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| -rw-r--r-- | bezout.tex | 3 |
1 files changed, 2 insertions, 1 deletions
@@ -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 } |