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authorJaron Kent-Dobias <jaron@kent-dobias.com>2020-12-07 17:02:21 +0100
committerJaron Kent-Dobias <jaron@kent-dobias.com>2020-12-07 17:02:21 +0100
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Merge branch 'master' of https://git.overleaf.com/5fcce4736e7f601ffb7e1484
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@@ -96,7 +96,8 @@ $N \Sigma=
\overline{\ln \mathcal N_J} = \int dJ \; \ln N_J$, a calculation that involves the replica trick. In most, but not all, of the parameter-space that we shall study here, the {\em annealed approximation} $N \Sigma \sim
\ln \overline{ \mathcal N_J} = \ln \int dJ \; N_J$ is exact.
-A useful propert
+A useful property of the Gaussian distributions is that gradient and Hessian may be seen to be independent \cite{BrayDean,Fyodorov},
+so that we may treat the delta-functions and the hessians as independent
}