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Grand canonical Monte Carlo simulations are used to explore the metastable fluid-fluid coexistence curve of the modified Lennard-Jones model of globular proteins of ten Wolde and Frenkel (Science, v277, 1975 (1997)). Using both mixed-field…

Soft Condensed Matter · Physics 2009-11-10 D. L. Pagan , M. E. Gracheva , J. D. Gunton

Many inverse problems in nuclear fusion and high-energy astrophysics research, such as the optimization of tokamak reactor geometries or the inference of black hole parameters from interferometric images, necessitate high-dimensional…

Machine Learning · Computer Science 2025-05-09 Jonathan Gorard , Ammar Hakim , Hong Qin , Kyle Parfrey , Shantenu Jha

Quantum Monte Carlo (QMC) methods can very accurately compute ground state properties of quantum systems. We applied these methods to a system of boson hard spheres to get exact, infinite system size results for the ground state at several…

Computational Physics · Physics 2016-09-08 Mark Dewing

We discuss the QCD critical point at finite density through the study of many flavor QCD, in which two light flavors and Nf massive flavors exist. Performing simulations of QCD with two flavors of improved Wilson fermions, we calculate…

High Energy Physics - Lattice · Physics 2015-12-29 Ryo Iwami , Shinji Ejiri , Norikazu Yamada

Many Monte Carlo light transport simulations use multiple importance sampling (MIS) to weight between different path sampling strategies. We propose to use the path throughput to compute the MIS weights instead of the commonly used…

Graphics · Computer Science 2018-09-07 Johannes Jendersie

Quantum Monte Carlo methods are powerful tools for studying quantum many-body systems but face difficulties in accessing excited states and in treating sign problems. We present a continuous-time path-integral Monte Carlo method for…

Strongly Correlated Electrons · Physics 2025-12-16 Abhishek Karna , Hansen S. Wu , Shailesh Chandrasekharan , Ribhu K. Kaul

The kinematic end-point technique for measuring the masses of supersymmetric particles in R-Parity conserving models at hadron colliders is re-examined with a focus on exploiting additional constraints arising from correlations in invariant…

High Energy Physics - Phenomenology · Physics 2010-04-23 Davide Costanzo , Daniel R. Tovey

We propose two efficient algorithms for configurational sampling of systems with rough energy landscape. The first one is a new method for the determination of the multicanonical weight factor. In this method a short replica-exchange…

Statistical Mechanics · Physics 2009-10-31 Yuji Sugita , Yuko Okamoto

We present a formalism of the transition matrix Monte Carlo method. A stochastic matrix in the space of energy can be estimated from Monte Carlo simulation. This matrix is used to compute the density of states, as well as to construct…

Statistical Mechanics · Physics 2011-12-30 Jian-Sheng Wang , Robert H. Swendsen

We present results on lattice QCD at finite temperature (T) and chemical potential (\mu). We apply the overlap-improving multi-parameter reweighting technique for n_f=4 and 2+1 staggered QCD. We use semi-realistic masses on L_t=4 lattices.…

High Energy Physics - Lattice · Physics 2008-11-26 Z. Fodor , S. D. Katz

We present clear numerical evidence for the coexistence of metallic and insulating dynamical mean field theory(DMFT) solutions in a half-filled single-band Hubbard model with bare semicircular density of states at finite temperatures.…

Strongly Correlated Electrons · Physics 2009-10-31 Jaewook Joo , Viktor Oudovenko

Re-weighting is a useful tool that has been employed in Lattice QCD in different contexts including, tuning the strange quark mass, approaching the light quark mass regime, and simulating electromagnetic fields on top of QCD gauge…

High Energy Physics - Lattice · Physics 2011-12-20 Abdou Abdel-Rehim , William Detmold , Kostas Orginos

Multi-dimensional density of states provides a useful description of complex frustrated systems. Recent advances in Monte Carlo methods enable efficient calculation of the density of states and related quantities, which renew the interest…

Disordered Systems and Neural Networks · Physics 2009-11-10 Yukito Iba , Hisanao Takahashi

We investigate the properties of a sequential Monte Carlo method where the particle weight that appears in the algorithm is estimated by a positive, unbiased estimator. We present broadly-applicable convergence results, including a central…

Methodology · Statistics 2022-08-26 Paul B. Rohrbach , Robert L. Jack

We extend a systematic renormalization procedure for quantum field theory to include particle masses and present several applications. We use a Hamiltonian formulation and light-front quantization because this may produce a convergent…

High Energy Physics - Phenomenology · Physics 2009-09-25 Roger D. Kylin

Matrix element reweighting is a powerful experimental technique widely employed to maximize the amount of information that can be extracted from a collider data set. We present a procedure that allows to automatically evaluate the weights…

High Energy Physics - Phenomenology · Physics 2011-02-02 P. Artoisenet , V. Lemaître , F. Maltoni , O. Mattelaer

Monte Carlo simulations are an essential tool in particle physics data analysis. Events are typically generated alongside weights that redistribute the cross section of the simulated process across the phase space. These weights can be…

High Energy Physics - Phenomenology · Physics 2026-05-13 Benjamin Nachman , Dennis Noll

Based on multiple parallel short molecular dynamics simulation trajectories, we designed the reweighted ensemble dynamics (RED) method to more efficiently sample complex (biopolymer) systems, and to explore their hierarchical metastable…

Statistical Mechanics · Physics 2015-02-24 Linchen Gong , Xin Zhou , Zhong-Can Ou-Yang

We employ a general Monte Carlo method to test composite hypotheses of goodness-of-fit for several popular multivariate models that can accommodate both asymmetry and heavy tails. Specifically, we consider weighted L2-type tests based on a…

Methodology · Statistics 2023-03-09 Maicon J. Karling , Marc G. Genton , Simos G. Meintanis

The montecarlo method, which is quite commonly used to solve maximum entropy problems in statistical physics, can actually be used to solve inverse problems in a much wider context. The probability distribution which maximizes entropy can…

Statistical Mechanics · Physics 2007-05-23 Jan Naudts
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