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| author | Jaron Kent-Dobias <jaron@kent-dobias.com> | 2018-05-15 10:58:29 -0400 |
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| committer | Jaron Kent-Dobias <jaron@kent-dobias.com> | 2018-05-15 10:58:29 -0400 |
| commit | a8f8a3fad2d07780c48db7e15036dec5ea8ab90d (patch) | |
| tree | c56d013cdd8fa7ef0912badf0db68766d7d85f68 /prl-paragraph.txt | |
| parent | f18c2b124885a1ba7ed3ebd263da4679c2efed4e (diff) | |
| download | PRE_98_063306-a8f8a3fad2d07780c48db7e15036dec5ea8ab90d.tar.gz PRE_98_063306-a8f8a3fad2d07780c48db7e15036dec5ea8ab90d.tar.bz2 PRE_98_063306-a8f8a3fad2d07780c48db7e15036dec5ea8ab90d.zip | |
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| -rw-r--r-- | prl-paragraph.txt | 1 |
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diff --git a/prl-paragraph.txt b/prl-paragraph.txt new file mode 100644 index 0000000..754692b --- /dev/null +++ b/prl-paragraph.txt @@ -0,0 +1 @@ +Monte Carlo simulations are important pedagogical and research tools in statistical physics. Cluster methods, like Wolff, continue to be important research tools. This paper takes a method little-known to even those as immersed in the subject as Jon Machta for extending cluster algorithms to operate in a field, generalizes it to a broad class of systems and fields, and makes a quantitative test of its efficiency. This fills an much-needed gap in a canonical method. Fast simulations of the Ising model in a field have been essential in recent work on information geometry, universal scaling of correlation functions, and more. |