A measure of data collapse for scaling

By S. M. Bhattacharjee, Flavio Seno. 2001

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Data collapse is a way of establishing scaling and extracting associated exponents in problems showing self-similar or self-affine characteristics as, for example, 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.

Subfields: Condensed Matter Physics, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/81a754b7717c85dbc3caca818dc3866efaef6237