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Coarse-grained (CG) molecular dynamics enables the study of biological processes at temporal and spatial scales that would be intractable at an atomistic resolution. However, accurately learning a CG force field remains a challenge. In this…

We present a systematic coarse-graining (CG) strategy for many particle molecular systems based on cluster expansion techniques. We construct a hierarchy of coarse-grained Hamiltonians with interaction potentials consisting of two, three…

Soft Condensed Matter · Physics 2017-10-11 Anastasios Tsourtis , Vagelis Harmandaris , Dimitrios Tsagkarogiannis

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a…

Machine Learning · Statistics 2017-02-01 Markus Schöberl , Nicholas Zabaras , Phaedon-Stelios Koutsourelakis

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

Coupled natural systems are generally modeled at multiple abstraction levels. Both structural scale and behavioral complexity of these models are determinants in the kinds of questions that can be posed and answered. As scale and complexity…

Computational Engineering, Finance, and Science · Computer Science 2018-07-23 Hessam S. Sarjoughian , William A. Boyd , Miguel F. Acevedo

The first paper of this series [J. Chem. Phys. 158, 034103 (2023)] demonstrated that excess entropy scaling holds for both fine-grained and corresponding coarse-grained (CG) systems. Despite its universality, a more exact determination of…

Chemical Physics · Physics 2023-01-18 Jaehyeok Jin , Kenneth S. Schweizer , Gregory A. Voth

Reducing the complexity of large systems described as complex networks is key to understand them and a crucial issue is to know which properties of the initial system are preserved in the reduced one. Here we use random walks to design a…

Disordered Systems and Neural Networks · Physics 2009-11-13 David Gfeller , Paolo De los Rios

Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units (CGU)…

Molecular Networks · Quantitative Biology 2009-11-10 Shalev Itzkovitz , Reuven Levitt , Nadav Kashtan , Ron Milo , Michael Itzkovitz , Uri Alon

Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically grounded bottom-up models are appealing due to their thermodynamic consistency with the…

Computational Physics · Physics 2022-11-01 Blake R. Duschatko , Jonathan Vandermause , Nicola Molinari , Boris Kozinsky

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of such graphs. Some of the most useful graph metrics are based on triangles, such as those measuring social…

Social and Information Networks · Computer Science 2014-10-21 C. Seshadhri , Ali Pinar , Tamara G. Kolda

We study coarse-grained (group-level) alignment dynamics of individual-based animal group models for {\it heterogeneous} populations consisting of informed (on preferred directions) and uninformed individuals. The orientation of each…

Quantitative Methods · Quantitative Biology 2007-05-23 Sung Joon Moon , B. Nabet , Naomi E. Leonard , Simon A. Levin , I. G. Kevrekidis

Predictive simulations of complex systems are essential for applications ranging from weather forecasting to drug design. The veracity of these predictions hinges on their capacity to capture the effective system dynamics. Massively…

Computational Physics · Physics 2021-10-20 Pantelis R. Vlachas , Georgios Arampatzis , Caroline Uhler , Petros Koumoutsakos

A method for studying the qualitative dynamical properties of abstract computing machines based on the approximation of their program-size complexity using a general lossless compression algorithm is presented. It is shown that the…

Computational Complexity · Computer Science 2011-01-24 Hector Zenil

Coarse-graining (CG) accelerates molecular simulations of protein dynamics by simulating sets of atoms as singular beads. Backmapping is the opposite operation of bringing lost atomistic details back from the CG representation. While…

Machine Learning · Computer Science 2023-03-06 Soojung Yang , Rafael Gómez-Bombarelli

We extend a recently developed exact schema based, or coarse grained, formulation of genetic dynamics \cite{stewael,stewael1,stewael2} and its associated exact Schema theorem to an arbitrary selection scheme and a general crossover…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 C. R. Stephens

Molecular Dynamics (MD) simulations are essential for accurately predicting the physical and chemical properties of large molecular systems across various pressure and temperature ensembles. However, the high computational costs associated…

A hallmark of meso-scale interfacial fluids is the multi-faceted, scale-dependent interfacial energy, which often manifests different characteristics across the molecular and continuum scale. The multi-scale nature imposes a challenge to…

Computational Physics · Physics 2023-02-22 Pei Ge , Linfeng Zhang , Huan Lei

Numerical simulation is powerful to study nonlinear solid mechanics problems. However, mesh-based or particle-based numerical methods suffer from the common shortcoming of being time-consuming, particularly for complex problems with…

Machine Learning · Statistics 2024-09-18 Ming-Jian Li , Yanping Lian , Zhanshan Cheng , Lehui Li , Zhidong Wang , Ruxin Gao , Daining Fang

We propose a generalized Langevin dynamics (GLD) technique to construct non-Markovian particle-based coarse-grained models from fine-grained reference simulations and to efficiently integrate them. The proposed GLD model has the form of a…

Soft Condensed Matter · Physics 2018-11-16 Gerhard Jung , Martin Hanke , Friederike Schmid

In this paper, we present an advanced high-order compact gas-kinetic scheme (CGKS) for 3D unstructured mixed-element meshes, augmented with a geometric multigrid technique to accelerate steady-state convergence. The scheme evolves…

Computational Physics · Physics 2024-02-06 Hongyu Liu , Xing Ji , Yunpeng Mao , Yuan Ding , Kun Xu
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