Update on Overleaf.

1 files changed, 2 insertions, 2 deletions

diff --git a/bezout.tex b/bezout.tex
index 753b65b..702f1ae 100644
--- a/bezout.tex
+++ b/bezout.tex
@@ -39,14 +39,14 @@ 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 \cite{crisanti1992sphericalp} 
+The most tractable family of these  are the mean-field spherical p-spin models \cite{crisanti1992sphericalp} (for a review see \cite{castellani2005spin})
 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}
+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\cite{crisanti1992sphericalp}, a Kac--Rice \cite{Kac_1943_On,