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We describe a number of strategies for minimizing and calculating accurately the statistical uncertainty in quantum Monte Carlo calculations. We investigate the impact of the sampling algorithm on the efficiency of the variational Monte…

Computational Physics · Physics 2012-02-14 R. M. Lee , G. J. Conduit , N. Nemec , P. Lopez Rios , N. D. Drummond

Due to the potential benefits of parallelization, designing unbiased Monte Carlo estimators, primarily in the setting of randomized multilevel Monte Carlo, has recently become very popular in operations research and computational…

Computation · Statistics 2024-04-03 Guanyang Wang , Jose Blanchet , Peter W. Glynn

Markov chain Monte Carlo (MCMC) sampling is an important and commonly used tool for the analysis of hierarchical models. Nevertheless, practitioners generally have two options for MCMC: utilize existing software that generates a black-box…

Monte Carlo simulations are used to study the behavior of two polymers under confinement in a cylindrical tube. Each polymer is modeled as a chain of hard spheres. We measure the free energy of the system, F, as a function of the distance…

Soft Condensed Matter · Physics 2015-06-22 James M. Polson , Logan G. Montgomery

We adapted existing polymer growth strategies for equilibrium sampling of peptides described by modern atomistic forcefields with implicit solvent. The main novel feature of our approach is the use of pre-calculated statistical libraries of…

Biological Physics · Physics 2010-03-04 A. B. Mamonov , X. Zhang , D. M. Zuckerman

Performing numerical integration when the integrand itself cannot be evaluated point-wise is a challenging task that arises in statistical analysis, notably in Bayesian inference for models with intractable likelihood functions. Markov…

Computation · Statistics 2020-06-17 Lawrence Middleton , George Deligiannidis , Arnaud Doucet , Pierre E. Jacob

The use of the Monte Carlo technique in a reliable and inexpensive way without the need for a standard radioactive source in determining the detector efficiency is becoming widespread every passing day. It is important to model the detector…

Instrumentation and Detectors · Physics 2023-01-18 Esra Uyar , Zeynep Aybüke Günekbay

We give the first polynomial-time algorithm for robust regression in the list-decodable setting where an adversary can corrupt a greater than $1/2$ fraction of examples. For any $\alpha < 1$, our algorithm takes as input a sample…

Data Structures and Algorithms · Computer Science 2019-05-31 Sushrut Karmalkar , Adam R. Klivans , Pravesh K. Kothari

We use an off-lattice microscopic model for solutions of equilibrium polymers (EP) in a lamellar shear flow generated by means of a self-consistent external field between parallel hard walls. The individual conformations of the chains are…

Soft Condensed Matter · Physics 2009-10-31 A. Milchev , J. P. Wittmer , D. P. Landau

We develop Monte Carlo simulations for uniformly charged polymers and machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments.…

Soft Condensed Matter · Physics 2025-11-21 Lijie Ding , Chi-Huan Tung , Jan-Michael Y. Carrillo , Wei-Ren Chen , Changwoo Do

We consider the well-known problem of enumerating all triangles of an undirected graph. Our focus is on determining the input/output (I/O) complexity of this problem. Let $E$ be the number of edges, $M<E$ the size of internal memory, and…

Data Structures and Algorithms · Computer Science 2014-03-25 Rasmus Pagh , Francesco Silvestri

We compare different methods for sampling from discrete probability distributions and introduce a new algorithm which is especially efficient on massively parallel processors, such as GPUs. The scheme preserves the distribution properties…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-02 Nikolaus Binder , Alexander Keller

The problem of monotone missing data has been broadly studied during the last two decades and has many applications in different fields such as bioinformatics or statistics. Commonly used imputation techniques require multiple iterations…

Machine Learning · Computer Science 2020-09-25 Thu Nguyen , Duy H. M. Nguyen , Huy Nguyen , Binh T. Nguyen , Bruce A. Wade

We give efficient algorithms for volume sampling, i.e., for picking $k$-subsets of the rows of any given matrix with probabilities proportional to the squared volumes of the simplices defined by them and the origin (or the squared volumes…

Data Structures and Algorithms · Computer Science 2010-04-26 Amit Deshpande , Luis Rademacher

We present computer simulations of three systems of randomly branching polymers in d=3 dimensions: ideal trees and self-avoiding trees with annealed and quenched connectivities. In all cases, we performed a detailed analysis of trees…

Statistical Mechanics · Physics 2016-10-11 Angelo Rosa , Ralf Everaers

We study the problem of estimating the covariance matrix of a high-dimensional distribution when a small constant fraction of the samples can be arbitrarily corrupted. Recent work gave the first polynomial time algorithms for this problem…

Machine Learning · Computer Science 2019-06-12 Yu Cheng , Ilias Diakonikolas , Rong Ge , David Woodruff

This paper makes three contributions to estimating the number of perfect matching in bipartite graphs. First, we prove that the popular sequential importance sampling algorithm works in polynomial time for dense bipartite graphs. More…

Probability · Mathematics 2022-07-07 Yeganeh Alimohammadi , Persi Diaconis , Mohammad Roghani , Amin Saberi

We study the \emph{{interval completion}} problem, which asks for the insertion of a set of at most $k$ edges to make a graph of $n$ vertices into an interval graph. We focus on chordal graphs with no small obstructions, where every…

Data Structures and Algorithms · Computer Science 2013-06-14 Yixin Cao

We investigate the relationship between several enumeration complexity classes and focus in particular on problems having enumeration algorithms with incremental and polynomial delay (IncP and DelayP respectively). We show that, for some…

Computational Complexity · Computer Science 2017-07-04 Florent Capelli , Yann Strozecki

The absorption of free linear chains in a polymer brush was studied with respect to chain size $L$ and compatibility $\chi$ with the brush by means of Monte Carlo (MC) simulations and Density Functional Theory (DFT) / Self-Consistent Field…

Soft Condensed Matter · Physics 2015-05-18 A. Milchev , S. A. Egorov , K. Binder