Update on Overleaf.

1 files changed, 2 insertions, 1 deletions

diff --git a/bezout.tex b/bezout.tex
index 573fe90..a29cd4b 100644
--- a/bezout.tex
+++ b/bezout.tex
@@ -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 property 
+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
 
 }