A Measure of data-collapse for scaling
arXiv:cond-mat/0102515 · doi:10.1088/0305-4470/34/33/302
Abstract
Data-collapse is a way of establishing scaling and extracting associated exponents in problems showing self-similar or self-affine characteristics as e.g. in equilibrium or non-equilibrium phase transitions, in critical phases, in dynamics of complex systems and many others. We propose a measure to quantify the nature of data collapse. Via a minimization of this measure, the exponents and their error-bars can be obtained. The procedure is illustrated by considering finite-size-scaling near phase transitions and quite strikingly recovering the exact exponents.
3 pages, revtex, 3 figures,2 in colour. Replaced by the proper version - slightly longer and no mismatch of abstract
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