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arXiv 0810.2719cond-mat.stat-mech
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对数修正的Fisher重整化

Fisher Renormalization for Logarithmic Corrections

Ralph Kenna, Hsiao-Ping Hsu, Christian von Ferber

摘要:

对于具有幂律发散特征的连续相变,Fisher重整化给出了如何从理想系统中得到系统的临界指数。在统计力学中,这种在相变时的理想行为经常被乘法对数修正所修正。在这里,Fisher重整化的指数,这些矩阵是在一般的方式。对于前导指数,对数水平的Fisher重整化被认为是对合的,重整化指数服从与其理想类似物相同的标度关系。该计划在晶格动物和杨-李问题在其上临界尺寸,对数修正的预测进行了测试。

英文摘要:

For continuous phase transitions characterized by power-law divergences, Fisher renormalization prescribes how to obtain the critical exponents for a system under constraint from their ideal counterparts. In statistical mechanics, such ideal behaviour at phase transitions is frequently modified by multiplicative logarithmic corrections. Here, Fisher renormalization for the exponents of these logarithms is developed in a general manner. As for the leading exponents, Fisher renormalization at the logarithmic level is seen to be involutory and the renormalized exponents obey the same scaling relations as their ideal analogs. The scheme is tested in lattice animals and the Yang-Lee problem at their upper critical dimensions, where predictions for logarithmic corrections are made.

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