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authorJaron Kent-Dobias <jaron@kent-dobias.com>2020-12-09 13:23:05 +0100
committerJaron Kent-Dobias <jaron@kent-dobias.com>2020-12-09 13:23:05 +0100
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Merge branch 'master' of https://git.overleaf.com/5fcce4736e7f601ffb7e1484
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@@ -39,12 +39,15 @@ different topological properties.
Spin-glasses have long been considered the paradigm of `complex landscapes' of many variables, a subject that
includes Neural Networks and optimization problems, most notably Constraint Satisfaction ones.
-The most tractable family of these are the mean-field spherical p-spin models defined by the energy:
+The most tractable family of these are the mean-field spherical p-spin models
+
+defined by the energy:
\begin{equation} \label{eq:bare.hamiltonian}
H_0 = \sum_p \frac{c_p}{p!}\sum_{i_1\cdots i_p}^NJ_{i_1\cdots i_p}z_{i_1}\cdots z_{i_p},
\end{equation}
where the $J_{i_1\cdots i_p}$ are real Gaussian variables and the $z_i$ are real and constrained
to a sphere $\sum_i z_i^2=N$. If there is a single term of a given $p$, this is known as the `pure $p$-spin' model, the case we shall study here.
+Also in the algebra \cite{cartwright2013number} and probability literature \cite{auffinger2013complexity,auffinger2013random}
This problem has been attacked from several angles: the replica trick to
compute the Boltzmann--Gibbs distribution, a Kac--Rice \cite{Kac_1943_On,