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We propose new polymer models for Monte Carlo simulation and apply them to a polymer chain confined in a relatively thin box which has both curved and flat sides, and show that either an ideal or an excluded-volume chain spends more time in…

Soft Condensed Matter · Physics 2007-05-23 Y. Y. Suzuki , T. Dotera , M. Hirabayashi

Monte Carlo computer simulations are used to study the segregation behaviour of two polymers under cylindrical confinement. Using a multiple-histogram method, the conformational free energy, F, of the polymers was measured as a function of…

Soft Condensed Matter · Physics 2018-05-24 James M. Polson , Deanna R. -M. Kerry

Primitive path analyses of entanglements are performed over a wide range of chain lengths for both bead spring and atomistic polyethylene polymer melts. Estimators for the entanglement length N_e which operate on results for a single chain…

Soft Condensed Matter · Physics 2015-05-13 Robert S. Hoy , Katerina Foteinopoulou , Martin Kröger

We present the first polynomial-time algorithm to exactly compute the number of labeled chordal graphs on $n$ vertices. Our algorithm solves a more general problem: given $n$ and $\omega$ as input, it computes the number of…

Data Structures and Algorithms · Computer Science 2024-10-04 Ursula Hebert-Johnson , Daniel Lokshtanov , Eric Vigoda

We report results of extensive Dynamical Monte Carlo investigations on self-assembled Equilibrium Polymers (EP) without loops in good solvent. (This is thought to provide a good model of giant surfactant micelles.) Using a novel algorithm…

Soft Condensed Matter · Physics 2009-10-31 J. P. Wittmer , A. Milchev , M. E. Cates

Pre-calculated libraries of molecular fragment configurations have previously been used as a basis for both equilibrium sampling (via "library-based Monte Carlo") and for obtaining absolute free energies using a polymer-growth formalism.…

Quantitative Methods · Quantitative Biology 2018-12-26 Steven Lettieri , Artem B. Mamonov , Daniel M. Zuckerman

Monte Carlo simulations of coarse-grained polymers provide a useful tool to deepen the understanding of conformational and statistical properties of polymers both in physical as well as in biological systems. In this study we sample compact…

Soft Condensed Matter · Physics 2009-05-07 Manfred Bohn , Dieter W. Heermann

We consider flexible branched polymer, with quenched branch structure, and show that its conformational entropy as a function of its gyration radius $R$, at large $R$, obeys, in the scaling sense, $\Delta S \sim R^2/(a^2L)$, with $a$ bond…

Statistical Mechanics · Physics 2015-09-02 Alexander Y. Grosberg , Sergei K. Nechaev

Leverage scores, loosely speaking, reflect the importance of the rows and columns of a matrix. Ideally, given the leverage scores of a rank-$r$ matrix $M\in\mathbb{R}^{n\times n}$, that matrix can be reliably completed from just…

Information Theory · Computer Science 2017-11-21 Armin Eftekhari , Michael B. Wakin , Rachel A. Ward

We present a detailed analysis of the error budget for the TreePM method for doing cosmological N-Body simulations. It is shown that the choice of filter for splitting the inverse square force into short and long range components suggested…

Astrophysics · Physics 2009-11-07 J. S. Bagla , Suryadeep Ray

We present a method to generate realistic, three-dimensional networks of crosslinked semiflexible polymers. The free energy of these networks is obtained from the force-extension characteristics of the individual polymers and their…

Soft Condensed Matter · Physics 2009-11-13 E. M. Huisman , C. Storm , G. T. Barkema

We propose efficient algorithms for enumerating maximal common subsequences (MCSs) of two strings. Efficiency of the algorithms are estimated by the preprocessing-time, space, and delay-time complexities. One algorithm prepares a…

Data Structures and Algorithms · Computer Science 2023-07-21 Miyuji Hirota , Yoshifumi Sakai

Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that existing solutions dependent on simple Gaussian formulations…

Machine Learning · Computer Science 2022-05-11 Jurijs Nazarovs , Ronak R. Mehta , Vishnu Suresh Lokhande , Vikas Singh

We give an algorithm that generates a uniformly random contingency table with specified marginals, i.e. a matrix with non-negative integer values and specified row and column sums. Such algorithms are useful in statistics and combinatorics.…

Combinatorics · Mathematics 2021-06-17 Andrii Arman , Pu Gao , Nicholas Wormald

Effective sample size is a standard summary of Markov chain Monte Carlo output, but it is usually attached to scalar or Euclidean summaries chosen by the analyst. For manifold-valued samples this choice is not canonical: coordinate-wise…

Machine Learning · Statistics 2026-05-06 Kisung You

Recent developments of microscopic mechanical experiments allow the manipulation of individual polymer molecules in two main ways: \textit{uniform} stretching by external forces and \textit{non-uniform} stretching by external fields. Many…

Biological Physics · Physics 2015-06-11 Fabio Manca , Stefano Giordano , Pier Luca Palla , Fabrizio Cleri , Luciano Colombo

In Monte Carlo integration an accurate and reliable determination of the numerical intregration error is essential. We point out the need for an independent estimate of the error on this error, for which we present an unbiased estimator. In…

Numerical Analysis · Mathematics 2016-10-12 R. Bakx , R. H. P. Kleiss , F. Versteegen

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

Given a way to evaluate an unknown polynomial with integer coefficients, we present new algorithms to recover its nonzero coefficients and corresponding exponents. As an application, we adapt this interpolation algorithm to the problem of…

Symbolic Computation · Computer Science 2022-05-19 Pascal Giorgi , Bruno Grenet , Armelle Perret du Cray , Daniel S. Roche

This paper studies the mixing time of certain adaptive Markov Chain Monte Carlo algorithms. Under some regularity conditions, we show that the convergence rate of Importance Resampling MCMC (IRMCMC) algorithm, measured in terms of the total…

Probability · Mathematics 2014-07-29 Yves Atchadé , Yizao Wang