Abstract
A new method is proposed to numerically extract the diffusivity of a (typically nonlinear) diffusion equation from underlying stochastic particle systems. The proposed strategy requires the system to be in local equilibrium and have Gaussian fluctuations but it is otherwise allowed to undergo arbitrary outofequilibrium evolutions. This could be potentially relevant for particle data obtained from experimental applications. The key idea underlying the method is that finite, yet large, particle systems formally obey stochastic partial differential equations of gradient flow type satisfying a fluctuation–dissipation relation. The strategy is here applied to three classic particle models, namely independent random walkers, a zerorange process and a symmetric simple exclusion process in one space dimension, to allow the comparison with analytic solutions.
Original language  English 

Article number  20170694 
Journal  Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences 
Volume  474 
Issue number  2212 
Early online date  11 Apr 2018 
DOIs  
Publication status  Published  25 Apr 2018 
Keywords
 Coarsegraining
 Fluctuation–dissipation
 Nonequilibrium thermodynamics
 Transport coefficients
ASJC Scopus subject areas
 Mathematics(all)
 Engineering(all)
 Physics and Astronomy(all)
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Codes for "Computing diffusivities from particle models out of equilibrium"
Zimmer, J. (Creator), Embacher, P. (Creator), Dirr, N. (Creator) & Reina, C. (Creator), University of Bath, 11 Apr 2018
DOI: 10.15125/BATH00488
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