论文标题
扩散颗粒的运输特性,适合在捕获环境中生存的条件
Transport properties of diffusive particles conditioned to survive in trapping environments
论文作者
论文摘要
我们认为在$ n $的存在下,具有扩散系数$ d $的一维的布朗运动,部分吸收了强度$β$,距距离$ l $隔开,并且在粒子的初始位置周围均匀地间隔。我们研究该过程的运输属性,以生存为$ t $。我们发现幸存的粒子首先在遇到陷阱之前正常扩散,然后经历瞬时异常扩散的时期,之后它达到了最终的扩散状态。渐近方案由有效的扩散系数$ d_ \ text {eff} $控制,该{eff} $由陷阱环境引起,通常与原始环境不同。我们表明,当陷阱的数量为\ emph {有限}时,环境会增强扩散并诱导有效的扩散系数,该系数在系统上等于$ d_ \ text {eff} = 2d $,独立于陷阱的数量,陷阱强度$β$和距离$ l $。相反,当陷阱的数量为\ emph {infinite}时,我们发现环境通过有效的扩散系数抑制扩散,该系数取决于陷阱强度$β$和距离$ l $以及通过非平常缩放函数$ d_ \ d_ \ text {eff} = d \ ntect = d \ not fref f f f fref fref fl/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/wer/此外,我们提供了一种无排斥的算法来通过得出有效的langevin方程,该方程具有由陷阱引起的有效排斥潜力,从而产生了幸存的轨迹。最后,我们将结果扩展到其他陷阱环境。
We consider a one-dimensional Brownian motion with diffusion coefficient $D$ in the presence of $n$ partially absorbing traps with intensity $β$, separated by a distance $L$ and evenly spaced around the initial position of the particle. We study the transport properties of the process conditioned to survive up to time $t$. We find that the surviving particle first diffuses normally, before it encounters the traps, then undergoes a period of transient anomalous diffusion, after which it reaches a final diffusive regime. The asymptotic regime is governed by an effective diffusion coefficient $D_\text{eff}$, which is induced by the trapping environment and is typically different from the original one. We show that when the number of traps is \emph{finite}, the environment enhances diffusion and induces an effective diffusion coefficient that is systematically equal to $D_\text{eff}=2D$, independently of the number of the traps, the trapping intensity $β$ and the distance $L$. On the contrary, when the number of traps is \emph{infinite}, we find that the environment inhibits diffusion with an effective diffusion coefficient that depends on the traps intensity $β$ and the distance $L$ through a non-trivial scaling function $D_\text{eff}=D \mathcal{F}(βL/D)$, for which we obtain a closed-form. Moreover, we provide a rejection-free algorithm to generate surviving trajectories by deriving an effective Langevin equation with an effective repulsive potential induced by the traps. Finally, we extend our results to other trapping environments.