Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session R45: Computational Methods for Statistical Mechanics: Advances and Applications IFocus
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Sponsoring Units: DCOMP GSNP Chair: Markus Eisenbach, Oak Ridge National Lab Room: 706 |
Thursday, March 5, 2020 8:00AM - 8:36AM |
R45.00001: Efficient Simulation of Self-Avoiding Walks Invited Speaker: Nathan Clisby Self-avoiding walks are simply defined as walks on a lattice that avoid themselves, and provide the simplest model of a polymer that captures universal features such as the Flory exponent ν which characterises the size of a polymer. In recent years, high precision Monte Carlo simulations of self-avoiding walks with many millions of steps have been realised through the use of a radically efficient implementation of the pivot algorithm via a hierarchical data structure. This data structure allows for global updates of the system to be performed in the same CPU time as local updates. |
Thursday, March 5, 2020 8:36AM - 8:48AM |
R45.00002: Smart random walks for accelerated Monte Carlo simulations Ying Wai Li, Alfred C.K. Farris, Markus Eisenbach Monte Carlo simulations are robust methods to study statistical physics. However, the unpredictable convergence time and the ease of being trapped in local minima have plagued the efficiency of both traditional and modern Monte Carlo algorithms. We propose strategies to mitigate these problems. We highlight two recent algorithmic developments: the histogram-free multicanonical method for obtaining the density of states for physical systems [1], and a global update scheme that adjusts the sampling weights across the phase space simultaneously. Combining these two methods, we have observed speedups ranging from 1-3 orders of magnitude compared to existing flat-histogram methods such as Wang-Landau sampling and multicanonical sampling, depending on the problem of interest. These methods are implemented and publicly available in an open-source Monte Carlo software suite, the Oak-ridge Wang-Landau (OWL) code [2]. |
Thursday, March 5, 2020 8:48AM - 9:00AM |
R45.00003: Replica-Exchange Wang-Landau Simulations of Lattice Peptide Aggregation Matthew Wilson, Guangjie Shi, Thomas Wuest, David P Landau, Friederike Schmid The computational study of interacting biomolecules is a challenging endeavor due to the large range of time and length scales associated with the relevant physical transitions. In order to analyze the general, qualitative statistical physics of such systems as they transition from dissolved to aggregated crystalline states, we use the H0P lattice protein model1,2 simulated on simple cubic and face centered cubic lattices. Utilizing the parallel Replica-Exchange Wang-Landau3 Monte Carlo algorithm, the energy states and density of states are calculated for multiple interacting H0P peptides. Thermodynamic quantities are studied for short (< 20 residues) model peptides at a range of concentrations and temperatures as structures such as disordered oligomers, amyloid fibrils, and aggregates are formed. Additional structural observables such as the cluster size distribution are calculated in a post-simulation production run, and used to further elucidate the physical behavior during transitions. |
Thursday, March 5, 2020 9:00AM - 9:12AM |
R45.00004: A Combinatorial Perspective on Ising Model Hysteresis Yuling Guan, Ang Li, Stephan Wolfgang Haas, Satish Kumar Thittamaranahalli, Sven Koenig In this work, we apply combinatorial methods used extensively in Artificial Intelligence (AI) to understand Ising model hysteresis. Our approach is based on efficiently generating the top K solutions of the Ising model and its generalization in AI, called the Weighted Constraint Satisfaction Problem (WCSP). We discuss how the WCSP model with a memory effect can be used to study hysteresis combinatorially; and in this context, we also discuss how the memory effect is related to an effective temperature parameter. Turning to more complex variants of the Ising model, we show that the introduction of long-range dipole interactions leads to variations of the hysteresis curves and the introduction of three-spin interactions leads to the emergence of meta-stable plateau states. We also show how to apply the Discrete Fourier Transform for the analysis of such phase transitions in the Ising model induced by three-spin interactions. |
Thursday, March 5, 2020 9:12AM - 9:24AM |
R45.00005: Steering a solute between coexisting solvation states: calculation of free energy differences in the adaptive resolution method Maziar Heidari, Robinson Cortes Huerto, Raffaello Potestio, Kurt Kremer In the adaptive resolution method, it is possible to represent molecules with atomistic resolution in a simulation subregion and as ideal gas particles in a large reservoir. To enforce a uniform density profile across the simulation box, an external potential is applied and identified with the system's excess chemical potential. Indeed, atomistic and ideal gas images coexist at a constant temperature, volume, and chemical potential. |
Thursday, March 5, 2020 9:24AM - 9:36AM |
R45.00006: Effects of Lattice Constraints in Coarse-Grained Protein Models: A Wang-Landau Study Alfred Farris, Daniel T Seaton, David P Landau Using Wang-Landau sampling [1], we compare and contrast folding behavior in coarse-grained models for Crambin -- a 46 amino acid protein. We investigate Crambin in the context of the hydrophobic polar (HP) lattice model [2] and the semi-flexible H0P lattice model [3] -- an extension to the HP model in which an additional monomer type and an interaction accounting for chain-stiffness are included. We also examine folding behavior in the analogous continuum models, with potentials designed specifically to mimic the lattice models. Through analysis of thermodynamic and structural behavior, we paint a clear picture of the folding process in all cases, and gain an understanding of the effects of certain interactions on the folding process, as well as how lattice constraints impact the folding process. As the complexity of the model interactions increases, the two major transitions observed in nature -- the coil-globule collapse and the folding transition, split into multi-step processes, wherein the level of model coarse-graining has a significant impact on the details of the folding. |
Thursday, March 5, 2020 9:36AM - 9:48AM |
R45.00007: The self-consistent multi scale simulation of complex fluids Hideki Kobayashi, Paul Rohrbach, Robert Scheichl, Nigel B. Wilding, Robert L Jack We present a method that uses 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. |
Thursday, March 5, 2020 9:48AM - 10:00AM |
R45.00008: Equilibrium density calculation of generalized Muttalib-Borodin ensembles. Swapnil Yadav, Kazi Alam, Khandker A Muttalib, Dong Wang The Muttalib-Borodin (MB) random matrix ensemble, which has an additional interaction, was introduced as a solvable toy model for quasi one-dimensional (1D) disordered conductors. We generalize the MB random matrix ensemble with a disorder dependent parameter γ which characterizes the strength of the additional interaction term. This generalization can be considered as a simple toy model which captures the essential features of a quasi 1D to 3D generalization of disordered conductors and we call it the γ -ensembles. Our results suggest that the γ-ensembles can be mapped on to an MB ensemble by replacing the single particle confining potential with a γ-dependent effective confining potential. We numerically solve the Riemann-Hilbert (RH) problem associated with the equilibrium density of γ-ensembles for a range of γ between 0 and 1. We also study some interesting limits of the parameters of the γ-ensembles, where the equilibrium density for a generalized form of the β-ensembles can be explored. |
Thursday, March 5, 2020 10:00AM - 10:12AM |
R45.00009: Enhanced sampling of cylindrical microphase separation via shell-averaged bond-orientational order parameter Min Young Ha, Bumjoon Seo, Won Bo Lee The formation of a hexagonal phase from the disordered phase is one of the typical order-disorder transitions (ODT) observed in asymmetric diblock copolymer systems. In order to drive this transition in a particle-based simulation, we introduce a shell-based bond-orientational order parameter that selectively responds to the mesoscopic order of the hexagonal cylinder phase. From metadynamics simulations in a bond-free particle model system, the characteristic pathway involved with the underlying free energy surface is deduced for the disordered-to-hexagonal transition. It is shown consecutively that the transition pathway and the metastable state are reproduced in dissipative particle dynamics simulations for the corresponding transition in bulk asymmetric block copolymer melt system. These agreements suggest that efficient strategies for enhanced sampling with particle-based simulations of block copolymer systems can be devised using coarse-grained pictures of the mesoscopic order. |
Thursday, March 5, 2020 10:12AM - 10:24AM |
R45.00010: Probing predictions due to the nonlocal interface Hamiltonian: Monte Carlo simulations of interfacial fluctuations in Ising films Lijun Pang, David P Landau, Kurt Binder Extensive Monte Carlo simulations have been performed on an Ising ferromagnet under conditions that would lead to complete wetting in a semi-infinite system. We studied an L×L×D slab geometry with oppositely directed surface fields so that a single interface is formed and can undergo a localization-delocalization transition. Under the chosen conditions the interface position is, on average, in the middle of the slab, and its fluctuations allow a sensitive test of predictions that the effective interactions between the interface and the confining surfaces are nonlocal. The decay of distance dependent correlation functions are measured within the surface, in the middle of the slab, and between middle and the surface for slabs of varying thickness D. From Fourier transforms of these correlation functions a non-linear correlation length is extracted, and its behavior is found to confirm theoretical predictions for D>6 lattice spacings. |
Thursday, March 5, 2020 10:24AM - 10:36AM |
R45.00011: Integer lattice gases, Molecular Dynamics Lattice Gas and an alternative derivation of the lattice Boltzmann method Alexander Wagner, Noah Seekins, Reza Parsa, Aleksandra Pachalieva We report on recent progress in two related areas: |
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R45.00012: Machine-learning approach to real-space renormalization of the 2D Potts model Chak Ming Chan, Liang Tian, Lei-Han Tang The ordering transition of the q-state Potts model on a square lattice changes from continuous to first-order at q=4. This changeover has been analyzed in real-space renormalization group (RSRG) studies[1] but a clear physical picture is lacking. We have previously conjectured that the weak first order transition at q>4 is related to the four-color theorem in graph theory[2]. Here we implement a recently proposed deep-learning scheme that maps configurations at successive scales to each other[3]. Parameters of the mapping are learned by maximizing mutual information. We take into account symmetry properties of the model and analyze the resulting RG flow to extract critical exponents and other properties. The emergence of "mosaic domains" which represent dilution of the original Potts model under the RG transformation will be discussed[4]. |
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