New concepts emerging from a linear response theory for nonequilibrium · 2017-06-06 · New...
Transcript of New concepts emerging from a linear response theory for nonequilibrium · 2017-06-06 · New...
New concepts emerging from a linear response theory for
nonequilibriumMarco Baiesi!
Physics and Astronomy Department “Galileo Galilei”, !University of Padova, and INFN!
!in collaboration with Christian Maes, Urna Basu,!
Eugenio Lippiello, Alessandro Sarracino, Bram Wynants, Eliran Boksenbojm
GGI Workshop, 26-30 May, 2014
Overview
Linear response!
Linear response to temperature kicks!
Entropy production and something else!
Time-symmetric quantities: how many?
A macroscopic FPU?
Livia Conti, Lamberto Rondoni, et al: www.rarenoise.lnl.infn.it
Linear response for FPU?
How does a Fermi-Pasta-Ulam chain react to a change in one temperature?!
Nonequilibrium specific heat variance of the energy!
Compressibility in nonequilibrium?
6=
Fluctuation-Dissipation Th.: Kubo!
An observable A(t) reacts to the appearance of a potential V(s)!
is the entropy production from -V
dhA(t)idhs
=1
T
d
dshA(t)V (s)i E ! E � hsV
1
T
d
dsV (s)
Out of equilibrium: many FDT
a1) perturb the density of states and evolve (Agarwal, Vulpiani & C, Seifert & Speck, Parrondo &C,…) !
a2) “bring back” the observable to the perturbation (Ruelle)!
b) probability of paths (Cugliandolo &C, Harada-Sasa, Lippiello &C, Ricci-Tersenghi, Chatelain, Maes, …)!
short review: Baiesi & Maes, New J. Phys. (2013)
Path probability (Markov),
Overdamped Langevin!
!
Discrete states C, C’, …with jump rates
! ! {xs} for 0 s t
dxs = µF (s) ds+p
2µT dBs
W (C ! C 0)
Diffusion
Probability of a sequence dx0, dx1, dx2, . . .
dPi = (2⇡dt)�1/2exp
⇢(dBi)
2
2dt
�
= (4⇡µTdt)
�1/2exp
⇢[dxi � µF (i)]
2
4µTdt
�
P (!) = limdt!0
⇧idPi
Diffusion + perturbation
Perturbation changes the path probability!
Ratio of path probabilities is finite for
dxs = µF (s) ds+hsµ@V
@x
(s)ds+p
2µT dBs
dt ! 0
Ph(!)
P (!)
Susceptibility (h>0 for s>0)
Susceptibility
hA(t)ih � hA(t)i =⌧A(t)
Ph(!)
P (!)� 1
��
�AV (t) = limh!0
hA(t)ih � hA(t)ih
Generator
Ph(!)
P (!)= exp
⇢h
2T[V (t)� V (0)]� h
2T
Z t
0LV (s)ds
�
Markov generator
In this case: L = µF
@
@x
+ µT
@
2
@x
2
hLV i = d
dthV i
LV (x) =
⌧dV
dt
�����x
interpret as expected variation:
Response function
1/2 entropy production !
minus 1/2 “expected” entropy production
�AV (t) =
Z t
0RAV (t, s)ds
RAV (t, s) =1
2T
d
dshV (s)A(t)i � hLV (s)A(t)i
�
Response function
�AV (t) =
Z t
0RAV (t, s)ds
RAV (t, s) =1
2T
d
dshV (s)A(t)i � hLV (s)A(t)i
�
Entropic term Frenetic term
Baiesi, Maes, Wynants, PRL (2009) !Lippiello, Corberi, Zannetti, PRE (2005) !
Negative response
The sum of the two terms may be <0!
!
Example: negative mobility for strong forces
Baerts, Basu, Maes, Safaverdi, PRE (2013)!
RAV (t, s) =1
2T
d
dshV (s)A(t)i � hLV (s)A(t)i
�
Negative mobility
The structure of R(t,s) is different for inertial systems!
Achieved in a standard path-space comparison, with different drift terms (Radon-Nicodym derivative, Girsanov Th.)
dxs = µF (s) ds+p
2µT dBs
The structure of R(t,s) is different for inertial systems!
Achieved in a standard path-space comparison, with different drift terms (Radon-Nicodym derivative, Girsanov Th.)
What happens if we change the noise term?
dxs = µF (s) ds+p
2µT dBs
Mathematical problem
The response to T kicks involves changing the noise term!!
not well defined for different noises!
However: we are interested in the limit h—> 0
Ph(!)
P (!)
T(1+h), small deviation from T
dP
ht
dPt= (2⇡T (1 + h)dt)
�1/2exp
⇢� [dxt � µF (t)dt]
2
4µT (1 + h)dt
)
�/dPt
= exp
⇢h
2T
�T +
(dxt)2
2µdt
+
µ
2
F
2(t)dt+ µT
@F
@x
(t)dt� F (t) � dxt
��
= exp
⇢h
2
[dS �BS dt] +h
2
[dM �BM dt]
�
Dangerous term (mathematically)
entropy production, !as before new terms
Four terms:
Entropy production!
Expected entropy production!
!
!
Activity (?)!
Expected activity (?)
dS(t) =dQ(t)
T
= � 1
T
F (t) � dxt
BS(t)dt = � µ
T
F
2(t) + T
dF
dx
(t)
�dt
dM(xt) ⌘1
T
(dxt)2
2µdt� T
�
BM (t)dt ⌘ hdMi (xt) =µ
2TF
2(t)dt
[Sekimoto, Stochastic Energetics]
heat flux / temperature
Four terms:
Entropy production!
Expected entropy production!
!
!
Activity (?)!
Expected activity (?)
dS(t) =dQ(t)
T
= � 1
T
F (t) � dxt
BS(t)dt = � µ
T
F
2(t) + T
dF
dx
(t)
�dt
dM(xt) ⌘1
T
(dxt)2
2µdt� T
�
BM (t)dt ⌘ hdMi (xt) =µ
2TF
2(t)dt
[Sekimoto, Stochastic Energetics]
heat flux / temperature
Time symmetric
Dynamical activity
Very relevant in kinetically constrained models!
Count the number of jumps between states!
time-symmetric quantity
! Lecomte, Appert-Rolland, van Wijland, PRL (2005) !! Merolle, Garrahan, D. Chandler, PNAS (2005) !
Relation with activity
The (dx)^2 term should scale as the number of successful jumps in an underlying random walk description
Susceptibility
�A(t) =1
2T
⌧A(t)
hS(t)�
Z t
0BS(s)ds+M(t)�
Z t
0BM (s)ds
i�
antisymmetric!(entropy produced) symmetric terms!
(frenetic contributions + activity)
Susceptibility
Example: harmonic spring
Susceptibility of the internal energy
Inertial dynamics!
Harada-Sasa/stochastic energetics for the entropy production terms
T dS(xt, vt) = mvt � dvt � F (xt)vtdt
T BS(xt, vt) =�
m
[T �mv
2t ]
dxt = vtdt
mdvt = F (xt)dt� �vtdt+p
2�T dBt
Harada-Sasa for transients/jumps: Lippiello, Baiesi, Sarracino, PRL (2014)
Inertial dynamics
T dM(xt, vt) =(mdvt)2
2�dt� T � m
�
F (xt)dvt
T BM (xt, vt) =�
2
"v
2t �
✓F (xt)
�
◆2#
�A(t) =1
2T
⌧A(t)
hS(t)�
Z t
0BS(s)ds+M(t)�
Z t
0BM (s)ds
i�
antisymmetric symmetric terms
Susceptibility
Conclusions
General scheme: probability of trajectories -> physics!
Time-symmetric quantities in response formulas!
Not only dissipation, but also “activation”!
Name(s): dynamical activity, frenesy, traffic, … !
Attempt to compare trajectories with different T