Automatic Parallelisation of Quantum Circuits Using the Measurement Based Quantum Computing
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Transcript of Automatic Parallelisation of Quantum Circuits Using the Measurement Based Quantum Computing
Einar Pius
Automatic Parallelisation of Quantum Circuits
Using the Measurement Based Quantum
Computing
2Automatic Parallelisation of Quantum Circuits
Motivation
• Quantum computation uses quantum mechanical properties
to represent data and perform operations on it
• Quantum bits (qubits) can be kept stable only for short time
– Due to quantum decoherence
• Algorithms must have as few steps as possible to be able to run on current experimental quantum computers
A two qubit quantum processor created at Yale University in 2009
3Automatic Parallelisation of Quantum Circuits
Goal of this project
• Creating a program that automatically decrease the number
of sequential steps required to perform a quantum
computation
• This was done by applying algebraic transformations to
quantum algorithms
– This may reduce the depth of the quantum computation due to
parallelisation
A two qubit quantum processor created at Yale University in 2009
4Automatic Parallelisation of Quantum Circuits
What we did not do
• Quantum computers do not exist yet
• This was a theoretical project
• No quantum computation was done in this project
A two qubit quantum processor created at Yale University in 2009
5Automatic Parallelisation of Quantum Circuits
Quantum Circuit
• Quantum Circuit is a model of quantum computation
• Qubits are represented by horizontal wires
• Operations on the qubits are represented as gates
6Automatic Parallelisation of Quantum Circuits
Quantum Circuit
• Quantum Circuit is a model of quantum computation
• Qubits are represented by horizontal wires
• Operations on the qubits are represented as gates
• The gates are applied sequentially from left to right
• Gates on the distinct qubits can be applied in parallel
7Automatic Parallelisation of Quantum Circuits
Project Goal
• Transform a quantum circuit to an equivalent quantum circuit
whose depth is less than or equal to the original depth
8Automatic Parallelisation of Quantum Circuits
The parallelisation process
• Translation to the Measurement Based Quantum Computing
(MBQC) model
• Optimisations on MBQC representation
– Standardisation– Signal sifting– Pauli resetting
• Translation back to quantum circuit
• Optimisations on the final circuit
• Result:
– In general the depth of the circuit increases by a log(n) factor– For some circuits the computational depth decreases
9Automatic Parallelisation of Quantum Circuits
A new algorithm
• Translation to MBQC model
• Optimisations on MBQC representation
– Standardisation– Signal sifting– Pauli resetting
• Translation back to quantum circuit
• Optimisations on the final circuit
• We created a new iterative algorithm that translates the
quantum circuits to MBQC model and optimises them
– Runtime O(n³)
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Automatic Parallelisation of Quantum Circuits
Experiments with the program
• The Toffoli staircase circuit
– Depth will decrease by a constant amount
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Automatic Parallelisation of Quantum Circuits
Experiments with the program
• The Toffoli + CNOT staircase circuit
– The depth of the parallelised circuit will be
constant
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Automatic Parallelisation of Quantum Circuits
Experiments with the program
• A new set of gates
– Every circuit consisting of only the following gates:– The CNOT gate– The ∧Z gate– The ω gate– The phase gate Z(α)– The J(-π/2) gate
– These circuits can be parallelise to a logarithmic depth
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Automatic Parallelisation of Quantum Circuits
Results
• A program for automatic parallelisation of quantum circuits
was created
• A new O(n³) algorithm for translating the quantum circuits to
an optimised MBQC computation was designed
• Three new classes of quantum circuits that could benefit
from the implemented parallelisation method were found
– The Toffoli circuit– The Toffoli + CNOT circuit– A set of gates consisting of CNOT, ∧Z, ω, Z(α), J(-π/2) gates