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# Computational Physics - Science topic

Explore the latest publications in Computational Physics, and find Computational Physics experts.

Publications related to Computational Physics (10,000)

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Operator learning techniques have recently emerged as a powerful tool for learning maps
between infinite-dimensional Banach spaces. Trained under appropriate constraints, they can
also be effective in learning the solution operator of partial differential equations (PDEs) in
an entirely self-supervised manner. In this work we analyze the training d...

The recently proposed high-order TENO scheme [Fu et al., Journal of Computational Physics, 305, pp.333-359] has shown great potential in predicting complex fluids owing to the novel weighting strategy, which ensures the high-order accuracy, the low numerical dissipation, and the sharp shock-capturing capability. However, the applications are still...

Unsupervised machine learning (ML) methods are incorporated in this work to depict correlations and investigate hidden relations between data points that refer to a diffusion coefficient dataset for the Lennard-Jones (LJ) fluid. Widely used clustering algorithms are incorporated, such as the k-means, k-medoids, and DBSCAN, to create data frames of...

In this work, we introduce a deep artificial neural network (ANN) that can detect locations of discontinuity and build a six-point ENO-type scheme based on a set of smooth and discontinuous training data. While a set of candidate stencils of incremental width is constructed, the ANN instead of a classical smoothness indicator is deployed for an ENO...

Variational Bayes (VB) inference algorithm is used widely to estimate both the parameters and the unobserved hidden variables in generative statistical models. The algorithm -- inspired by variational methods used in computational physics -- is iterative and can get easily stuck in local minima, even when classical techniques, such as deterministic...

This paper presents a directional ghost-cell immersed boundary method for low Mach number reacting flows with general boundary conditions, extending the approach described in Chi et al. [C. Chi, A. Abdelsamie, D. Thévenin, A directional ghost-cell immersed boundary method for incompressible flows, Journal of Computational Physics, 404 (2020) 109122...

Multi-fidelity modeling and learning are important in physical simulation-related applications. It can leverage both low-fidelity and high-fidelity examples for training so as to reduce the cost of data generation while still achieving good performance. While existing approaches only model finite, discrete fidelities, in practice, the fidelity choi...

Recent developments in predicting microemulsion phase behavior for use in chemical flooding are based on the hydrophilic-lipophilic deviation (HLD) and net-average curvature (NAC) equation-of-state (EoS). The most advanced version of the HLD-NAC EoS assumes that the three-phase micelle characteristic length is constant as parameters like salinity a...

Boundary element methods produce dense linear systems that can be accelerated
via multipole expansions. Solved with Krylov methods, this implies computing
the matrix-vector products within each iteration with some error, at an
accuracy controlled by the order of the expansion, $p$. We take advantage of a
unique property of Krylov iterations that al...

The ability to extract generative parameters from high-dimensional fields of data in an unsupervised manner is a highly desirable yet unrealized goal in computational physics. This work explores the use of variational autoencoders for non-linear dimension reduction with the specific aim of disentangling the low-dimensional latent variables to ident...

With the advancing digitisation of society and industry we observe a progressing blending of computational, physical, and social processes. The trustworthiness and sustainability of these systems will be vital for our society. However, engineering modern computing systems is complex as they have to: i) operate in uncertain and continuously changing...

As a fun departure from more difficult research, these notes document a relaxing romp into solving a simple mathematical physics problem. We consider the gravity driven fall of a body from a fixed altitude above the Earth's surface. In this case, the acceleration of gravity is determined by the Law of Universal Gravitation. The body (or mass) is in...

Heterogeneous computer architectures (multi-core CPUs with GPUs) offer many benefits but require using fine-grain parallelism in a code with vendor specific programming languages, which creates challenges with both creating and maintaining portable software. Performance portability libraries like Kokkos are revolutionary in that they allow a single...

A closed and predictive particle cloud tracer method is presented. The tracer builds upon the Subgrid Particle Averaged Reynolds Stress Equivalent (SPARSE) formulation first introduced in [Davis et al., Proceedings of the Royal Society A, 473(2199), 2017] for the tracing of particle clouds. It was later extended to a Cloud-In-Cell (CIC) formulation...

Despite the close relationship between planetary science and plasma physics, few advanced numerical tools allow bridging the two topics. The code Menura proposes a breakthrough towards the self-consistent modelling of these overlapping fields, in a novel two-step approach allowing for the global simulation of the interaction between a fully turbule...

In this study, we propose an analytic statistical mechanics approach to solve a fundamental problem in biological physics called protein design. Protein design is an inverse problem of protein structure prediction, and its solution is the amino acid sequence that best stabilizes a given conformation. Contrary to previous computational physics studi...

We investigate quantum inspired algorithms to compute physical observables of quantum many-body systems at finite energies. They are based on the quantum algorithms proposed in [Lu et al. PRX Quantum 2, 020321 (2021)], which use the quantum simulation of the dynamics of such systems, as well as classical filtering and sampling techniques. Here, we...

It is notable that, the nonlocal reaction-diffusion equation carries math and computational physics to the core of extremely dynamic multidisciplinary studies that emerge from a huge assortment of uses. In this investigation, a totally new methodology for building a locally numerical pointwise solution is given by the agent the reproducing kernel a...

Recently, a novel type of neural networks: the physics-informed neural networks, were discovered to have a great deal of applications in computational physics. By integrating knowledge of physical laws and processes in the form of partial differential equations, fast convergence and effective solutions are obtained. With the field of rapidly evolvi...

In computational physics it is standard to approximate continuum systems with discretised representations. Here we consider a specific discretisation of the continuum complex Hilbert space of quantum mechanics - a discretisation where squared amplitudes and complex phases are rational numbers. The fineness of this discretisation is determined by a...

One promising cancer therapy is related to the treatment of diseased cells through thermal ablation by an individual or an agglomeration of nanoparticles acting as photothermal agents. The main principle of such a therapy consists in the photo-energy absorption by the nanoparticles and its conversion into heat in order to kill the biological media/...

Computer algebra systems play an important role in science as they facilitate the development of new theoretical models. The resulting symbolic equations are often implemented in a compiled programming language in order to provide fast and portable codes for practical applications. We describe sympy2c, a new Python package designed to bridge the ga...

Finding the probability that a stochastic system stays in a certain region of its state space over a specified time—a long-standing problem both in computational physics and in applied and theoretical mathematics—is approached through the extended and multivariate Rice formula. In principle, it applies to any smooth process multivariate both in arg...

In this chapter, we overview intelligent reflecting surface (IRS)-empowered wireless communication systems. We first present the fundamentals of IRS-assisted wireless transmission. On this basis, we explore the integration of IRS with various advanced transmission technologies, such as millimeter wave/Terahertz, non-orthogonal multiple access, mobi...

Enabling fast and accurate physical simulations with data has become an important area of computational physics to aid in inverse problems, design-optimization, uncertainty quantification, and other various decision-making applications. This paper presents a data-driven framework for parametric latent space dynamics identification procedure that en...

Computational thinking (CT) is an essential skill in the twenty-first century. The computational physics course (CPC) is one subject that is designed to support students in the practice of CT. Many studies show that the worksheets could be a solution in a CPC as a scaffold to achieve the CT objectives both online and offline. The study aims to deve...

We construct quantum algorithms to compute physical observables of nonlinear PDEs with M initial data. Based on an exact mapping between nonlinear and linear PDEs using the level set method, these new quantum algorithms for nonlinear Hamilton-Jacobi and scalar hyperbolic PDEs can be performed with a computational cost that is independent of M, for...

Computer Physics Communications
Available online 16 June 2022, 108452
In Press, Journal Pre-proofWhat are Journal Pre-proof articles?
CellListMap.jl: Efficient and customizable cell list implementation for calculation of pairwise particle properties within a cutoff
Author links open overlay panelLeandroMartínez
https://doi.org/10.1016/j.cpc.2022.10...

High-resolution computed micro-tomography is an important area of science, which correlates well with several experimental methodologies and serves as a basis for advanced computational physics studies, in which high-resolution images are used as input to different scientific simulation models. The dataset presented herein includes (raw) grayscale...

Resumen-El objetivo de la investigación fue mostrar la importancia que tiene el uso del software Tracker para el análisis del movimiento parabólico. En la primera etapa, en clase, se explicó la cinemática del movimiento parabólico y en la segunda etapa, los estudiantes construyeron una catapulta, se familiarizaron con la interfaz del programa, grab...

We are seeking a Postdoctoral Appointee at Sandia National Laboratories to join our department! This position involves research on surrogate and reduced order modeling with an eye towards developing methods that can be deployed to large-scale computational physics simulations. This position will also involve collaboration with domain experts to app...

MS2 morphology is strongly influenced by several parameters including the addition of a chelating agent and sulfidation temperature. In this work, we report the use of citric acid as chelating agent in order to prepare a series of WS2/Al2O3 catalysts that were submitted to sulfidation at several temperatures. The effect of these two parameters in t...

The concept of magnetohydrodynamic (MHD) flow control is of current interest for its applications in spacecraft reentry and aerodynamic control for hypersonic vehicles. This work presents an efficient approach for realistically simulating MHD effects in weakly ionised plasmas produced by hypersonic flows. The governing equations consists of the ful...

The objective of this paper is to analyse and demonstrate the dynamics of Kala-azar infected group using stochastic model, particularly using simple SIR model with python script over time. The model is used under a closed population with N = 100, transmission rate coefficient β = 0.09, recovery rate γ = 0.03 and initial condition I(0) = 1. In the p...

Quantum computation represents an emerging framework to solve lattice gauge theories (LGTs) with arbitrary gauge groups, a general and long-standing problem in computational physics. While quantum computers may encode LGTs using only polynomially increasing resources, a major open issue concerns the violation of gauge invariance during the dynamics...

Section 1.2, in case of not seeing well inside the .pdf:
• And second to the collisional radiative average atom models, making ATMED CR possible the computation of relativistic orbital fractional populations as a consequence of the nlj-splitting of the screened hydrogenic atomic model; and so improving the resolution and precision of atomic and ra...

Compressible multi-materialflows are encountered in a wide range of natural phenomena and industrial applications, such as supernova explosions in space, high speed flows in jet and rocket propulsion, underwater explosions, and vapor explosions in post accidental situations in nuclear reactors. In the numerical simulations of these flows, interface...

The data flow paradigm has established itself as a powerful approach to machine learning. In fact, it isalso very powerful for computational physics, although it is not used as much in the field. One of thecomplications is that physical models are much less homogeneous compared to ML, which makestheir description a complicated task. In this paper w...

In Grossu (2022) [1] it was discussed the migration of Hyper-Fractal Analysis from Visual Basic 6 to C# .Net. The main goal of current work was developing a medical module for fractal analysis of computed tomography multi-channel images. A new tool for comparing images by RGB channels superposition was also considered. This could be of particular i...

In this paper, we perform the numerical modelling of lower-band VLF chorus in the earth’s magnetosphere. Assuming parallel propagation the 1d3v code has one spatial dimension z along the ambient magnetic field, which has a parabolic z dependence about the equator. The method used is Vlasov Hybrid Simulation (VHS) also known in the literature as the...

We discuss two parallelization schemes for MagIC, an open-source, high-performance, pseudo-spectral code for the numerical solution of the magnetohydrodynamics equations in a rotating spherical shell. MagIC calculates the non-linear terms on a numerical grid in spherical coordinates, while the time step updates are performed on radial grid points w...

Numerical simulations of Earth's weather and climate require substantial amounts of computation. This has led to a growing interest in replacing subroutines that explicitly compute physical processes with approximate machine learning (ML) methods that are fast at inference time. Within weather and climate models, atmospheric radiative transfer (RT)...

This paper is devoted to the study of collisionless multicomponent plasma expansion in vacuum discharges. Based on the fundamental principles of physical kinetics formulated for vacuum discharge plasma, an answer is given to the following question: What is the main mechanism of cathode plasma transport from cathode to anode, which ensures non-therm...

Nanoscale devices, either biological or artificial, operate in a regime where the usual assumptions of a structureless Markovian bath do not hold. Being able to predict and study the dynamics of such systems is crucial and is usually done by tracing out the bath degrees of freedom, which implies losing information about the environment. To go beyon...

Cyber-Physical-Human System (CPHS) is receiving increasing attention as an interrelated system that integrates computing, physical, and human resources. Different from existing computing paradigms, CPHS generally comprises heterogeneous software and hardware resources from multiple resource providers and allows interaction among them. The existing...

A bstract
Finding out root patterns of quantum integrable models is an important step to study their physical properties in the thermodynamic limit. Especially for models without U(1) symmetry, their spectra are usually given by inhomogeneous T − Q relations and the Bethe root patterns are still unclear. In this paper with the antiperiodic XXZ spin...

Visualization in three dimensions is invaluable for understanding the nature of condensed and fluid systems, but it is not always easy. In nature it is hard to view sample interiors, but on computers it is possible. We describe and contrast two opposite approaches - “smoke” visualization for viewing interiors of liquid samples and interactive WebGL...

In this article, the structure of a deep ultraviolet laser is proposed. The material gain of this laser structure reaches a maximum at the 262 nm band. The active area structures of different numbers of quantum wells are simulated via Crosslight software. The number of quantum enthalpies is designed to be single, double, triple and quadruple. The p...

The Poisson–Boltzmann equation (PBE) arises in various disciplines including biophysics,
electrochemistry, and colloid chemistry, leading to the need for efficient and accurate simulations of PBE. However, most of the finite difference/element methods developed so far are rather complicated to implement. In this study, we develop a ResNet-based art...

Lab-on-a-chip (LOC) devices capable of manipulating micro/nano-sized samples have spurred advances in biotechnology and chemistry. Designing and analyzing new and more advanced LOCs require accurate modeling and simulation of sample/particle dynamics inside such devices. In this work, we present a generalized computational physics model to simulate...

We present an a posteriori shock-capturing finite volume method algorithm called GP-MOOD that solves a compressible hyperbolic conservative system at high-order solution accuracy (e.g., third-, fifth-, and seventh-order) in multiple spatial dimensions. The GP-MOOD method combines two methodologies, the polynomial-free spatial reconstruction methods...

In most of the existing sound source location methods, the final result only contains the direction of arrival (DOA) of the sound source but does not contain the relative distance of the sound source. In order to get the true position of the sound source, this paper proposes a multi-sound source position estimation method based on sparse component...

A general theoretical and numerical framework for the strength and mass optimisation of variable-stiffness composite laminates (VSCLs) is presented in this work. The optimisation is performed in the context of the first-level problem of the multi-scale two-level optimisation strategy (MS2LOS) for VSCLs. Both the failure load maximisation problem (s...

Uncertainty quantification in computational physics requires running many simulations. For some industrial applications, the complexity of the numerical model is incompatible with the number of simulations to be run. Solving physics equations in a reduced computation time is therefore essential for the design of safe and reliable systems. In this t...

Concrete is one of the most commonly used construction materials, yet industrial fabrication continues to default to established standards of planar formwork and uniform cross-sections for the sake of simplicity and predictability. The research conducted within Concrete Form[ing]work explored alternative methods of producing concrete formwork with...

Mémoire de Fin d'Étude Mastere de Physique des Hautes Énergies, Astrophysique et Physique Computationnelle Parcours Physique des Hautes Énergies et Physique Computationnelle Sujet : Physique du neutrino auprès du détecteur KM3NeT Auteur : Marouane BENHASSI Encadrant : Mohamed CHABAB

The widespread use of neural networks across different scientific domains often involves constraining them to satisfy certain symmetries, conservation laws, or other domain knowledge. Such constraints are often imposed as soft penalties during model training and effectively act as domain-specific regularizers of the empirical risk loss. Physics-inf...

The COVID-19 pandemic has made conducting in-person research a health risk for interviewers and participants. Near the start of the pandemic, many universities pivoted to emergency remote teaching where courses were delivered remotely in observance of safety guidelines. The safety guidelines also necessitated that research be done remotely. We desi...

RichardsFoam3 is an updated version of the OpenFOAM solver RichardsFoam, previously presented in ”An open source massively parallel solver for Richards equation: Mechanistic modelling of water fluxes at the watershed scale” by L. Orgogozo et al (2014, Computer Physics Communications 185 : 3358-3371. DOI: 10.1016/j.cpc.2014.08.004), and in the new v...

The strong computing power of Cloud computing enables rapid processing of mass data. Hadoop, the most extensively-distributed architecture among Cloud-computing platforms, uses the MapReduce programming model in a server cluster to separate the applications into many small parts in order to conduct arithmetic processing of big data. Virtualization...

Obstetric studies had long revealed that the human female mental state, although subjective, has a nonlinear relation to the gestation, which could eventually leads to eugenics characteristics. Due to the difference of regions, there are differences between the data, people want to analyze the correlation between the survey data of different region...

This paper addresses the numerical simulation of nonlinear eigenvector problems such as the Gross-Pitaevskii and Kohn-Sham equation arising in computational physics and chemistry. These problems characterize critical points of energy minimization problems on the infinite-dimensional Stiefel manifold. To efficiently compute minimizers, we propose a...

With the advancing digitisation of society and industry we observe a progressing blending of computational, physical, and social processes. The trustworthiness and sustainability of these systems will be vital for our society. However, engineering modern computing systems is complex as they have to: i) operate in uncertain and continuously changing...