Bressloff Paul C
Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom.
Phys Rev E. 2024 Feb;109(2-1):024103. doi: 10.1103/PhysRevE.109.024103.
There are a large variety of hybrid stochastic systems that couple a continuous process with some form of stochastic switching mechanism. In many cases the system switches between different discrete internal states according to a finite-state Markov chain, and the continuous dynamics depends on the current internal state. The resulting hybrid stochastic differential equation (hSDE) could describe the evolution of a neuron's membrane potential, the concentration of proteins synthesized by a gene network, or the position of an active particle. Another major class of switching system is a search process with stochastic resetting, where the position of a diffusing or active particle is reset to a fixed position at a random sequence of times. In this case the system switches between a search phase and a reset phase, where the latter may be instantaneous. In this paper, we investigate how the behavior of a stochastically switching system is modified when the maximum number of switching (or reset) events in a given time interval is fixed. This is motivated by the idea that each time the system switches there is an additive energy cost. We first show that in the case of an hSDE, restricting the number of switching events is equivalent to truncating a Volterra series expansion of the particle propagator. Such a truncation significantly modifies the moments of the resulting renormalized propagator. We then investigate how restricting the number of reset events affects the diffusive search for an absorbing target. In particular, truncating a Volterra series expansion of the survival probability, we calculate the splitting probabilities and conditional MFPTs for the particle to be absorbed by the target or exceed a given number of resets, respectively.
存在各种各样的混合随机系统,这些系统将一个连续过程与某种形式的随机切换机制相结合。在许多情况下,系统会根据有限状态马尔可夫链在不同的离散内部状态之间切换,并且连续动力学取决于当前的内部状态。由此产生的混合随机微分方程(hSDE)可以描述神经元膜电位的演化、基因网络合成蛋白质的浓度或活性粒子的位置。另一类主要的切换系统是具有随机重置的搜索过程,其中扩散或活性粒子的位置会在随机的时间序列上被重置到一个固定位置。在这种情况下,系统在搜索阶段和重置阶段之间切换,后者可能是瞬时的。在本文中,我们研究当给定时间间隔内的最大切换(或重置)事件数量固定时,随机切换系统的行为是如何被修改的。这是由每次系统切换都会产生附加能量成本这一想法所推动的。我们首先表明,在hSDE的情况下,限制切换事件的数量等同于截断粒子传播子的沃尔泰拉级数展开。这样的截断会显著改变所得重整化传播子的矩。然后,我们研究限制重置事件的数量如何影响对吸收目标的扩散搜索。特别是,通过截断生存概率的沃尔泰拉级数展开,我们分别计算了粒子被目标吸收或超过给定重置次数的分裂概率和条件平均首次通过时间。