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authorJaron Kent-Dobias <jaron@kent-dobias.com>2022-07-12 16:49:25 +0200
committerJaron Kent-Dobias <jaron@kent-dobias.com>2022-07-12 16:49:25 +0200
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Spelling and abstract.
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+++ b/frsb_kac-rice.tex
@@ -25,9 +25,11 @@
\author{Jaron Kent-Dobias \& Jorge Kurchan}
\maketitle
\begin{abstract}
- We derive the general solution for the computation of stationary points of
+ We derive the general solution for counting the stationary points of
mean-field complex landscapes. It incorporates Parisi's solution
- for the ground state, as it should.
+ for the ground state, as it should. Using this solution, we count the
+ stationary points of two models: one with multi-step replica symmetry
+ breaking, and one with full replica symmetry breaking.
\end{abstract}
\section{Introduction}
@@ -410,7 +412,7 @@ the value of the stability $\mu$ in all replicas to the value $\mu^*$.
\item For $\mu^*<\mu_m$, this amounts to fixing the index density. Since the
overwhelming majority of saddles have a semicircle distribution, the
fluctuations are rarer than exponential.
- \item For the gapped case $\mu^*>\mu_m$, there is a an exponentially small
+ \item For the gapped case $\mu^*>\mu_m$, there is an exponentially small
probability that $r=1,2,...$ eigenvalues detach from the semicircle in such
a way that the index is in fact $N {\cal{I}}=r$. We shall not discuss
these subextensive index fluctuations in this paper, the interested reader
@@ -697,7 +699,7 @@ $\hat\beta=\tilde\beta$, and $C=\tilde Q$.
{\em Therefore a $(k-1)$RSB ansatz in
Kac--Rice will predict the correct ground state energy for a model whose
equilibrium state at small temperatures is $k$RSB } Moreover, there is an
-exact correspondance between the saddle parameters of each. If the equilibrium
+exact correspondence between the saddle parameters of each. If the equilibrium
is given by a Parisi matrix with parameters $x_1,\ldots,x_k$ and
$q_1,\ldots,q_k$, then the parameters $\hat\beta$, $r_d$, $d_d$, $\tilde
x_1,\ldots,\tilde x_{k-1}$, and $c_1,\ldots,c_{k-1}$ for the
@@ -1346,9 +1348,10 @@ global overlap between different states is at most $1/2$. At $\hat \beta>\hat
\subsection{\textit{R} and \textit{D}: response functions}
The matrix field $R$ is related to responses of the stationary points to
-perturbations of the tensors $J$. One adds to the Hamiltonian a random term $\varepsilon \tilde H_p = \varepsilon \sum_{i_1,...,i_p} \tilde J_{i_1,...,i_p} s_{i_1}...s_{i_p}$, where the $\tilde J$ are
-random Gaussian uncorrelated with the $J$'s.
-The response to these is:
+perturbations of the tensors $J$. One adds to the Hamiltonian a random term
+$\varepsilon \tilde H_p = \varepsilon \sum_{i_1,...,i_p} \tilde J_{i_1,...,i_p}
+s_{i_1}...s_{i_p}$, where the $\tilde J$ are random Gaussian uncorrelated with
+the $J$'s. ] The response to these is:
\begin{equation}
\begin{aligned}
& \overline{ \frac{\partial \langle \tilde H_p \rangle_{\tilde J} } {\partial \varepsilon} }
@@ -1454,7 +1457,7 @@ saddles at this transition point.
The authors would like to thank Valentina Ros for helpful discussions.
\paragraph{Funding information}
-J K-D and J K are supported by the Simons Foundation Grant No. 454943.
+JK-D and JK are supported by the Simons Foundation Grant No.~454943.
\printbibliography