Stochastic self-tuning hybrid algorithm for reaction-diffusion systems
- Authors:
-
- 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:
- 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.
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.
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.
@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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DOI: 10.1063/1.5125022
DOI: 10.1063/1.5125022
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