Stochastic self-tuning hybrid algorithm for reaction-diffusion systems

doi:10.1063/1.5125022

This content will become publicly available on December 27, 2020

Title: Stochastic self-tuning hybrid algorithm for reaction-diffusion systems

Authors:

Ruiz-Martínez, Á. ^[1]; Bartol, T. M. ^[2]; Sejnowski, T. J. ^[2];

^[3]

Department of Mechanical and Aerospace Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA
Computational Neurobiology Laboratory, Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, California 92037, USA
Department of Energy Resources Engineering, Stanford University, 367 Panama Street, Stanford, California 94305, USA

Publication Date:: 2019-12-28

Sponsoring Org.:: USDOE

OSTI Identifier:: 1580549

Grant/Contract Number:: SC0019130

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Journal of Chemical Physics

Additional Journal Information:: Journal Name: Journal of Chemical Physics Journal Volume: 151 Journal Issue: 24; Journal ID: ISSN 0021-9606

Publisher:: American Institute of Physics

Country of Publication:: United States

Language:: English

Citation Formats


                    Ruiz-Martínez, Á., Bartol, T. M., Sejnowski, T. J., and Tartakovsky, D. M. Stochastic self-tuning hybrid algorithm for reaction-diffusion systems.  United States: N. p., 2019. 
        Web.  doi:10.1063/1.5125022.

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                    Ruiz-Martínez, Á., Bartol, T. M., Sejnowski, T. J., & Tartakovsky, D. M. Stochastic self-tuning hybrid algorithm for reaction-diffusion systems.  United States.  doi:10.1063/1.5125022.

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                    Ruiz-Martínez, Á., Bartol, T. M., Sejnowski, T. J., and Tartakovsky, D. M. Sat .  
        "Stochastic self-tuning hybrid algorithm for reaction-diffusion systems".  United States.  doi:10.1063/1.5125022.

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@article{osti_1580549,

  title        = {Stochastic self-tuning hybrid algorithm for reaction-diffusion systems},

  author       = {Ruiz-Martínez, Á. and Bartol, T. M. and Sejnowski, T. J. and Tartakovsky, D. M.},

  abstractNote = {},

  doi          = {10.1063/1.5125022},

  journal      = {Journal of Chemical Physics},

  number       = 24,

  volume       = 151,

  place        = {United States},

  year         = {2019},

  month        = {12}

}

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This content will become publicly available on December 27, 2020

Title: Stochastic self-tuning hybrid algorithm for reaction-diffusion systems

Citation Formats

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journal, January 2012

ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics
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journal, June 2019

Multiscale Reaction-Diffusion Algorithms: PDE-Assisted Brownian Dynamics
journal, January 2013

Alternating Direction Methods for Parabolic Systems in m Space Variables
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Multiscale reaction-diffusion simulations with Smoldyn: Fig. 1.
journal, March 2015

Combining molecular dynamics with mesoscopic Green’s function reaction dynamics simulations
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journal, May 2007

Mathematical and Experimental Analyses of Antibody Transport in Hollow-Fiber-Based Specific Antibody Filters
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