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One-dimensional irreversible aggregation with dynamics of a totally asymmetric simple exclusion process

机译:一维不可逆聚集,具有全部不对称简单排除过程的动力学

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We define and study one-dimensional model of irreversible aggregation of particles obeying a discrete-time kinetics, which is a special limit of the generalized Totally Asymmetric Simple Exclusion Process (gTASEP) on open chains. The model allows for clusters of particles to translate as a whole entity one site to the right with the same probability as single particles do. A particle and a cluster, as well as two clusters, irreversibly aggregate whenever they become nearest neighbors. Nonequilibrium stationary phases appear under the balance of injection and ejection of particles. By extensiveMonte Carlo simulations it is established that the phase diagram in the plane of the injection-ejection probabilities consists of three stationary phases: a multiparticle (MP) one, a completely filled (CF) phase, and a “mixed” (MP+CF) one. The transitions between these phases are: an unusual transition between MP and CF with jump discontinuity in both the bulk density and the current, a conventional first-order transition with a jump in the bulk density between MP and MP+CF, and a continuous clustering-type transition from MP to CF, which takes place throughout the MP+CF phase between them. By the data collapse method a finite-size scaling function for the current and bulk density is obtained near the unusual phase transition line. A diverging correlation length, associated with that transition, is identified and interpreted as the size of the largest cluster. The model allows for a future extension to account for possible cluster fragmentation.
机译:我们定义并研究遵守离散时间动力学的粒子不可逆聚集的一维模型,这是开放链上广义完全不对称简单排除过程(GTASEP)的特殊限制。该模型允许颗粒作为整个实体向右转换为整个实体,并且具有与单个粒子相同的概率。每当它们变为最近的邻居时,粒子和簇,以及两个簇,不可逆转地聚集。非预测固定阶段出现在注射和喷射颗粒的平衡下。通过extenSiveMonte Carlo模拟,建立了注射喷射概率平面中的相图由三个固定阶段组成:多粒(MP),完全填充(CF)相和“混合”(MP + CF ) 一。这些阶段之间的转换是:MP和CF之间的异常过渡,在堆积密度和电流中具有跳转不连续,传统的一阶转换,跳跃在MP和MP + CF之间的堆积密度,以及连续聚类-Type从MP转换到CF,它在它们之间进行整个MP + CF相位进行。通过数据折叠方法,在不寻常的相位过渡线附近获得电流和堆积密度的有限尺寸缩放功能。与该转换相关联的不同关系长度被识别并被解释为最大簇的大小。该模型允许将来的扩展帐户解释为可能的群集碎片。

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