2019
DOI: 10.1063/1.5120833
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Correction of coarse-graining errors by a two-level method: Application to the Asakura-Oosawa model

Abstract: We present a method that exploits self-consistent simulation of coarse-grained and fine-grained models, in order to analyse properties of physical systems. The method uses the coarse-grained model to obtain a first estimate of the quantity of interest, before computing a correction by analysing properties of the fine system. We illustrate the method by applying it to the Asakura-Oosawa (AO) model of colloid-polymer mixtures. We show that the liquid-vapour critical point in that system is affected by three-body… Show more

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Cited by 13 publications
(29 citation statements)
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“…29, 39, and 40). Multi-body terms have been added in CG models as a correction [41][42][43][44][45] or by considering the physical nature of the corresponding interactions, as for instance, water-mediated potentials. 20,46 However, the multi-body terms are often crucial to reproduce the system's behavior correctly.…”
Section: Introductionmentioning
confidence: 99%
“…29, 39, and 40). Multi-body terms have been added in CG models as a correction [41][42][43][44][45] or by considering the physical nature of the corresponding interactions, as for instance, water-mediated potentials. 20,46 However, the multi-body terms are often crucial to reproduce the system's behavior correctly.…”
Section: Introductionmentioning
confidence: 99%
“…This work uses a two-level numerical method [25] to characterise the critical point for fluid-fluid phase separation in hard sphere mixtures. The first level of the method relies on an accurate coarse-grained (CG) model where the small particles are integrated out, providing an effective theory for the large ones.…”
mentioning
confidence: 99%
“…This problem is avoided by the two-level method. We outline the approach, see [25] and Appendix A for details. The critical points of interest generically occur for parameters where the fluid phase is metastable with respect to crystallisation of the large particles [18] (recall Fig.…”
mentioning
confidence: 99%
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