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== Quenched vs annealed, and the replica trick==
== Quenched vs annealed, and the replica trick==
In Problems 1 and 2, we defined the <ins>quenched free energy</ins> as the quantity controlling the scaling of the typical value of the partition function <math>Z </math>, which means:  
In Problems 1 and 2, we defined the <ins>quenched free energy</ins> as the physically relevant quantity controlling the scaling of the typical value of the partition function <math>Z </math>, which means:  
<center><math>
 
f= -\lim_{N \to \infty} \frac{1}{\beta N} \overline{ \log Z}.
<math display="block">
</math></center>
f= -\lim_{N \to \infty} \, \frac{1}{\beta N} \, \mathbb{E}[ \log Z].
</math>
 
The <ins>annealed free energy</ins> <math>f_{\text{a}} </math> instead controls the scaling of the average value of  <math>Z </math>, and it is defined by
<math display="block">
f_{\text{a}} = -\lim_{N \to \infty}\, \frac{1}{\beta N} \,\log \mathbb{E}[Z].
</math>
These formulas differ by the order in which the logarithm and the average over disorder are taken.
 


The <ins>annealed free energy</ins> <math>f_{\text{a}} </math> instead controls the scaling of the average value of <math>Z </math>. It is defined by
For the REM, because of the simplicity of the model  we could compute the quenched free-energy by computing the typical value of the number of configurations with a given energy. This can not be done in general, and one has to resort to the computation of the average of the logarithm, which is a hard problem. To address it, one can use a smart representation of the logarithm, that goes under the name of <ins>replica trick</ins>:   
<center><math>
<math display="block">
f_{\text{a}} = -\lim_{N \to \infty} \frac{1}{\beta N} \log \overline{Z}.
\log x= \lim_{n \to 0} \, \frac{x^n-1}{n}, \quad \quad x>0
</math></center>
</math>
These formulas differ by the order in which the logarithm and the average over disorder are taken. Computing the average of the logarithm is in general a hard problem, which one can address by using a smart representation of the logarithm, that goes under the name of <ins>replica trick</ins>:   
which can be easily shown to be true by Taylor expanding <math>x^n= e^{n \log x}= 1+ n \log x+ O(n^2) </math>. Applying this to the average of the partition function, we see that
<center><math>
<math display="block">
\log x= \lim_{n \to 0} \frac{x^n-1}{n}
f= -\lim_{N \to \infty} \lim_{n \to 0}\,\frac{1}{\beta N }\, \frac{\mathbb{E}[Z^n]-1}{n}.
</math></center>
</math>
which can be easily shown to be true by Taylor expanding <math>x^n= e^{n \log x}= 1+ n\log x+ O(n^2) </math>. Applying this to the average of the partition function, we see that
Therefore, to compute the quenched free-energy we need to compute the moments <math>\mathbb{E}[Z^n]</math> and then take the limit  <math>n \to 0</math>. The calculations in the following Problems rely on this replica trick. The annealed one only requires to do the calculation with <math>n=1</math>.
<center><math>
f= -\lim_{N \to \infty} \lim_{n \to 0}\frac{1}{\beta N } \frac{\overline{Z^n}-1}{n}.
</math></center>
Therefore, to compute the quenched free-energy we need to compute the moments <math>{\overline{Z^n}}</math> and then take the limit  <math>n \to 0</math>. The calculations in the following Problems rely on this replica trick. The annealed one only requires to do the calculation with <math>n=1</math>.
<br><br>
<br><br>


== Problems==
== The spherical p-spin model ==
In this and the following set of problems, we analyse a mean-field model that is slightly more complicated than the REM: the spherical <math>p</math>-spin model. In the spherical <math>p</math>-spin model the configurations <math> \vec{\sigma}=(\sigma_1, \cdots, \sigma_N) </math> satisfy the spherical constraint <math> \sum_{i=1}^N \sigma_i^2=N </math>, and the energy associated to each configuration is  
We discuss the Replica formalism for a mean-field model that is slightly more complicated than the REM: the spherical <math>p</math>-spin model. In the spherical <math>p</math>-spin model the configurations <math> \vec{\sigma}=(\sigma_1, \cdots, \sigma_N) </math> satisfy the spherical constraint <math> \sum_{i=1}^N \sigma_i^2=N </math>, and the energy associated to each configuration is  
<center>
<math display="block">
<math>
E(\vec{\sigma}) =\sum_{1 \leq i_1 <i_2 <\cdots i_p \leq N} J_{i_1 \,i_2 \cdots i_p} \sigma_{i_1} \sigma_{i_2} \cdots \sigma_{i_p},  
E(\vec{\sigma}) =\sum_{1 \leq i_1 \leq i_2 \leq \cdots i_p \leq N} J_{i_1 \,i_2 \cdots i_p} \sigma_{i_1} \sigma_{i_2} \cdots \sigma_{i_p},  
</math>
</math></center>
where the coupling constants <math>J_{i_1 \,i_2 \cdots i_p}</math> are independent random variables with Gaussian distribution with zero mean and variance <math> p!/ N^{p-1},</math> and <math> p \geq 3</math> is an integer.
where the coupling constants <math>J_{i_1 \,i_2 \cdots i_p}</math> are independent random variables with Gaussian distribution with zero mean and variance <math> p!/ N^{p-1},</math> and <math> p \geq 3</math> is an integer.


<br>
== Problems==


=== Problem 3.1: correlations, p-spin vs REM ===
<!-- === Problem 3.1: correlations, p-spin vs REM ===
<br>
<br>
At variance with the REM, in the spherical <math>p</math>-spin the energies at different configurations are correlated. Show that  
At variance with the REM, in the spherical <math>p</math>-spin the energies at different configurations are correlated. Show that  
<center><math>
<math display="block">
\overline{E(\vec{\sigma}) E(\vec{\sigma}')}= N \, q(\vec{\sigma}, \vec{\sigma}')^p + O(1) , \quad \quad \text{where} \quad \quad q(\vec{\sigma}, \vec{\sigma}')= \frac{1}{N}\sum_{i=1}^N \sigma_i \sigma'_i </math></center>  
\overline{E(\vec{\sigma}) E(\vec{\tau})}= N \, q(\vec{\sigma}, \vec{\tau})^p + o(N) , \quad \quad \text{where} \quad \quad q(\vec{\sigma}, \vec{\tau})= \frac{1}{N}\sum_{i=1}^N \sigma_i \tau_i
is the overlap between the two configurations. Why can we say that for <math>p \to \infty </math> this model converges with the REM discussed in the previous lecture?
</math>
<br>
is the overlap between the two configurations. Why can we say that for <math>p \to \infty </math> this model converges with the REM?
<br>-->


=== Problem 3.2, DO IT YOURSELF: the annealed free energy ===
<!--=== Problem 3.2: the annealed free energy ===
As a preliminary exercise, we compute the annealed free energy of the spherical <math>p</math>-spin model.  
As a preliminary exercise, we compute the annealed free energy of the spherical <math>p</math>-spin model.  


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This result is only slightly different with respect to the annealed free-energy of the REM: can you identify the source of this difference? </li>
This result is only slightly different with respect to the annealed free-energy of the REM: can you identify the source of this difference? </li>
</ol>
</ol>
<br>
<br>-->


=== Problem 3.3: the replica trick and the quenched free energy ===
=== Problem 3: the replica trick and the quenched free energy ===
In this Problem, we set up the replica calculation of the quenched free energy. This will be done in 3 steps, that are general in each calculation of this type.
In this Problem, we set up the replica calculation of the quenched free energy. This will be done in 3 steps, that are general in each calculation of this type.


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<li> <em> Step 1: average over the disorder.</em> By using the same Gaussian integration discussed above, show that the <math>n</math>-th moment of the partition function is  
<li> <em> Step 1: average over the disorder.</em> By using the same Gaussian integration discussed above, show that the <math>n</math>-th moment of the partition function is  


<center>
<math display="block">
<math>\overline{Z^n}= \int_{S_N} \prod_{a=1}^n d \vec{\sigma}^a e^{\frac{\beta^2}{2} \sum_{a,b=1}^n \left[q({\vec{\sigma}^a, \vec{\sigma}^b})\right]^p}</math></center>
\mathbb{E}[Z^n]= \int_{S_N} \prod_{a=1}^n d \vec{\sigma}^a \; \text{exp}\left({\frac{\beta^2}{2} \sum_{a,b=1}^n \left[q({\vec{\sigma}^a, \vec{\sigma}^b})\right]^p}\right)
</math>


Justify why averaging over the disorder induces a coupling between the replicas.
Justify why averaging over the disorder induces a coupling between the replicas.
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<ol start="2">
<ol start="2">
<li><em> Step 2: identify the order parameter.</em> Using the identity <math> 1=\int dq_{ab} \delta \left( q({\vec{\sigma}^a, \vec{\sigma}^b})- q_{ab}\right) </math>, show that <math>\overline{Z^n}</math> can be rewritten as an integral over <math>n(n-1)/2</math> variables  only, as:
<li><em> Step 2: identify the order parameter.</em> Using the identity <math> 1=\int dq_{ab}\, \delta \left( q({\vec{\sigma}^a, \vec{\sigma}^b})- q_{ab}\right) </math>, show that <math>\mathbb{E}[Z^n]</math> can be rewritten as an integral over <math>n(n-1)/2</math> variables  only, as:


<center>
<math display="block">
<math>\overline{Z^n}= \int \prod_{a<b} d q_{ab} e^{\frac{N\beta^2}{2} \sum_{a,b=1}^n q_{ab}^p+ \frac{Nn}{2} \log (2 \pi e) + \frac{N}{2} \log \det Q+ o(N)} \equiv \int \prod_{a<b} d q_{ab} e^{N \mathcal{A}[Q]+ o(N)}, \quad \quad Q_{ab} \equiv \begin{cases}
\mathbb{E}[Z^n]= \int \prod_{a<b} d q_{ab} e^{\frac{N\beta^2}{2} \sum_{a,b=1}^n q_{ab}^p+ \frac{Nn}{2} \log (2 \pi e) + \frac{N}{2} \log \det Q+ o(N)} \equiv \int \prod_{a<b} d q_{ab} e^{N \mathcal{A}[Q]+ o(N)}, \quad \quad Q_{ab} \equiv \begin{cases}
&q_{ab} \text{ if  } a <b\\
&q_{ab} \text{ if  } a <b\\
&1 \text{ if  } a =b\\
&1 \text{ if  } a =b\\
&q_{ba}\text{ if  } a >b
&q_{ba}\text{ if  } a >b
\end{cases}</math></center>
\end{cases}</math>
 
In the derivation, you can use the fact that
In the derivation, you can use the fact that
<math>
<math>
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<li><em> Step 3: the saddle point (RS).</em> For large N, the integral can be computed with a saddle point approximation for general <math>n</math>. The saddle point variables are the matrix elements <math> q_{ab}</math> with <math> a \neq b</math>. Show that the saddle point equations read
<li><em> Step 3: the saddle point (RS).</em> For large N, the integral can be computed with a saddle point approximation for general <math>n</math>. The saddle point variables are the matrix elements <math> q_{ab}</math> with <math> a \neq b</math>. Show that the saddle point equations read


<center><math>
<math display="block">
\frac{\partial \mathcal{A}[Q]}{\partial q_{ab}}=\frac{\beta^2}{2}p q_{ab}^{p-1}+ \frac{1}{2} \left(Q^{-1}\right)_{ab} \Big|_{Q=Q^*}=0 \quad \quad \text{for } \quad a \neq b,
\frac{\partial \mathcal{A}[Q]}{\partial q_{ab}}=\beta^2\, p q_{ab}^{p-1}+ \left(Q^{-1}\right)_{ab} \Big|_{Q=Q^*}=0 \quad \quad \text{for } \quad a <b,
</math></center>
</math>
where we called <math> Q^* </math> the value at which the saddle point is attained.
where we called <math> Q^*=(Q_{ab}^*) </math> the value at which the saddle point is attained.
To solve these equations and get the free energy, one first needs to make an assumption on the structure of the matrix <math> Q</math>, i.e., on the space where to look for the saddle point solutions. We discuss this in the next set of problems.
To solve these equations and get the free energy, one first needs to make an assumption on the structure of the matrix <math> Q</math>, i.e., on the space where to look for the saddle point solutions. We discuss this in the next set of problems.
</li>
</li>
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<br>
<br>


== The information encode in the saddle-point: a first hint==
== The physics within the replica formalism: a first hint==
The problems above show that within the replica formalism, the overlaps emerge naturally as order parameters of the theory: one derives an effective action <math> \mathcal{A}[Q] </math> which is a function of the overlaps only, like it happens with the magnetization in the mean field treatment of the Ising model. <br>
In Problem 2, we have introduced the overlap distribution, that for the spherical <math> p</math>-spin model takes the form:


In Problem 2, we have introduced the overlap distribution, which for the <math>p</math>-spin would take the form:
<math display="block">
<center>
P_{N, \beta}(q)= \int_{\mathcal{S}_N} d \vec{\sigma} \, \int_{\mathcal{S}_N} d \vec{\tau} \frac{e^{-\beta E(\vec{\sigma})}}{Z}\frac{e^{-\beta E(\vec{\tau})}}{Z}\delta \left(q- q(\vec{\sigma}, \vec{\tau}) \right)
<math>
</math>
P(q)= \int_{\mathcal{S}_N} d \vec{\sigma} \, \int_{\mathcal{S}_N} d \vec{\sigma}' \frac{e^{-\beta E(\vec{\sigma})}}{Z}\frac{e^{-\beta E(\vec{\sigma}')}}{Z}\delta \left(q- q(\vec{\sigma}, \vec{\sigma}') \right)
This is the distribution of overlaps between configurations extracted at equilibrium, in a fixed given realisation of disorder. On the other hand, the problems above show that replicas play exactly this game: they are different configurations of the system, extracted with a Boltzmann weight at a given realisation of the random energy landscape. They serve as probes for capturing correlations between equilibrium configurations. The saddle point solution <math> q_{ab}^* </math> capture precisely the information on the average distribution of overlaps in the system. More precisely, one can show that
<math display="block">
\mathbb{E}[P_\beta(q)]=\lim_{N \to \infty} \mathbb{E}[P_{N, \beta}(q)]=\lim_{n \to 0} \; \frac{2}{n(n-1)}\; \sum_{a>b}\delta \left(q- q_{ab}^{*}\right),
</math>
The solution of the saddle point equations for the overlap matrix <math> Q</math> thus contain the information on whether spin glass order emerges, which corresponds to having a non-trivial distribution <math> \mathbb{E}[P_\beta (q)]</math>. Moreover, the Edwards-Anderson order parameter introduced by Alberto in Lecture 1 can also be read out from the formalism:
<math display="block">
q_{EA}= \max \left\{ q_{a \neq b}^{*} \right\}.
</math>
</math>
</center>
Replicas are


== Check out: key concepts ==
== Check out: key concepts and exercises==


Annealed vs quenched averages, replica trick, fully-connected models, order parameters, the three steps of a replica calculation.
Annealed vs quenched averages, replica trick, fully-connected models, order parameters, the three steps of a replica calculation.<br>
To practice on the calculations, you can do <code>Exercise 9 </code>


== To know more ==
== To know more ==
* Castellani, Cavagna. Spin-Glass Theory for Pedestrians [https://arxiv.org/abs/cond-mat/0505032]
* Castellani, Cavagna. Spin-Glass Theory for Pedestrians [https://arxiv.org/abs/cond-mat/0505032]

Latest revision as of 14:33, 13 February 2026

Goal: use the replica method to compute the quenched free energy of a prototypical mean-field model of glasses, the spherical p-spin model.
Techniques: replica trick, Gaussian integrals, saddle point calculations.


Quenched vs annealed, and the replica trick

In Problems 1 and 2, we defined the quenched free energy as the physically relevant quantity controlling the scaling of the typical value of the partition function Z, which means:

f=limN1βN𝔼[logZ].

The annealed free energy fa instead controls the scaling of the average value of Z, and it is defined by fa=limN1βNlog𝔼[Z]. These formulas differ by the order in which the logarithm and the average over disorder are taken.


For the REM, because of the simplicity of the model we could compute the quenched free-energy by computing the typical value of the number of configurations with a given energy. This can not be done in general, and one has to resort to the computation of the average of the logarithm, which is a hard problem. To address it, one can use a smart representation of the logarithm, that goes under the name of replica trick: logx=limn0xn1n,x>0 which can be easily shown to be true by Taylor expanding xn=enlogx=1+nlogx+O(n2). Applying this to the average of the partition function, we see that f=limNlimn01βN𝔼[Zn]1n. Therefore, to compute the quenched free-energy we need to compute the moments 𝔼[Zn] and then take the limit n0. The calculations in the following Problems rely on this replica trick. The annealed one only requires to do the calculation with n=1.

The spherical p-spin model

We discuss the Replica formalism for a mean-field model that is slightly more complicated than the REM: the spherical p-spin model. In the spherical p-spin model the configurations σ=(σ1,,σN) satisfy the spherical constraint i=1Nσi2=N, and the energy associated to each configuration is E(σ)=1i1<i2<ipNJi1i2ipσi1σi2σip, where the coupling constants Ji1i2ip are independent random variables with Gaussian distribution with zero mean and variance p!/Np1, and p3 is an integer.

Problems

Problem 3: the replica trick and the quenched free energy

In this Problem, we set up the replica calculation of the quenched free energy. This will be done in 3 steps, that are general in each calculation of this type.

  1. Step 1: average over the disorder. By using the same Gaussian integration discussed above, show that the n-th moment of the partition function is 𝔼[Zn]=SNa=1ndσaexp(β22a,b=1n[q(σa,σb)]p) Justify why averaging over the disorder induces a coupling between the replicas.


  1. Step 2: identify the order parameter. Using the identity 1=dqabδ(q(σa,σb)qab), show that 𝔼[Zn] can be rewritten as an integral over n(n1)/2 variables only, as: 𝔼[Zn]=a<bdqabeNβ22a,b=1nqabp+Nn2log(2πe)+N2logdetQ+o(N)a<bdqabeN𝒜[Q]+o(N),Qab{qab if a<b1 if a=bqba if a>b In the derivation, you can use the fact that SNa=1ndσaa<bδ(q(σa,σb)qab)=eNS[Q]+o(N), where S[Q]=nlog(2πe)/2+(1/2)logdetQ. The matrix Q is an order parameter: explain the analogy with the magnetisation in the mean-field solution of the Ising model.


  1. Step 3: the saddle point (RS). For large N, the integral can be computed with a saddle point approximation for general n. The saddle point variables are the matrix elements qab with ab. Show that the saddle point equations read 𝒜[Q]qab=β2pqabp1+(Q1)ab|Q=Q*=0for a<b, where we called Q*=(Qab*) the value at which the saddle point is attained. To solve these equations and get the free energy, one first needs to make an assumption on the structure of the matrix Q, i.e., on the space where to look for the saddle point solutions. We discuss this in the next set of problems.


The physics within the replica formalism: a first hint

In Problem 2, we have introduced the overlap distribution, that for the spherical p-spin model takes the form:

PN,β(q)=𝒮Ndσ𝒮NdτeβE(σ)ZeβE(τ)Zδ(qq(σ,τ)) This is the distribution of overlaps between configurations extracted at equilibrium, in a fixed given realisation of disorder. On the other hand, the problems above show that replicas play exactly this game: they are different configurations of the system, extracted with a Boltzmann weight at a given realisation of the random energy landscape. They serve as probes for capturing correlations between equilibrium configurations. The saddle point solution qab* capture precisely the information on the average distribution of overlaps in the system. More precisely, one can show that 𝔼[Pβ(q)]=limN𝔼[PN,β(q)]=limn02n(n1)a>bδ(qqab*), The solution of the saddle point equations for the overlap matrix Q thus contain the information on whether spin glass order emerges, which corresponds to having a non-trivial distribution 𝔼[Pβ(q)]. Moreover, the Edwards-Anderson order parameter introduced by Alberto in Lecture 1 can also be read out from the formalism: qEA=max{qab*}.

Check out: key concepts and exercises

Annealed vs quenched averages, replica trick, fully-connected models, order parameters, the three steps of a replica calculation.
To practice on the calculations, you can do Exercise 9

To know more

  • Castellani, Cavagna. Spin-Glass Theory for Pedestrians [1]