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Related papers: Efficient simulation of semiflexible polymers

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The dynamic behavior of semi-dilute polymer solutions is governed by an interplay between solvent quality, concentration, molecular weight, and flow type. Semi-dilute solutions are characterized by large fluctuations in concentration,…

Soft Condensed Matter · Physics 2020-07-03 Kai-Wen Hsiao , Chandi Samsal , J. Ravi Prakash , Charles M. Schroeder

We report model calculations on DNA single strands which describe the equilibrium dynamics and kinetics of hairpin formation and melting. Modeling is at the level of single bases. Strand rigidity is described in terms of simple polymer…

Soft Condensed Matter · Physics 2007-10-01 Jalal Errami , Michel Peyrard , Nikos Theodorakopoulos

Motivated by decentralized approaches to machine learning, we propose a collaborative Bayesian learning algorithm taking the form of decentralized Langevin dynamics in a non-convex setting. Our analysis show that the initial KL-divergence…

Machine Learning · Statistics 2021-01-12 Anjaly Parayil , He Bai , Jemin George , Prudhvi Gurram

By means of Brownian dynamics simulations we study the steady-state dynamic properties of a flexible active polymer in a poor solvent condition. Our results show that the effective diffusion constant of the polymer $D_{\rm eff}$ gets…

Soft Condensed Matter · Physics 2023-08-29 Suman Majumder , Subhajit Paul , Wolfhard Janke

The endpoint distribution and dynamics of semiflexible fibers is studied by numerical simulation. A brief overview is given over the analytical theory of flexible and semiflexible polymers. In particular, a closed expression is given for…

Soft Condensed Matter · Physics 2013-06-13 Robert D. Groot

For "large" class $\mathcal{C}$ of continuous probability density functions (p.d.f.), we demonstrate that for every $w\in\mathcal{C}$ there is mixture of discrete Binomial distributions (MDBD) with $T\geq N\sqrt{\phi_{w}/\delta}$ distinct…

Discrete Mathematics · Computer Science 2016-04-22 Gorav Jindal , Pavel Kolev

We present a distilled multi-time-step (DMTS) strategy to accelerate molecular dynamics simulations using foundation neural network models. DMTS uses a dual-level neural network where the target accurate potential is coupled to a simpler…

The dynamics of flexible filaments entrained in flow, important for understanding many biological and industrial processes, are computationally expensive to model with full-physics simulations. This work describes a data-driven technique to…

Fluid Dynamics · Physics 2024-05-20 Andrew J Fox , Michael D. Graham

Simulations of biological macromolecules play an important role in understanding the physical basis of a number of complex processes such as protein folding. Even with increasing computational power and evolution of specialized…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-18 Hyungro Lee , Heng Ma , Matteo Turilli , Debsindhu Bhowmik , Shantenu Jha , Arvind Ramanathan

Single-filament tracing has been a valuable tool to directly determine geometrical and mechanical properties of entangled polymer networks. However, systematically verifying how the stiffness of the tracer filament or its molecular…

Soft Condensed Matter · Physics 2022-01-05 Tina Händler , Cary Tutmarc , Martin Glaser , Jessica S. Freitag , David M. Smith , Jörg Schnauß

This paper extends a field-theoretical dynamical networking formalism for mesoscopic polymer dynamics to explicitly include dedicated cross-linker particles. Cross-linkers are represented within a Martin-Siggia-Rose generating functional…

Soft Condensed Matter · Physics 2025-11-18 Nadine du Toit , Kristian K. Muller-Nedebock , Giuseppe Pellicane

Base stacking is crucial in nucleic acid stabilization, from DNA duplex hybridization to single-stranded DNA (ssDNA) protein binding. While stacking energies are tiny in ssDNA, they are inextricably mixed with hydrogen bonding in DNA base…

Soft Condensed Matter · Physics 2024-11-19 Xavier Viader-Godoy , Maria Manosas , Felix Ritort

Discrete mesoscale network models, in which explicitly modeled polymer chains are replaced by implicit pairwise potentials, are capable of predicting the macroscale mechanical response of polymeric materials such as elastomers and gels,…

Soft Condensed Matter · Physics 2024-07-16 Robert J. Wagner , Meredith N. Silberstein

We developed and applied a machine-learned discretization for one-dimensional (1-D) horizontal passive scalar advection, which is an operator component common to all chemical transport models (CTMs). Our learned advection scheme resembles a…

Atmospheric and Oceanic Physics · Physics 2023-09-21 Manho Park , Zhonghua Zheng , Nicole Riemer , Christopher W. Tessum

Modeling of turbulent flows is still challenging. One way to deal with the large scale separation due to turbulence is to simulate only the large scales and model the unresolved contributions as done in large-eddy simulation (LES). This…

Computational Physics · Physics 2019-10-03 Mathis Bode , Michael Gauding , Konstantin Kleinheinz , Heinz Pitsch

We define a discrete-time Markov chain for abstract polymer models and show that under sufficient decay of the polymer weights, this chain mixes rapidly. We apply this Markov chain to polymer models derived from the hard-core and…

Data Structures and Algorithms · Computer Science 2021-04-14 Zongchen Chen , Andreas Galanis , Leslie Ann Goldberg , Will Perkins , James Stewart , Eric Vigoda

We present a theoretical description of the dynamics of a semi-flexible polymer being pulled through a nanopore by an external force acting at the pore. Our theory is based on the tensile blob picture of Pincus in which the front of the…

Statistical Mechanics · Physics 2015-09-16 Pui-Man Lam , Yi Zhen

We consider the motion of semiflexible polymers in double-well potentials. We calculate shape, energy, and effective diffusion constant of kink excitations, and in particular their dependence on the bending rigidity of the semiflexible…

Statistical Mechanics · Physics 2009-11-11 P. Kraikivski , R. Lipowsky , J. Kierfeld

Polymer composites are ideal candidates for next generation biomimetic soft materials because of their exquisite bottom-up designability. However, the richness of behaviours comes at a price: the need for precise and extensive…

Soft Condensed Matter · Physics 2019-07-30 Davide Michieletto , Robert Fitzpatrick , Rae M Robertson-Anderson

We proposed a probabilistic algorithm to solve the Multiple Sequence Alignment problem. The algorithm is a Simulated Annealing (SA) that exploits the representation of the Multiple Alignment between $D$ sequences as a directed polymer in…

Genomics · Quantitative Biology 2016-08-16 M. Hernández-Guía , R. Mulet , S. Rodríguez-Pérez
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