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We provide an introduction to molecular dynamics simulations in the context of the Kob-Andersen model of a glass. We introduce a complete set of tools for doing and analyzing the results of simulations at fixed NVE and NVT. The modular…

Computational Physics · Physics 2020-05-25 K. Vollmayr-Lee

Ensuring the quality of quantum programs is increasingly important; however, traditional static analysis techniques are insufficient due to the unique characteristics of quantum computing. Quantum-specific linting tools, such as LintQ, have…

Software Engineering · Computer Science 2025-04-08 Seung Yeob Shin , Fabrizio Pastore , Domenico Bianculli

Supersymmetric models are grounded in the intriguing concept of a hypothetical symmetry that relates bosonic and fermionic particles. This symmetry has profound implications, offering valuable extensions to the Standard Model of particle…

High Energy Physics - Lattice · Physics 2024-11-25 Emanuele Mendicelli , David Schaich

The lattice Boltzmann method (LBM) has emerged as a prominent technique for solving fluid dynamics problems due to its algorithmic potential for computational scalability. We introduce XLB library, a Python-based differentiable LBM library…

Computational Physics · Physics 2024-04-03 Mohammadmehdi Ataei , Hesam Salehipour

Physics simulators are widely used in robotics fields, from mechanical design to dynamic simulation, and controller design. This paper presents an open-source MATLAB/Simulink simulator for rigid-body articulated systems, including…

Robotics · Computer Science 2022-11-18 Nuno Guedelha , Venus Pasandi , Giuseppe L'Erario , Silvio Traversaro , Daniele Pucci

We consider dynamically constrained Monte-Carlo dynamics and show that this leads to the generation of long ranged effective interactions. This allows us to construct a local algorithm for the simulation of charged systems without ever…

Statistical Mechanics · Physics 2009-11-10 L. Levrel , F. Alet , J. Rottler , A. C. Maggs

Boltzmann codes are used extensively by several groups for constraining cosmological parameters with Cosmic Microwave Background and Large Scale Structure data. This activity is computationally expensive, since a typical project requires…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-27 Diego Blas , Julien Lesgourgues , Thomas Tram

Inhomogeneities in real-world data, e.g., due to changes in the observation noise level or variations in the structural complexity of the source function, pose a unique set of challenges for statistical inference. Accounting for them can…

Machine Learning · Computer Science 2023-12-13 Danny Panknin , Stefan Chmiela , Klaus-Robert Müller , Shinichi Nakajima

The auxiliary-field quantum Monte Carlo (AFQMC) method is a general numerical method for correlated many-electron systems, which is being increasingly applied in lattice models, atoms, molecules, and solids. Here we introduce the theory and…

Computational Physics · Physics 2021-02-24 Hao Shi , Shiwei Zhang

The current work presents a novel COllaborative Open-source Lattice Boltzmann Method framework, so-called CooLBM. The computational framework is developed for the simulation of single and multi-component multi-phase problems, along with a…

Computational Physics · Physics 2025-02-19 R. Alamian , A. K. Nayak , M. S. Shadloo

We propose a general scheme for a digital construction of lattice gauge theories with dynamical fermions. In this method, the four-body interactions arising in models with $2+1$ dimensions and higher, are obtained stroboscopically, through…

Quantum Physics · Physics 2017-02-21 Erez Zohar , Alessandro Farace , Benni Reznik , J. Ignacio Cirac

We explore the potential application of quantum computers to the examination of lattice holography, which extends to the strongly-coupled bulk theory regime. With adiabatic evolution, we compute the ground state of a spin system on a…

High Energy Physics - Lattice · Physics 2023-12-19 Ying-Ying Li , Muhammad Omer Sajid , Judah Unmuth-Yockey

Active learning (AL) accelerates scientific discovery by prioritizing the most informative experiments, but traditional machine learning (ML) models used in AL suffer from cold-start limitations and domain-specific feature engineering,…

Machine Learning · Computer Science 2025-12-05 Hongchen Wang , Rafael Espinosa Castañeda , Jay R. Werber , Yao Fehlis , Edward Kim , Jason Hattrick-Simpers

A new approximation hierarchy, called the LPSUB$m$ scheme, is described for the coupled cluster method (CCM). It is applicable to systems defined on a regular spatial lattice. We then apply it to two well-studied prototypical (spin-1/2…

Strongly Correlated Electrons · Physics 2011-05-05 R F Bishop , P H Y Li

Recently, Large Language Models (LLMs) have showcased their potential in various natural language processing tasks, including code generation. However, while significant progress has been made in adapting LLMs to generate code for several…

Machine Learning · Computer Science 2024-07-29 Erica Coppolillo , Francesco Calimeri , Giuseppe Manco , Simona Perri , Francesco Ricca

Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key areas: mining scientific literature , predictive modelling,…

Computation and Language · Computer Science 2025-11-17 Fengxu Yang , Weitong Chen , Jack D. Evans

Immersed boundary-lattice Boltzmann method (IB-LBM) has been widely used for simulation of particle-laden flows recently. However, it was limited to small-scale simulations with no more than O(103) particles. Here, we expand IB-LBM for…

Computational Physics · Physics 2020-02-21 Maoqiang Jiang , Jing Li , Zhaohui Liu

We have developed an efficient simulation algorithm for strongly interacting relativistic fermions in two-dimensional field theories based on a formulation as a loop gas. The loop models describing the dynamics of the fermions can be mapped…

High Energy Physics - Lattice · Physics 2009-11-05 Urs Wenger

Learning exchange correlation functionals, used in quantum chemistry calculations, from data has become increasingly important in recent years, but training such a functional requires sophisticated software infrastructure. For this reason,…

Machine Learning · Computer Science 2023-09-29 Advika Vidhyadhiraja , Arun Pa Thiagarajan , Shang Zhu , Venkat Viswanathan , Bharath Ramsundar