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author | kurchan.jorge <kurchan.jorge@gmail.com> | 2020-12-07 16:00:36 +0000 |
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committer | overleaf <overleaf@localhost> | 2020-12-07 16:00:38 +0000 |
commit | 1f2b3de07c9a8b39e32f621b07ee5e19895e46b9 (patch) | |
tree | fbaca0b660cd0187301380dded86a85ae2343168 | |
parent | e173cb736bc07937d61564f303eab5d0b60f62ed (diff) | |
download | PRR_3_023064-1f2b3de07c9a8b39e32f621b07ee5e19895e46b9.tar.gz PRR_3_023064-1f2b3de07c9a8b39e32f621b07ee5e19895e46b9.tar.bz2 PRR_3_023064-1f2b3de07c9a8b39e32f621b07ee5e19895e46b9.zip |
Update on Overleaf.
-rw-r--r-- | bezout.tex | 2 |
1 files changed, 1 insertions, 1 deletions
@@ -96,7 +96,7 @@ $N \Sigma= \overline{\ln \mathcal N_J} = \int dJ \; \ln N_J$, 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 } |