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| </math></center> | | </math></center> |
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| == Feynman-Kac foruma== | | == Feynman-Kac formula== |
| Let's derive the Feyman Kac formula for <math>Z(x,t)</math> in the general case: | | Let's derive the Feyman Kac formula for <math>Z(x,t)</math> in the general case: |
| * First, focus on free paths and introduce the following probability | | * First, focus on free paths and introduce the following probability |
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| The initial condition is <math> Z[x,t=0]=\delta(x) </math>.
| | |
| This equation is a diffusive equation with multiplicative noise. The EW of the previous lecture is a diffusive equation with additive noise. The Cole Hopf transformation allows to map the diffusive equation with multiplicative noise in a non-linear equation with additive noise: the KPZ euqation. Hence, all KPZ results can be used for the directed polymer. | | ===Remarks=== |
| | <Strong>Remark 1:</Strong> |
| | |
| | This equation is a diffusive equation with multiplicative noise. Edwards Wilkinson is instead a diffusive equation with additive noise. The Cole Hopf transformation allows to map the diffusive equation with multiplicative noise in a non-linear equation with additive noise. We will apply this tranformation and have a surprise. |
| | |
| | <Strong>Remark 1:</Strong> |
| | This hamiltonian is time dependent because of the multiplicative noise <math>V(x,\tau)/T</math>. For a <Strong> time independent </Strong> hamiltonian, we can use the spectrum of the operator. In general we will have to parts: |
| | * A Discrete set of eignvalues <math>E_n</math> with the eigenstates <math>\psi_n(x)</math> |
| | * A continuum part where states <math>\psi_E(x)<math> of energy <math>E</math> are characterized by a density of states <math>\rho(E)</math>. |
| | In this case <math> Z[x,t] </math> can be written has the sum of two contributions: |
| | <center> <math> |
| | Z[x,t] = \left( e^{- \hat H t} \right)_{0 \to x}= \sum_n \psi_n(0) \psi_n^*(x) e^{- E_n t} + \int dE \, \rho(E) \psi_E(0) \psi_E^*(x) e^{- E t}. |
| | </math> |
| | </center> |
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| == Cole Hopf Transformation== | | == Cole Hopf Transformation== |
Goal: This lecture is dedicated to a classical model in disordered systems: the directed polymer in random media. It has been introduced to model vortices in superconductur or domain wall in magnetic film. We will focus here on the algorithms that identify the ground state or compute the free energy at temperature T, as well as, on the Cole-Hopf transformation that map this model on the KPZ equation.
Polymers, interfaces and manifolds in random media
We consider the following potential energy
The first term represents the elasticity of the manifold and the second term is the quenched disorder, due to the impurities. In general, the medium is D-dimensional, the internal coordinate of the manifold is d-dimensional and the height filed is N-dimensional. Hence,the following equations always holds:
In practice, we will study two cases:
- Directed Polymers (
),
. Examples are vortices, fronts...
- Elastic interfaces (
),
. Examples are domain walls...
Today we restrict to polymers. Note that they are directed because their configuration
is uni-valuated.
It is useful to study the model using the following change of variable
Directed polymers
Dijkstra Algorithm and transfer matrix
Sketch of the discrete Directed Polymer model. At each time the polymer grows either one step left either one step right. A random energy

is associated at each node and the total energy is simply
![{\displaystyle E[x(\tau )]=\sum _{\tau =0}^{t}V(\tau ,x)}](https://wikimedia.org/api/rest_v1/media/math/render/svg/93b0356dd1c49f25c798e141e27a40d486be2bfe)
.
We introduce a lattice model for the directed polymer (see figure). In a companion notebook we provide the implementation of the powerful Dijkstra algorithm.
Dijkstra allows to identify the minimal energy among the exponential number of configurations
We are also interested in the ground state configuration
.
For both quantities we expect scale invariance with two exponents
for the energy and for the roughness
Universal exponents: Both
are Independent of the lattice, the disorder distribution, the elastic constants, or the boudanry conditions. Note that
, while for an interface
.
Non-universal constants:
are of order 1 and depend on the lattice, the disorder distribution, the elastic constants... However
is independent on the boudanry conditions!
Universal distributions:
are instead universal, but depends on the boundary condtions. Starting from 2000 a magic connection has been revealed between this model and the smallest eigenvalues of random matrices. In particular I discuss two different boundary conditions:
- Droplet:
. In this case, up to rescaling,
is distributed as the smallest eigenvalue of a GUE random matrix (Tracy Widom distribution
)
- Flat:
while the other end
is free. In this case, up to rescaling,
is distributed as the smallest eigenvalue of a GOE random matrix (Tracy Widom distribution
)
Entropy and scaling relation
It is useful to compute the entropy
From which one could guess from dimensional analysis
We will see that this relation is actually exact.
Back to the continuum model
Let us consider polymers
of length
, starting in
and ending in
and at thermal equlibrium at temperature
. The partition function of the model writes as
For simplicity, we assume a white noise,
. Here, the partition function is written as a sum over all possible paths, corresponding to all possible polymer configurations that start at
and end at
, weighted by the appropriate Boltzmann factor.
Polymer partition function and propagator of a quantum particle
Let's perform the following change of variables:
. We also identifies
with
and
as the fine time.
Note that
is the classical action of a particle with kinetic energy
and time dependent potential
, evolving from time zero to time
.
From the Feymann path integral formulation,
is the propagator of the quantum particle.
In absence of disorder, one can find the propagator of the free particle, that, in the original variables, writes:
Feynman-Kac formula
Let's derive the Feyman Kac formula for
in the general case:
- First, focus on free paths and introduce the following probability
- Second, the moments generating function
- Third, the backward approach. Consider free paths evolving up to
and reaching
:
Here
is the average over all free paths, while
is the average over the last jump, namely
and
.
- At the lowest order we have
Replacing
we obtain the partition function is the solution of the Schrodinger-like equation:
Remark 1:
This equation is a diffusive equation with multiplicative noise. Edwards Wilkinson is instead a diffusive equation with additive noise. The Cole Hopf transformation allows to map the diffusive equation with multiplicative noise in a non-linear equation with additive noise. We will apply this tranformation and have a surprise.
Remark 1:
This hamiltonian is time dependent because of the multiplicative noise
. For a time independent hamiltonian, we can use the spectrum of the operator. In general we will have to parts:
- A Discrete set of eignvalues
with the eigenstates 
- A continuum part where states
are characterized by a density of states
.
In this case
can be written has the sum of two contributions:
Cole Hopf Transformation
Replacing




You get
The KPZ equation!
We can establish a KPZ/Directed polymer dictionary, valid in any dimension. Let us remark that the free energy of the polymer is
At low temperature, the free energy approaches the ground state energy,
.
Dictionary
KPZ |
KPZ exponents |
Directed polymer |
Directed polymer exponents
|
 |
 |
 |
|
 |
 |
 |
|
 |
 |
 |
|
We conclude that
Moreover, the scaling relation
is a reincarnation of the Galilean invariance
.