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The advances in materials and biological sciences have necessitated the use of molecular simulations to study polymers. The Markov chain Monte Carlo simulations enable the sampling of relevant microstates of polymeric systems by traversing…

Soft Condensed Matter · Physics 2023-07-24 Monika Angwani , Tushar Mahendrakar , Kaustubh Rane

We present a numerical method to evaluate worldline (WL) path integrals defined on a curved Euclidean space, sampled with Monte Carlo (MC) techniques. In particular, we adopt an algorithm known as YLOOPS with a slight modification due to…

High Energy Physics - Theory · Physics 2020-12-30 Olindo Corradini , Maurizio Muratori

High-order virtual excitations play an important role in microscopic models of nuclear reactions at intermediate energies. However, the factorial growth of their complexity has prevented their consistent inclusion in ab initio many-body…

Nuclear Theory · Physics 2025-05-15 Stefano Brolli , Carlo Barbieri , Enrico Vigezzi

The Diffusion Monte Carlo method is devoted to the computation of electronic ground-state energies of molecules. In this paper, we focus on implementations of this method which consist in exploring the configuration space with a {\bf fixed}…

Numerical Analysis · Mathematics 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

In this article, we discuss the optimal allocation problem in an experiment when a regression model is used for statistical analysis. Monotonic convergence for a general class of multiplicative algorithms for $D$-optimality has been…

Computation · Statistics 2013-10-28 Wei Gao , Ping Shing Chan , Hon Keung Tony Ng , Xiaolei Lu

We use a quantum Monte Carlo method to investigate various classes of 2D spin models with long-range interactions at low temperatures. In particular, we study a dipolar XXZ model with U(1) symmetry that appears as a hard-core boson limit of…

Quantum Gases · Physics 2016-11-11 Michal Maik , Philipp Hauke , Omjyoti Dutta , Jakub Zakrzewski , Maciej Lewenstein

The 15-vertex model of Statistical Mechanics is studied on a square domain with partially oriented boundary. With DWBC the model would reduce to the six-vertex model, but more general boundary configurations are available. After…

Statistical Mechanics · Physics 2018-07-23 Kari Eloranta

In recent years dynamical systems (of deterministic and stochastic nature), describing many models in mathematics, physics, engineering and finances, become more and more complex. Numerical analysis narrowed only to deterministic algorithms…

Numerical Analysis · Mathematics 2024-02-13 Paweł Przybyłowicz

The results of numerical simulation using a modified Monte Carlo method with a thermostat algorithm for a pseudospin model of orthonickelates are presented. Temperature phase diagrams are constructed for various degrees of filling and for…

Statistical Mechanics · Physics 2025-11-18 V. S. Ryumshin , Yu. D. Panov , V. A. Ulitko , A. S. Moskvin

In the bond percolation model on a lattice, we colour vertices with $n_c$ colours independently at random according to Bernoulli distributions. A vertex can receive multiple colours and each of these colours is individually observable. The…

Statistics Theory · Mathematics 2019-06-14 Felix Beck , Bence Mélykúti

Graph clustering is widely used in many data analysis applications. In this paper we propose several parallel graph clustering algorithms based on Monte Carlo simulations and expectation maximization in the context of stochastic block…

Data Structures and Algorithms · Computer Science 2016-09-05 Frederic Prost , Jisang Yoon

We present a Monte Carlo study of the bond and site directed (oriented) percolation models in $(d+1)$ dimensions on simple-cubic and body-centered-cubic lattices, with $2 \leq d \leq 7$. A dimensionless ratio is defined, and an analysis of…

Statistical Mechanics · Physics 2013-10-11 Junfeng Wang , Zongzheng Zhou , Qingquan Liu , Timothy M. Garoni , Youjin Deng

We introduce a new Monte Carlo method by incorporating a guided distribution function to the conventional Monte Carlo method. In this way, the efficiency of Monte Carlo methods is drastically improved. To further speed up the algorithm, we…

Computational Physics · Physics 2009-11-07 S. P. Li

Many high-dimensional complex systems exhibit an enormously complex landscape of possible asymptotic states. Here, we present a numerical approach geared towards analyzing such systems. It is situated between the classical analysis with…

Adaptation and Self-Organizing Systems · Physics 2020-06-24 Maximilian Gelbrecht , Jürgen Kurths , Frank Hellmann

Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how they can be implemented in settings where the parameters live…

We present the loop algorithm, a new type of cluster algorithm that we recently introduced for the F model. Using the framework of Kandel and Domany, we show how to GENERALIZE the algorithm to the arrow flip symmetric 6 vertex model. We…

High Energy Physics - Lattice · Physics 2007-05-23 H. G. Evertz , M. Marcu

An algorithm is proposed that enables the imposition of shape constraints on regression curves, without requiring the constraints to be written as closed-form expressions, nor assuming the functional form of the loss function. This…

Methodology · Statistics 2019-04-08 Kenyon Ng , Berwin A. Turlach , Kevin Murray

We describe results of Monte Carlo simulations on a model that seems to have the necessary ingredients to describe a disordered type-II superconductor in a magnetic field. We compute the free energy cost to twist the direction of the phase…

Condensed Matter · Physics 2007-05-23 J. D. Reger , A. P. Young

The approach to the ergodic limit in Monte Carlo simulations is studied using both analytic and numerical methods. With the help of a stochastic model, a metric is defined that enables the examination of a simulation in both the ergodic and…

Chemical Physics · Physics 2009-11-06 J. P. Neirotti , D. L. Freeman , J. D. Doll

With the goal to provide absolute lower bounds for the best possible running times that can be achieved by $(1+\lambda)$-type search heuristics on common benchmark problems, we recently suggested a dynamic programming approach that computes…

Neural and Evolutionary Computing · Computer Science 2021-02-24 Kirill Antonov , Maxim Buzdalov , Arina Buzdalova , Carola Doerr
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