Literature DB >> 24697426

Adaptive two-regime method: application to front propagation.

Martin Robinson1, Mark Flegg2, Radek Erban1.   

Abstract

The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in terms of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.

Year:  2014        PMID: 24697426     DOI: 10.1063/1.4868652

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  17 in total

1.  Discrete-continuous reaction-diffusion model with mobile point-like sources and sinks.

Authors:  Svyatoslav Kondrat; Olav Zimmermann; Wolfgang Wiechert; Eric von Lieres
Journal:  Eur Phys J E Soft Matter       Date:  2016-01-29       Impact factor: 1.890

2.  The pseudo-compartment method for coupling partial differential equation and compartment-based models of diffusion.

Authors:  Christian A Yates; Mark B Flegg
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

3.  Hybrid finite element and Brownian dynamics method for charged particles.

Authors:  Gary A Huber; Yinglong Miao; Shenggao Zhou; Bo Li; J Andrew McCammon
Journal:  J Chem Phys       Date:  2016-04-28       Impact factor: 3.488

4.  Coupling volume-excluding compartment-based models of diffusion at different scales: Voronoi and pseudo-compartment approaches.

Authors:  P R Taylor; R E Baker; M J Simpson; C A Yates
Journal:  J R Soc Interface       Date:  2016-07       Impact factor: 4.118

5.  Stochastic self-tuning hybrid algorithm for reaction-diffusion systems.

Authors:  Á Ruiz-Martínez; T M Bartol; T J Sejnowski; D M Tartakovsky
Journal:  J Chem Phys       Date:  2019-12-28       Impact factor: 3.488

6.  Convergence of methods for coupling of microscopic and mesoscopic reaction-diffusion simulations.

Authors:  Mark B Flegga; Stefan Hellander; Radek Erban
Journal:  J Comput Phys       Date:  2015-05-15       Impact factor: 3.553

7.  A General Approximation for the Dynamics of Quantitative Traits.

Authors:  Katarína Bod'ová; Gašper Tkačik; Nicholas H Barton
Journal:  Genetics       Date:  2016-02-17       Impact factor: 4.562

8.  Incorporating domain growth into hybrid methods for reaction-diffusion systems.

Authors:  Cameron A Smith; Christian A Yates
Journal:  J R Soc Interface       Date:  2021-04-14       Impact factor: 4.118

9.  Multiscale reaction-diffusion simulations with Smoldyn.

Authors:  Martin Robinson; Steven S Andrews; Radek Erban
Journal:  Bioinformatics       Date:  2015-03-18       Impact factor: 6.937

10.  Hybrid approaches for multiple-species stochastic reaction-diffusion models.

Authors:  Fabian Spill; Pilar Guerrero; Tomas Alarcon; Philip K Maini; Helen Byrne
Journal:  J Comput Phys       Date:  2015-10-15       Impact factor: 3.553

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.