Computer Simulation Studies in Condensed-Matter Physics IX: by D. P. Landau, K. K. Mon, H.-B. Schüttler (auth.), Professor
By D. P. Landau, K. K. Mon, H.-B. Schüttler (auth.), Professor David P. Landau Ph. D., Professor K. K. Mon Ph. D., Professor Heinz-Bernd Schüttler Ph. D. (eds.)
Computer Simulation reviews in Condensed-Matter Physics IX covers contemporary advancements during this box. those lawsuits shape a checklist of the 9th workshop during this sequence and are released with the objective of well timed dissemination of the fabric to a much broader viewers. the 1st part includes invited papers that take care of simulational reviews of classical platforms. the second one part of the court cases is dedicated to invited papers on quantum structures, together with new effects for strongly correlated electron and quantum spin versions. the ultimate part contains contributed presentations.
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Additional resources for Computer Simulation Studies in Condensed-Matter Physics IX: Proceedings of the Ninth Workshop Athens, GA, USA, March 4–9, 1996
In this paper, we assume the functional form of w does not depend on the loeal unit u for the simplieity's sake, though the generalization to non-uniform eases is trivial. Here we introduee an auxiliary variable G( u) on eaeh loeal unit, and also define a delta function ß(S(u),G(u» whieh takes two values 0 and 1. We eaIl G( u) a local graph beeause it indeed corresponds to a graph in a typical applieation. Although we ean define these things as we like, the effieieney of the resulting algorithm strongly depends on those.
154 displays the signature of the hexatic phase: there is only short-range order in the pair distribution function, but the orientational correlation function decays algebraically. 02, which is less than the upper limit of 1/4 predicted by KTHNY. Although a mixed solidliquid coexistence region is unlikely to occur in an NPT simulation, we have done finite-size scaling analysis ofthe bond-angular susceptibility in subgrids of the 36864 atom sampie. All three phases observed as the temperature changes appear to be homogeneous.
We then consider the following three cases: 1) K 2+Ka+K4 ~ Kl, 2) K 2+Ka -K4 ~ K 1 ~ K2+Ka+K4, and 3) K 1 ~ K 2+ K a -K4. ) In general, we should minimize the weights for G("l1) which are proportional to the 'freezing probability'. However, in the case 1), it is easy to see that no solution exists for which a(ll) is zero. This means that a loop algorithm solution does not exist. The best we can seek, therefore, is a solution in which 51 a(22) = a(33) = a(44) = O. Among such solutions, the one that minimizes a(U) IS a(U) = K 1 - K 2 - K 3 - K 4 , a(lu) = Ku (for u = 2,3,4), (24) with all other a's vanishing.