Literature DB >> 26871142

Turning intractable counting into sampling: Computing the configurational entropy of three-dimensional jammed packings.

Stefano Martiniani1, K Julian Schrenk1, Jacob D Stevenson1,2, David J Wales1, Daan Frenkel1.   

Abstract

We present a numerical calculation of the total number of disordered jammed configurations Ω of N repulsive, three-dimensional spheres in a fixed volume V. To make these calculations tractable, we increase the computational efficiency of the approach of Xu et al. [Phys. Rev. Lett. 106, 245502 (2011)10.1103/PhysRevLett.106.245502] and Asenjo et al. [Phys. Rev. Lett. 112, 098002 (2014)10.1103/PhysRevLett.112.098002] and we extend the method to allow computation of the configurational entropy as a function of pressure. The approach that we use computes the configurational entropy by sampling the absolute volume of basins of attraction of the stable packings in the potential energy landscape. We find a surprisingly strong correlation between the pressure of a configuration and the volume of its basin of attraction in the potential energy landscape. This relation is well described by a power law. Our methodology to compute the number of minima in the potential energy landscape should be applicable to a wide range of other enumeration problems in statistical physics, string theory, cosmology, and machine learning that aim to find the distribution of the extrema of a scalar cost function that depends on many degrees of freedom.

Entities:  

Year:  2016        PMID: 26871142     DOI: 10.1103/PhysRevE.93.012906

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  1 in total

1.  Monte Carlo sampling for stochastic weight functions.

Authors:  Daan Frenkel; K Julian Schrenk; Stefano Martiniani
Journal:  Proc Natl Acad Sci U S A       Date:  2017-06-20       Impact factor: 11.205

  1 in total

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