FINITE SIZE SCALING ANALYSIS OF ISING-MODEL BLOCK DISTRIBUTION-FUNCTIONS
FINITE SIZE SCALING ANALYSIS OF ISING-MODEL BLOCK DISTRIBUTION-FUNCTIONS
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DOI:
10.1007/bf01293604
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发表时间:
1981-01-01
期刊:
影响因子:
--
通讯作者:
BINDER, K
中科院分区:
文献类型:
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作者:
BINDER, K
The distribution functionPL(s)of the local order parameters in finite blocks of linear dimensionLis studied for Ising lattices of dimensionalityd=2, 3 and 4. Apart from the case where the block is a subsystem of an infinite lattice, also the distribution in finite systems with free [PL(f)(s)] and periodic [PL(p)(s)] boundary conditions is treated. Above the critical pointTc, these distributions tend for largeLtowards the same gaussian distribution centered around zero block magnetization, while belowTcthese distributions tend towards two gaussians centered at ±M, whereMis the spontaneous magnetization appearing in the infinite systems. However, belowTcthe wings of the distribution at small |s| are distinctly nongaussian, reflecting two-phase coexistence. Hence the distribution functions can be used to obtain the interface tension between ordered phases.At criticality, the distribution functions tend for largeLtowards scaled universal forms, though dependent on the boundary conditions. These scaling functions are estimated from Monte Carlo simulations. For subsystem-blocks, good agreement with previous renormalization group work of Bruce is obtained.As an application, it is shown that Monte Carlo studies of critical phenomena can be improved in several ways using these distribution functions:(i)standard estimates of order parameter, susceptibility, interface tension are improved(ii) Tccan be estimated independent of critical exponent estimates(iii)A Monte Carlo “renormalization group” similar to Nightingale's phenomenological renormalization is proposed, which yields fairly accurate exponent estimates with rather moderate effort(iv)Information on coarse-grained hamiltonians can be gained, which is particularly interesting if the method is extended to more general Hamiltonians.