137,611 research outputs found
Accurate and efficient splitting methods for dissipative particle dynamics
We study numerical methods for dissipative particle dynamics (DPD), which is
a system of stochastic differential equations and a popular stochastic
momentum-conserving thermostat for simulating complex hydrodynamic behavior at
mesoscales. We propose a new splitting method that is able to substantially
improve the accuracy and efficiency of DPD simulations in a wide range of the
friction coefficients, particularly in the extremely large friction limit that
corresponds to a fluid-like Schmidt number, a key issue in DPD. Various
numerical experiments on both equilibrium and transport properties are
performed to demonstrate the superiority of the newly proposed method over
popular alternative schemes in the literature
Generalized k-core percolation on correlated and uncorrelated multiplex networks
It has been recognized that multiplexes and interlayer degree correlations can play a crucial role in the resilience of many real-world complex systems. Here we introduce a multiplex pruning process that removes nodes of degree less than ki and their nearest neighbors in layer i for i=1,...,m, and establish a generic framework of generalized k-core (Gk-core) percolation over interlayer uncorrelated and correlated multiplex networks of m layers, where k=(k1,...,km) and m is the total number of layers. Gk-core exhibits a discontinuous phase transition for all k owing to cascading failures. We have unraveled the existence of a tipping point of the number of layers, above which the Gk-core collapses abruptly. This dismantling effect of multiplexity on Gk-core percolation shows a diminishing marginal utility in homogeneous networks when the number of layers increases. Moreover, we have found the assortative mixing for interlayer degrees strengthens the Gk-core but still gives rise to discontinuous phase transitions as compared to the uncorrelated counterparts. Interlayer disassortativity on the other hand weakens the Gk-core structure. The impact of correlation effect on Gk-core tends to be more salient systematically over k for heterogenous networks than homogeneous ones
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