Rm) be a finite relational structure.

DefinitionThe relational complexity of X is defined to be the least k such that for everyrelation R in L(X) there exists a quantifier-free formula ϕ in Lk(X) withX |= ∀x (R(x)↔ ϕ(x)).

1 rc(X) is really an invariant of X, hence of Aut(X) = Aut(X).2 The definable subsets of Xk are unions of orbits of Aut(X) (acting

diagonally) on Xk.

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Joshua Wiscons Relational complexity

Page 14: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.

1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 15: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.

1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 16: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).

2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 17: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.

3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are inthe same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 18: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 19: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 20: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 21: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 22: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1

g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 23: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 24: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 25: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

(x1, x2, x3)

(y1, y2, y3)

g

(3-)equivalence

(x1, x2, x3)

(y1, y2, y3)

g1 g2

g3

2-equivalence

Note: 3-equivalenceimplies 2-equivalence

Joshua Wiscons Relational complexity

Page 26: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Relational Complexity

Definition (Fuzzy Reformulation)The relational complexity of X is defined to be the least k such that the orbitsof Aut(X) on Xk “determine” the orbits of Aut(X) on Xn for all finite n.

Terminology

Let (X,G) be a permutation group.1 Every g ∈ G acts diagonally on Xn via (x1, . . . , xn)g = (x1g, . . . , xng).2 The orbits of G on Xn are called n-types.3 Two tuples x, y ∈ Xn are k-equivalent if every k elements from x are in

the same orbit as the corresponding k elements from y.

DefinitionThe relational complexity of a permutation group (X,G) is the smallest k suchthat for all n ≥ k, k-equivalence of n-tuples implies equivalence.

Joshua Wiscons Relational complexity

Page 27: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.

Question: (1, 2, 3) ∼ (1, 5, 4)? Yes.(1, 2, 3)

(1, 5, 4)

?reflection: (25)(34)(7 10)(89)

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 28: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 2, 3) ∼ (1, 5, 4)?

Yes.

(1, 2, 3)

(1, 5, 4)

?

reflection: (25)(34)(7 10)(89)

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 29: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 2, 3) ∼ (1, 5, 4)? Yes.

(1, 2, 3)

(1, 5, 4)

?

reflection: (25)(34)(7 10)(89)

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 30: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.

Question: (1, 3, 7) ∼ (1, 3, 9)?(1, 3, 7)

(1, 3, 9)

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 31: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼ (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

?

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 32: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼ (1, 3, 9)? No.

(1, 3, 7)

(1, 3, 9)

?

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 33: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 34: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

id

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 35: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

id

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 36: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

reflection

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 37: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

reflection

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 38: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 39: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)?

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 40: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)? Yes!

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 41: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)? Yes!

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 42: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)? Yes!

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2.

It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 43: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)? Yes!

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2. It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 44: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A First Example

Example (Petersen Graph)

1

62

7

3

8

4

9

510

Let G be the automorphism group of the graph.Question: (1, 3, 7) ∼2 (1, 3, 9)? Yes!

(1, 3, 7)

(1, 3, 9)

it works . . . but hard to see

Thus, 2-equivalence does not imply equivalence.

Thus, rc(G) > 2. It turns out that rc(G) = 3.

RemarkBe aware that, for example, 2-equivalence may imply 3-equivalence withoutimplying 4-equivalence.

Joshua Wiscons Relational complexity

Page 45: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Joshua Wiscons Relational complexity

Page 46: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 2

2 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Joshua Wiscons Relational complexity

Page 47: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 2

2 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Choose a nontrivial g ∈ G.

Choose distinct x, y ∈ X with xg = y.

Then (x, x) and (x, y) are 1-equivalent but not 2-equivalent.

Joshua Wiscons Relational complexity

Page 48: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 2

2 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Choose a nontrivial g ∈ G.

Choose distinct x, y ∈ X with xg = y.

Then (x, x) and (x, y) are 1-equivalent but not 2-equivalent.

Joshua Wiscons Relational complexity

Page 49: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 2

2 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Choose a nontrivial g ∈ G.

Choose distinct x, y ∈ X with xg = y.

Then (x, x) and (x, y) are 1-equivalent but not 2-equivalent.

Joshua Wiscons Relational complexity

Page 50: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 2

2 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Choose a nontrivial g ∈ G.

Choose distinct x, y ∈ X with xg = y.

Then (x, x) and (x, y) are 1-equivalent but not 2-equivalent.

Joshua Wiscons Relational complexity

Page 51: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 2

2 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Joshua Wiscons Relational complexity

Page 52: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Joshua Wiscons Relational complexity

Page 53: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries

3 rc(X,G) ≤ max(2, |X| − 1)

Joshua Wiscons Relational complexity

Page 54: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Joshua Wiscons Relational complexity

Page 55: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Let x and y be (|X| − 1)-equivalent.

We may assume that neither tuple has repeated entries, so

x and y areenumerations of X.

If g ∈ G takes the first (|X| − 1) entries of x to the first (|X| − 1) entriesy, it must take the remaining entry of x to the remaining entry of y.

Thus, x and y are |X|-equivalent.

Joshua Wiscons Relational complexity

Page 56: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Let x and y be (|X| − 1)-equivalent.

We may assume that neither tuple has repeated entries, so

x and y areenumerations of X.

If g ∈ G takes the first (|X| − 1) entries of x to the first (|X| − 1) entriesy, it must take the remaining entry of x to the remaining entry of y.

Thus, x and y are |X|-equivalent.

Joshua Wiscons Relational complexity

Page 57: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Let x and y be (|X| − 1)-equivalent.

We may assume that neither tuple has repeated entries, so x and y areenumerations of X.

If g ∈ G takes the first (|X| − 1) entries of x to the first (|X| − 1) entriesy, it must take the remaining entry of x to the remaining entry of y.

Thus, x and y are |X|-equivalent.

Joshua Wiscons Relational complexity

Page 58: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Let x and y be (|X| − 1)-equivalent.

We may assume that neither tuple has repeated entries, so x and y areenumerations of X.

If g ∈ G takes the first (|X| − 1) entries of x to the first (|X| − 1) entriesy, it must take the remaining entry of x to the remaining entry of y.

Thus, x and y are |X|-equivalent.

Joshua Wiscons Relational complexity

Page 59: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Proof.

Let x and y be (|X| − 1)-equivalent.

We may assume that neither tuple has repeated entries, so x and y areenumerations of X.

If g ∈ G takes the first (|X| − 1) entries of x to the first (|X| − 1) entriesy, it must take the remaining entry of x to the remaining entry of y.

Thus, x and y are |X|-equivalent.

Joshua Wiscons Relational complexity

Page 60: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) =

22 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 61: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) =

22 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 62: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 63: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 64: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 65: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 66: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

?· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 67: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume x and y are 2-equivalent.

x1 x2 · · · xn

y1 y2 · · · yn

Of Course!· · ·

all distinct

all distinct

Joshua Wiscons Relational complexity

Page 68: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 2

2 rc(X,Alt(n)) =

n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 69: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) =

n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 70: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) = n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 71: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) = n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 72: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) = n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

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Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) = n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 74: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) = n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 75: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Remarks And More Examples

RemarkLet (X,G) be a nontrivial permutation group.

1 rc(X,G) ≥ 22 rc(X,G) = max(2, rc′(X,G))

where rc′(X,G) is computed only for tuples with no repeated entries3 rc(X,G) ≤ max(2, |X| − 1)

Example (Let X = {1, . . . , n}.)1 rc(X,Sym(n)) = 22 rc(X,Alt(n)) = n−1

Assume rc(X,Alt(n)) = r with 2 ≤ r ≤ n− 2.

Let x, y be any two enumerations of X.

Key point: (X,Alt(n)) is (n− 2)-transitive.

Thus, x and y are (n− 2)-equivalent.

So, if r ≤ n− 2, x and y are equivalent.

Joshua Wiscons Relational complexity

Page 76: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems

1 Gather data: determine the relational complexities of natural permutationgroups.

E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.

Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 77: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.

E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.

Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 78: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.

E.g, study the various natural actions of Sn (and An).2 Classify the finite permutation groups of relational complexity at most r.

Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 79: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.

Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 80: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.

Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 81: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.Need to restrict to so-called primitive groups.

E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 82: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 83: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 84: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2.

Then rc(V,GL(V)) = ?1 Lower bound:

rc(V,GL(V)) ≥ d + 1Let x = (e1, . . . , ed,

∑ei) and y = (e1, . . . , ed,

∑2ei).

Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 85: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?

1 Lower bound:

rc(V,GL(V)) ≥ d + 1Let x = (e1, . . . , ed,

∑ei) and y = (e1, . . . , ed,

∑2ei).

Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 86: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound:

rc(V,GL(V)) ≥ d + 1Let x = (e1, . . . , ed,

∑ei) and y = (e1, . . . , ed,

∑2ei).

Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 87: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound:

rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).

Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 88: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound:

rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.

Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 89: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound:

rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.

But, x and y are not equivalent.2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 90: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound:

rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 91: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 92: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound:

rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 93: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound: rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 94: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 1

Let x = (e1, . . . , ed,∑

ei) and y = (e1, . . . , ed,∑

2ei).Key point: GL(V) is transitive on the set of bases.Thus, x and y are d-equivalent.But, x and y are not equivalent.

2 Upper bound: rc(V,GL(V)) ≤ d + 1

Joshua Wiscons Relational complexity

Page 95: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 96: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalence

Assume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 97: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalent

Let m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 98: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)

Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 99: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independent

m equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 100: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 101: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and

- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to ym + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 102: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 103: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that

- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 104: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so

- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 105: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym

=⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 106: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym =⇒ g fixes span{y1, . . . , ym}

=⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 107: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym =⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 108: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym =⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ m

Thus, x ∼ (y1, . . . , ym, x′m+1, . . . , x′n) = y

Joshua Wiscons Relational complexity

Page 109: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = ?1 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym =⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 110: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

An easy, natural example

Example (GL(V))

Let V = Fd with char(F) > 2. Then rc(V,GL(V)) = d + 11 Lower bound: rc(V,GL(V)) ≥ d + 12 Upper bound: rc(V,GL(V)) ≤ d + 1

Want to show that (d + 1)-equivalence implies equivalenceAssume that x = (x1, . . . , xn) and y = (y1, . . . , yn) are (d + 1)-equivalentLet m be the size of a maximal independent subset of x. (m ≤ d)Without loss, assume that x1, . . . , xm are independentm equivalence implies that

- x = (x1, . . . , xm, xm+1, . . . , xn) ∼ (y1, . . . , ym, x′m+1, . . . , x′n) and- (y1, . . . , ym, x′m+1, . . . , x′n) is (d + 1)-equivalent to y

m + 1 equivalence implies that- there exists g ∈ GL(V) taking (y1, . . . , ym, x′m+1) to (y1, . . . , ym, ym+1), so- g fixes y1, . . . , ym =⇒ g fixes span{y1, . . . , ym} =⇒ x′m+1 = ym+1

Repeating, we find that x′i = yi for all i ≥ mThus, x ∼ (y1, . . . , ym, x′m+1, . . . , x

′n) = y

Joshua Wiscons Relational complexity

Page 111: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

Example

P4(8) :

[1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 112: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

Example

P4(8) :

[1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 113: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) :

[1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 114: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678],

[2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 115: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357],

. . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 116: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . .

note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 117: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 118: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) :

[12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 119: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) : [12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 120: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) : [12 | 34 | 56 | 78], . . .

P3(9) :

[147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 121: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) : [12 | 34 | 56 | 78], . . .

P3(9) : [147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 122: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) : [12 | 34 | 56 | 78], . . .

P3(9) : [147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 123: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) : [12 | 34 | 56 | 78], . . .

P3(9) : [147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 124: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

DefinitionPm(n) is the set of all partitions of {1, . . . , n} into subsets of (equal) size m.

ExampleP4(8) : [1234 | 5678], [2468 | 1357], . . . note: [1234 | 5678] = [8765 | 4321]

P2(8) : [12 | 34 | 56 | 78], . . .

P3(9) : [147 | 258 | 369], . . .

Of course, there are many partitions of a given set, e.g. |P3(9)| = 280.

Definition (Action on Partitions)

Every σ ∈ Sn can be naturally regarded as a permutation of Pm(n) via the rule

σ ([x1 · · · xm | y1 · · · ym | · · · ]) = [σ(x1) · · ·σ(xm) | σ(y1) · · ·σ(ym) | · · · ].

Joshua Wiscons Relational complexity

Page 125: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 126: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 127: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2

P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 128: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3

P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 129: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 130: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3

P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 131: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 132: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 133: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3

P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 134: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5

P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 135: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4

P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 136: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural example

ProblemDetermine the relational complexity of Sn acting on Pm(n).

Some answers are known, but the reasons why aren’t so unclear.

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P2(6) : [∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S6) = 3P2(8) : [∗ ∗ | ∗ ∗ | ∗ ∗ | ∗ ∗] =⇒ rc(S8) = 4

P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P3(9) : [∗ ∗ ∗ | ∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S9) = 5

P2(4) : [∗ ∗ | ∗ ∗] =⇒ rc(S4) = 2P3(6) : [∗ ∗ ∗ | ∗ ∗ ∗] =⇒ rc(S6) = 3P4(8) : [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗] =⇒ rc(S8) = 5P5(10) : [∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗] =⇒ rc(S10) = 4P6(12) : [∗ ∗ ∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗ ∗ ∗] =⇒ rc(S12) ≥ 6

Joshua Wiscons Relational complexity

Page 137: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 138: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 139: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 140: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

[5234 | 1678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 141: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

[5234 | 1678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 142: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

[1678 | 3245]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 143: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

[5234 | 1678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 144: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

[5234 | 1678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 145: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

[1234 | 5678]

[5234 | 1678]

(1, 3)-pattern

[1234 | 5678]

[5634 | 1278]

(2, 2)-pattern

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 146: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 147: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

Joshua Wiscons Relational complexity

Page 148: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

[1234 | 5678]

[5234 | 1678]

(1, 5)

[1234 | 5678]

[6234 | 5178]

(1, 6)

Joshua Wiscons Relational complexity

Page 149: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

[1234 | 5678]

[5234 | 1678]

(1, 5)

[1234 | 5678]

[6234 | 5178]

(1, 6)

Joshua Wiscons Relational complexity

Page 150: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

[1234 | 5678]

[5234 | 1678]

(1, 5)

[1234 | 5678]

[6234 | 5178]

(1, 6)

Joshua Wiscons Relational complexity

Page 151: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

[1234 | 5678]

[5234 | 1678]

(1, 5)

[1234 | 5678]

[6234 | 5178]

(1, 6)

Joshua Wiscons Relational complexity

Page 152: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

[1234 | 5678]

[5234 | 1678]

(1, 5)

[1234 | 5678]

[6234 | 5178]

(1, 6)

Joshua Wiscons Relational complexity

Page 153: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

Joshua Wiscons Relational complexity

Page 154: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

Joshua Wiscons Relational complexity

Page 155: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

1

5

2

6

3

7

4

8

y1

y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

Joshua Wiscons Relational complexity

Page 156: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

Joshua Wiscons Relational complexity

Page 157: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

Joshua Wiscons Relational complexity

Page 158: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

Set x = [1234 | 5678].

Every x′ 6= x can have one of two relationships with x.

Let Y ⊂ P4(8) be the partitions that have a (1, 3)-pattern with x.

Every y ∈ Y is determined by two numbers.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

Joshua Wiscons Relational complexity

Page 159: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 160: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 161: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

No! The stabilizer of (x, y1, y2, y3) is〈(34)〉.

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 162: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

No!

The stabilizer of (x, y1, y2, y3) is〈(34)〉.

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 163: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

No! The stabilizer of (x, y1, y2, y3) is〈(34)〉.

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 164: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes!

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 165: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes!

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 166: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes: (23)(78) (“rotation”)

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 167: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes: (23)(78) (“rotation”)

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 168: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes: (15)(27)(38)(46) (“reflection”)

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 169: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes: (15)(27)(38)(46) (“reflection”)

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 170: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes: “reflection”

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 171: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes: “reflection”

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 172: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes!

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 173: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes!

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 174: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes!

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 175: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

A harder, natural (concrete) example

Let’s look at P4(8), i.e. [∗ ∗ ∗ ∗ | ∗ ∗ ∗ ∗], and try to see why rc(S8) = 5.

1

5

2

6

3

7

4

8

y1 y2

y3 u

v

x = [1234 | 5678]

y1 = [5234 | 1678]

y2 = [6234 | 5178]

y3 = [1734 | 5628]

u = [1834 | 5672]

v = [1274 | 5638]

x y1 y2 y3 u

x y1 y2 y3 v

Yes!

So these tuples are 4-equivalentbut not equivalent.

rc(S8) ≥ 5

Joshua Wiscons Relational complexity

Page 176: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 177: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

Theorem

Cherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 178: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},

a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

Theorem

Cherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 179: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

Theorem

Cherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 180: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

Theorem

Cherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 181: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

Theorem

Cherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 182: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

Theorem

Cherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 183: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

TheoremCherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 184: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Groups of relational complexity 2

Conjecture (Cherlin, 2000)A finite primitive permutation group of relational complexity 2 is either

Sn acting naturally on {1, . . . , n},a cyclic group of prime order acting regularly, or

an affine orthogonal group V o O(V) where V is a vector spaceequipped with an anisotropic quadratic form.

Fact (O’Nan–Scott)A finite primitive permutation group falls into one of five classes: (1) affine,(2) regular nonabelian, (3) almost simple, (4) diagonal, or (5) product.

TheoremCherlin, ’15: The conjecture holds for affine groups.

W, ’16: The conjecture reduces to the almost simple case.

Joshua Wiscons Relational complexity

Page 185: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 186: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.

In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 187: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.

In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 188: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.

In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 189: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 190: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, and

H ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 191: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 192: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 193: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 194: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.

2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 195: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)

3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 196: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Upper bounds on rc(X,G) in terms of |X|

Let (X,G) be a finite primitive permutation group.

Remark1 If (X,G) is of affine type, then rc(X,G) ≤ log2(|X|) + 2.2 Generically, rc(X,G) is likely not to be much bigger than log(|X|)3 But, we have already seen that big examples exist (Alt(n) on {1, . . . , n})

Proof.In this type, (X,G) ∼= (V,H) where

V is a vector space, say of characteristic p and dimension d, andH ≤ AGL(V) = V o GL(V)

Our method for bounding rc(V,GL(V)) above by d + 1 can be used toshow that rc(V,AGL(V)) ≤ d + 2

More generally, rc(V,H) ≤ d + 2

Thus rc(X,G) = rc(V,H) ≤ logp(|V|) + 2

Joshua Wiscons Relational complexity

Page 197: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Some Problems (posed by Cherlin)

Problems1 Gather data: determine the relational complexities of natural permutation

groups.E.g. study the various natural actions of classical groups.E.g, study the various natural actions of Sn (and An).

2 Classify the finite permutation groups of relational complexity at most r.Need to restrict to so-called primitive groups.E.g, what are the finite primitive permutation groups of relationalcomplexity 2?

3 Classify the finite permutation groups of relational complexity at least rwhen r is “big” compared to |X|.

Joshua Wiscons Relational complexity

Page 198: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.

What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type.

This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 199: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type.

This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 200: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type.

This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 201: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 202: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 203: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 204: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 205: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 206: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 207: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 208: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 209: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 210: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

h

Joshua Wiscons Relational complexity

Page 211: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 212: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

h−1

Joshua Wiscons Relational complexity

Page 213: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

Joshua Wiscons Relational complexity

Page 214: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

aha−1

Joshua Wiscons Relational complexity

Page 215: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1)

= (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

aha−1

Joshua Wiscons Relational complexity

Page 216: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1) = (aah)a−1

= ahaa−1 = ah

1 a a−h

1 ah a−1

aha−1

Joshua Wiscons Relational complexity

Page 217: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1) = (aah)a−1 = ahaa−1

= ah

1 a a−h

1 ah a−1

aha−1

Joshua Wiscons Relational complexity

Page 218: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Proof.

Want to show (1, a, ah) ∼ (1, ah, a)

This is the same as (1, a, a−h) ∼ (1, ah, a−1)

Suffices to show (1, a, a−h) ∼2 (1, ah, a−1)

a · (aha−1) = (aah)a−1 = ahaa−1 = ah

1 a a−h

1 ah a−1

aha−1

Joshua Wiscons Relational complexity

Page 219: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Joshua Wiscons Relational complexity

Page 220: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Punchline:

in these cases, complexity equal to 2 can be used to createinvolutions in a point stabilizer. (This is very useful.)

Joshua Wiscons Relational complexity

Page 221: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Punchline: in these cases, complexity equal to 2 can be used to createinvolutions in a point stabilizer.

(This is very useful.)

Joshua Wiscons Relational complexity

Page 222: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Back to binary groups

Let (X,G) be a finite primitive permutation group of relational complexity 2.What does this tell us about (X,G)?

Example

Assume that (X,G) is of affine or nonabelian regular type. This implies that

G ∼= M o H with H the stabilizer of a point,

X can be identified with M in such a way that (X,G) ∼= (M,MH) where

a · mh = (am)h

Claim: if a ∈ X, h ∈ H, and [a, ah] = 1, then ∃h′ ∈ H swapping a and ah.

Punchline: in these cases, complexity equal to 2 can be used to createinvolutions in a point stabilizer. (This is very useful.)

Joshua Wiscons Relational complexity

Page 223: An introduction to relational complexity: …An introduction to relational complexity: background, questions, and a few answers Joshua Wiscons California State University, Sacramento

Thank You

Joshua Wiscons Relational complexity