Existence of two distinct time scales in the Fairen-Velarde model of bacterial respiration

IF 1.5 4区 物理与天体物理 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Soumyadeep Kundu, M. Acharyya
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引用次数: 0

Abstract

We study the bacterial respiration through the numerical solution of the Fairen-Velarde coupled nonlinear differential equations. The instantaneous concentrations of the oxygen and the nutrients are computed. The fixed point solution and the stable limit cycle are found in different parameter ranges as predicted by the linearized differential equations. In a specified range of parameters, it is observed that the system spends some time near the stable limit cycle and eventually reaches the stable fixed point. This metastability has been investigated systematically. Interestingly, it is observed that the system exhibits two distinctly different time scales in reaching the stable fixed points. The slow time scale of the metastable lifetime near the stable limit cycle and a fast time scale (after leaving the zone of limit cycle) in rushing towards the stable fixed point. The gross residence time, near the limit cycle (described by a slow time scale), can be reduced by varying the concentrations of nutrients. This idea can be used to control the harmful metastable lifespan of active bacteria.
Fairen-Velarde 细菌呼吸模型中存在两种不同的时间尺度
我们通过对 Fairen-Velarde 耦合非线性微分方程的数值求解来研究细菌呼吸。计算了氧气和营养物质的瞬时浓度。根据线性化微分方程的预测,在不同参数范围内找到了定点解决方案和稳定的极限循环。在特定的参数范围内,可以观察到系统在稳定的极限循环附近停留了一段时间,并最终到达稳定的固定点。我们对这种可转移性进行了系统研究。有趣的是,我们观察到系统在到达稳定固定点时表现出两种截然不同的时间尺度。在稳定的极限周期附近,瞬变寿命的时间尺度较慢,而在冲向稳定固定点的过程中,时间尺度较快(离开极限周期区域后)。可以通过改变营养物质的浓度来缩短极限循环附近的总停留时间(用慢时间尺度描述)。这一想法可用于控制活性细菌有害的新陈代谢寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Modern Physics C
International Journal of Modern Physics C 物理-计算机:跨学科应用
CiteScore
3.00
自引率
15.80%
发文量
158
审稿时长
4 months
期刊介绍: International Journal of Modern Physics C (IJMPC) is a journal dedicated to Computational Physics and aims at publishing both review and research articles on the use of computers to advance knowledge in physical sciences and the use of physical analogies in computation. Topics covered include: algorithms; computational biophysics; computational fluid dynamics; statistical physics; complex systems; computer and information science; condensed matter physics, materials science; socio- and econophysics; data analysis and computation in experimental physics; environmental physics; traffic modelling; physical computation including neural nets, cellular automata and genetic algorithms.
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