Postprocessing techniques for gradient percolation predictions on the square lattice

Tencer, John; Forsberg, Kelsey Meeks

doi:10.1103/physreve.103.012115

Postprocessing techniques for gradient percolation predictions on the square lattice

Journal Article · Fri Jan 15 00:00:00 EST 2021 · Physical Review E

DOI:https://doi.org/10.1103/physreve.103.012115· OSTI ID:1778027

^[1]; Forsberg, Kelsey Meeks ^[1]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

In this work, we revisit the classic problem of site percolation on a regular square lattice. In particular, we investigate the effect of quantization bias errors on percolation threshold predictions for large probability gradients and propose a mitigation strategy. We demonstrate through extensive computational experiments that the assumption of a linear relationship between probability gradient and percolation threshold used in previous investigations is invalid. Moreover, we demonstrate that, due to skewness in the distribution of occupation probabilities visited the average does not converge monotonically to the true percolation threshold. Furthermore, we identify several alternative metrics which do exhibit monotonic (albeit not linear) convergence and document their observed convergence rates.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC04-94AL85000; NA0003525

OSTI ID:: 1778027

Report Number(s):: SAND--2021-3550J; 695049

Journal Information:: Physical Review E, Journal Name: Physical Review E Journal Issue: 1 Vol. 103; ISSN 2470-0045

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

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