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Publications related to Computational Physics (10,000)
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von Neumann algebras have been playing an increasingly important role in the context of gauge theories and gravity. The crossed product presents a natural method for implementing constraints through the commutation theorem, rendering it a useful tool for constructing gauge-invariant algebras. The crossed product of a Type III algebra with its modul...
Preprint
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The Holographic Principle suggests that the information content of a higher-dimensional space can be encoded on a lower-dimensional boundary, fundamentally reshaping our understanding of spacetime and quantum gravity. However, the process of dimensional reduction remains an open question—does it occur instantaneously, or does it involve intermediat...
Preprint
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Modern physics describes the universe in terms of particles, forces, and space-time, yet fundamental gaps remain. Quantum mechanics and general relativity remain incompatible, and the nature of consciousness and intelligence is still unresolved. This paper explores an alternative paradigm: the Computational Aether hypothesis, proposing that reality...
Preprint
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The nature of good and evil, free will, and consciousness has been a central debate in philosophy, theology, and science for millennia. Traditional perspectives view good and evil as opposing forces, but emerging insights from physics, information theory, and computation suggest a deeper principle at play—an entropic balance governing knowledge evo...
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Exponentiating sums of non-commuting operators is a central yet computation-ally demanding task in physics and mathematics, particularly in quantum mechanics where Hamiltonians typically consist of multiple, non-commuting terms. To address this challenge, our study systematically presents and analyzes the Suzuki-Trotter decomposition-a powerful met...
Preprint
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This comprehensive review paper explores Trotterization and its pivotal role in digital quantum simulation, providing both theoretical foundations and practical insights. The work delves into fundamental decomposition techniques (including first- and second-order Suzuki-Trotter methods), advanced error mitigation strategies, and optimizations for H...
Preprint
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Quantum randomness is conventionally regarded as an irreducible feature of nature, fundamental to quantum mechanics and essential for applications in cryptography, secure communication, and probabilistic computing. Quantum number generators (QNGs) leverage quantum uncertainty to produce sequences that are assumed to be purely random. However, emerg...
Preprint
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Quantum number generators (QNGs) are widely regarded as the gold standard for generating truly random sequences, leveraging the fundamental indeterminacy of quantum mechanics. Unlike classical pseudo-random number generators, which rely on deterministic algorithms, QNGs extract randomness from quantum phenomena such as vacuum fluctuations, photon b...
Preprint
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The nature of randomness has long been a central question in both quantum mechanics and artificial intelligence. The Born rule, a fundamental postulate of quantum mechanics, assumes that measurement outcomes follow purely probabilistic distributions. However, emerging evidence from quantum chaos, fractal wavefunctions, and structured stochasticity...
Article
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This study explores multi-soliton solutions and their interactions within the framework of the Klein-Fock-Gordon (K-F-G) equation. The K-F-G equation plays a crucial role in modeling relativistic wave phenomena and has diverse applications in describing energy particles in physics. The newly modified simple equation (NMSE) method is employed to ana...
Article
Full-text available
Exponentiating sums of non-commuting operators is a central yet computationally demanding task in physics and mathematics, particularly in quantum mechanics where Hamiltonians typically consist of multiple, non-commuting terms. To address this challenge, our study systematically presents and analyzes the Suzuki–Trotter decomposition—a powerful meth...
Article
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Special effects are a defining feature of modern filmmaking, transforming imaginative ideas into visually stunning and believable cinematic experiences. At the core of these effects lies the science of physics, which provides the tools and principles necessary to simulate motion, light, sound, and complex natural phenomena. Physics enables filmmake...
Preprint
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The logarithm-determinant is a common quantity in many areas of physics and computer science. Derivatives of the logarithm-determinant compute physically relevant quantities in statistical physics models, quantum field theories, as well as the inverses of matrices. A multi-variable version of the quantum gradient algorithm is developed here to eval...
Preprint
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The complexity of modern scientific challenges demands a comprehensive framework capable of bridging the gap between diverse mathematical and physical structures. Traditional topological and geometric frameworks, while powerful, often struggle to fully capture the behavior of irregular, dynamic, or computationally complex spaces such as fractals, k...
Article
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The comprehensive progress of mental and physical quality is majorly influenced by the college physical education, which is considered a part of the educational system. Developing a scientific and efficient evaluation index is significant to compute physical education teaching quality. The traditional methods of assessing performance in physical ed...
Preprint
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The unification of quantum mechanics and general relativity remains one of the most profound challenges in modern physics. Quantum mechanics accurately describes the behavior of matter and energy at microscopic scales, while general relativity governs the dynamics of spacetime and gravity on cosmological scales. However, these two foundational theo...
Article
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We perform a set of high-fidelity simulations of geochemical reactions within three-dimensional discrete fracture networks (DFN) and use various machine learning techniques to determine the primary factors controlling mineral dissolution. The DFN are partially filled with quartz that gradually dissolves until quasi-steady state conditions are reach...
Article
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For solving hyperbolic conservation laws that arise frequently in computational physics, high order finite volume WENO (FV-WENO) schemes and discontinuous Galerkin (DG) methods are more popular because of their applicability to any monotone fluxes and easily handle complicated geometries and boundary conditions. However, when there are smaller scal...
Article
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Gegenbauer polynomial approximations play an important role in applied mathematics and computational physics. In this paper, we present sharp bounds for Gegenbauer expansion coefficients of functions belonging to fractional spaces and then derive some new and sharp error bounds for Gegenbauer approximations in weighted \documentclass[12pt]{minimal}...
Article
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This study presented a comprehensive analysis of nonlinear fractional systems governed by the advection-dispersion equations (ADE), utilizing the Mohand transform iterative method (MTIM) and the Mohand residual power series method (MRPSM). By incorporating the Caputo fractional derivative, we enhanced the modeling capability for fractional-order di...
Article
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In this article, the spatial symmetric nonlinear dispersive wave model in (2+1)-dimensions is studied, which have many applications in wave phenomena and soliton interactions in a two-dimensional space with time. In this framework, the Hirota bilinear form is applied to acquire diverse types of breather wave solutions from the foresaid equation. Ab...
Research
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This research investigates how the dodecahedron linear string field hypothesis (DLSFH) introduces fractal symmetries into computational physics. It provides a novel framework for understanding algorithmic randomness, such as Chaitin's constant (Ω), in terms of higher-dimensional geometric and fractal structures. By integrating concepts of self-simi...
Preprint
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The presentation will provide an overview of the capabilities of the Methodical Accelerator Design Next Generation (MAD-NG) tool. MAD-NG is a standalone, all-in-one, multi-platform tool well-suited for linear and nonlinear optics design and optimization, and has already been used in large-scale studies such as HiLumi-LHC or FCC-ee. It embeds LuaJIT...
Article
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The structural instability observed owing to Sn²⁺ and the toxic effects of lead has prohibited the commercial use of all inorganic CsPb1-xSnxBr3 for optoelectronic memory device applications. In this work, we have inspected the structural, mechanical, electronic, optical, and thermoelectric response of all inorganic halide perovskite CsPb1-xGexBr3...
Preprint
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The acceleration of material property calculations while maintaining ab initio accuracy (1 meV/atom) is one of the major challenges in computational physics. In this paper, we introduce a Python package enhancing the computation of (finite temperature) material properties at the ab initio level using machine learning interatomic potentials (MLIP)....
Article
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Next-generation gravitational-wave detectors, with their improved sensitivity and wider frequency bandwidth, will be capable of observing almost every compact binary coalescence signal from epochs before the first stars began to form, increasing the number of detectable binaries to hundreds of thousands annually. This will enable us to observe comp...
Preprint
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With the approach of the High Luminosity Large Hadron Collider (HL-LHC) era set to begin particle collisions by the end of this decade, it is evident that the computational demands of traditional collision simulation methods are becoming increasingly unsustainable. Existing approaches, which rely heavily on first-principles Monte Carlo simulations...
Preprint
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This article presents updates to lifex [Africa, SoftwareX (2022)], a C++ library for high-performance finite element simulations of multiphysics, multiscale and multidomain problems. In this release, we introduce an additional intergrid transfer method for non-matching multiphysics coupling on the same domain, significantly optimize nearest-neighbo...
Article
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Turbidity currents are a sort of density-driven flow carrying particles that are generated between fluids with small density differences. They also are a mechanism responsible for the deposition of sediments on a seabed. A deep understanding of this phenomenon may help geologists on strategic knowledge in oil exploration. We simulate such currents...
Article
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Contribution: This study proffers a practical flexible framework for teachers and researchers embodying diverse computing pedagogies, to impart computing education (CE) to autistic students. The framework is based on the tenets of inclusion and personalised learning manipulating explicit CE pedagogies. Background: Research and anecdotal evidence...
Preprint
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In computational physics, chemistry, and biology, the implementation of new techniques in a shared and open source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited i...
Preprint
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The universe, at its most fundamental level, may operate as a vast computational system, with Planck-scale operations serving as its foundational "ticks." These operations occur at the smallest measurable scales of space and time, where the classical notions of continuity break down, and quantum phenomena dominate. In this paper, we argue that the...
Preprint
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Quantum computers, with their unique ability to process information through quantum superposition, entanglement, and interference, are transforming the landscape of computation. These machines push beyond the capabilities of classical systems, solving complex problems with unparalleled efficiency. However, as quantum systems grow in complexity, the...
Article
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Los lineamientos curriculares establecidos para la formación de Profesores en Física incluyen explícitamente la construcción de conocimientos y el desarrollo de competencias en Tecnologías de la Información y de la Comunicación. Esto se debe a la propia dinámica de la disciplina de referencia y a las demandas del mundo laboral. La conjunción de est...
Preprint
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Since more than 30 years, the equiangular Cubed Sphere CS_N has been used in many domains of Computational Physics, in concurrence with other spherical grids (the longitude-latitude grid, the icosahedral grid, the yin-yang grid, the doubly periodic grid, and so on). Previous studies have analyzed the relation between the set of nodes CS_N and inter...
Article
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This work addresses the analytical solution of the fourth-Order Korteweg–de Vries (KdV4) equation, a nonlinear model describing the dynamics of optical soliton in (2+1) dimensions. To obtain exact results, we use the energy balance approach with two contemporary integration norms. The urgent need for precise mathematical representations in nonlinea...
Article
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Physics‐informed neural networks (PINNs) have successfully addressed various computational physics problems based on partial differential equations (PDEs). However, while tackling issues related to irregularities like singularities and oscillations, trained solutions usually suffer low accuracy. In addition, most current works only offer the traine...
Article
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Em grande parte das aplicações da Termodinâmica nas Engenharias são empregadas as equações das taxas de transferência de calor, de modo que a modelagem matemática e as simulações tomam lugar na construção de importantes dispositivos e equipamentos. O presente artigo traz a modelagem e solução da aplicação de camadas de isolante térmico em sistemas...
Preprint
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We report a novel, computationally efficient approach for solving hard nonlinear problems of reinforcement learning (RL). Here we combine umbrella sampling, from computational physics/chemistry, with optimal control methods. The approach is realized on the basis of neural networks, with the use of policy gradient. It outperforms, by computational e...
Article
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Advanced materials with heterogeneous microstructures enable superior properties unattainable in conventional materials. Challenges remain in predictive design, requiring morphological control principles to retain optimized structures. This review covers computational physics, materials science, and multiscale modeling advances elucidating process-...
Presentation
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This study presents a comprehensive investigation into enhancing computational efficiency in the analysis of porous media through the integration of Monte Carlo ray tracing (MCRT) and machine learning (ML) methodologies. MCRT has long been recognized for its reliability in calculating light-matter interactions within porous structures. However, the...
Preprint
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We present a novel reduced-order Model (ROM) that leverages optimal transport (OT) theory and displacement interpolation to enhance the representation of nonlinear dynamics in complex systems. While traditional ROM techniques face challenges in this scenario, especially when data (i.e., observational snapshots) is limited, our method addresses thes...
Article
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In this article, the potential Kadomtsev-Petviashvili (pKP) type coupled system with variable coefficients is studied, which have many applications in wave phenomena and soliton interactions in a two-dimensional space with time. In this framework, Hirota bilinear form is applied to acquire diverse types of interaction lump solutions from the foresa...
Article
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Microwave ablation is becoming a standard procedure for treating tumors based on heat generation, causing an elevation in the tissue temperature level from 50 to 60 °C, causing tissue death. Microwave ablation is associated with uniform cell killing within ablation zones, multiple-antenna capability, low complication rates, and long-term survival....
Preprint
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Photonic crystals (PhCs) are periodic dielectric structures that exhibit unique electromagnetic properties, such as the creation of band gaps where electromagnetic wave propagation is inhibited. Accurately predicting dispersion relations, which describe the frequency and direction of wave propagation, is vital for designing innovative photonic devi...
Article
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NECP-MCX is a Monte-Carlo particle-transport code developed by the Nuclear Engineering Computational Physics (NECP) Lab. of Xi’an Jiaotong University in 2018. The first version of NECP-MCX is focused on addressing the challenge of deep-penetration radiation-shielding problems. In recent years, new capabilities of unstructured-mesh geometries, dose...
Preprint
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We propose a scaling approach to evaluating the qubit resources required by concatenated fault-tolerant quantum computing. The approach gives closed-form expressions, which remain simple for multiple levels of concatenation, making it an ideal tool to compare and minimize the resource costs of different concatenation schemes. We then use it to stud...
Article
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Tackling the complexity of particle interactions, this investigation introduces a unified computational methodology employing Moldy, Gnuplot, and Visual Molecular Dynamics (VMD). Inspired by the n-body problem's persistent intrigue, specifically the three-body dynamics within molecular systems, we leverage Molecular Dynamics (MD) simulations to for...
Article
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The expression for the potential energy of interaction of two neutral atoms in the absence of a chemical bond consists of the sum of multiple and improper integrals. Due to the cumbersome nature of the functions, finding these integrals in explicit form is not possible. Software systems widely used in practice based on standard methods of computati...
Article
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The contributions in magnetic confinement fusion theory presented at the 29th Fusion Energy Conference (FEC 2023) are summarized here. This summary aims at providing an overview of the advances in the field and new directions in integrated modeling, computational physics, control design and application of artificial intelligence to discharge design...
Research
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Objectifs de la formation : Assurer une excellente formation ayant comme but la maîtrise de différents concepts et disciplines des sciences physiques (fondamentales et appliquées), tout en utilisant des nouvelles technologies digitales et des connaissances pointues et articulées autour de la modélisation, les mathématiques avancées, la programmatio...
Preprint
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The numerical solution of partial differential equations (PDEs) is essential in computational physics. Over the past few decades, various quantum-based methods have been developed to formulate and solve PDEs. Solving PDEs incur high time complexity for real-world problems with high dimensions, and using traditional methods becomes practically ineff...
Article
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The utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simu...
Preprint
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Computational physics simulation can be a powerful tool to accelerate industry deployment of new scientific technologies. However, it must address the challenge of computationally tractable, moderately accurate prediction at large industry scales, and training a model without data at such large scales. A recently proposed component reduced order mo...
Poster
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Recent studies explore living polymer systems formed from mixtures of surfactants and hydrotropes with oppositely charged headgroups, resulting in unique mixed surfactants. ➢ Charge neutralization produces highly hydrophobic surfactants that may behave like nonionic surfactants, which can significantly impact various applications in materials scien...
Article
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The connection formulae provide a systematic way to compute physical quantities, such as the quasinormal modes, Green functions, in blackhole perturbation theories. In this work, we test whether it is possible to consistently take the collision limit, which brings two or more regular singularities into an irregular one, of the connection formulae,...
Preprint
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Surveys of computational science show that many scientists use languages like C and C++ in order to write code for scientific computing, especially in scenarios where performance is a key factor. In this paper, we seek to evaluate the use of Rust in such a scenario, through implementations of a physics simulation in both C++ and Rust. We also creat...
Conference Paper
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Este artigo apresenta uma análise comparativa do desempenho da linguagem de programação Bend em relação ao Python (utilizando multiprocessing) e C (utilizando OpenMP) no contexto de uma Simulação de N-Body, um problema clássico de física computacional. O estudo explora as capacidades da linguagem Bend, que se destaca por abstrair a complexidade do...
Article
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A univariate stochastic system driven by multiplicative Gaussian white noise is considered. The standard method for simulating its Langevin equation of motion involves incrementing the system’s state variable by a biased Gaussian random number at each time step. It is shown that the efficiency of such simulations can be significantly enhanced by in...
Preprint
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Spectral densities encode non-perturbative information crucial in computing physical observables in strongly coupled field theories. Using lattice gauge theory data, we perform a systematic study to demonstrate the potential of recent technological advances in the reconstruction of spectral densities. We develop, maintain and make publicly availabl...
Book
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Dear Colleagues, The Special Issue, "Computational Physics and Artificial Neural Networks", aims to bring together advances in special numerical methods together with new work in AI. A mathematical foundation is the basis on which special numerical methods are built, as well as that on which new types of neuromorphic software are designed (for ins...
Preprint
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In scientific fields such as quantum computing, physics, chemistry, and machine learning, high dimensional data are typically represented using sparse tensors. Tensor contraction is a popular operation on tensors to exploit meaning or alter the input tensors. Tensor contraction is, however, computationally expensive and grows quadratically with the...
Preprint
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A recent article by Ivander, Lindoy and Lee [Nature Communications 15, 8087 (2024)] claims to discover the relationship between the generalized quantum master equation (GQME) and the path integral for a system coupled to a harmonic bath. However, this relationship was already established in 2020 by Makri in the context of the small matrix decomposi...
Article
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We present SIESTA-BdG, an implementation of the simultaneous solution of the Bogoliubov-de Gennes (BdG) and density functional theory (DFT) problem in SIESTA, a first-principles method and code for material simulations which uses pseudopotentials and a localized basis set. This unified approach describes both conventional and unconventional superco...
Article
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Se elaboraron códigos en lenguaje Python con fines educativos para abordar problemas de Física Computacional y Métodos Numéricos en el área de Física, y códigos de Procesos de Separación, Ingeniería de Calor y Termodinámica Química, que permitieron abordar problemas clásicos de la Ingeniería Química. Los códigos se elaboraron por medio de Google Co...
Article
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We look at computational physics from an electrical engineering perspective and suggest that several concepts of mathematics, not so well-established in computational physics literature, present themselves as opportunities in the field. We discuss elliptic complexes and highlight the category theoretical background and its role as a unifying langua...
Article
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Large Language Models (LLMs) can solve some undergraduate-level to graduate-level physics textbook problems and are proficient at coding. Combining these two capabilities could one day enable AI systems to simulate and predict the physical world. We present an evaluation of state-of-the-art (SOTA) LLMs on PhD-level to research-level computational p...
Research Proposal
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Special Issue about "Advances in physics aware machine learning" in Computer Physics Communications Special issue information: Traditional machine learning methods often focus solely on data patterns and correlations without explicitly incorporating the underlying physics. While these approaches can be effective for tasks like image recognition or...
Article
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Paperless movement is a conservation effort. This refers to transitioning from conventional paper-based processes to replacing them with digital alternatives. The paperless movement has been globally implemented in various sectors, ranging from the corporate world to the educational sector. This movement is still little applied as a student's monum...
Article
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In the literature, there are many algorithms for the computation of Feynman diagrams (Hahn, Nucl. Phys. B Proc. Suppl. 89, 231–236 2000; Smirnov and Zeng, Comput. Phys. Commun. 302, 109261 2024; Patel, Comput. Phys. Commun. 197, 276–290 2015). QCD Sum Rules, however, differ from standard loop computations in several key aspects. One of the fundamen...
Article
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One of the most promising applications of machine learning in computational physics is to accelerate the solution of partial differential equations (PDEs). The key objective of machine-learning-based PDE solvers is to output a sufficiently accurate solution faster than standard numerical methods, which are used as a baseline comparison. We first pe...
Article
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The finite element discretization of computational physics problems frequently involves the manual generation of an initial mesh and the application of adaptive mesh refinement (AMR). This approach is employed to selectively enhance the accuracy of resolution in regions that encompass significant features throughout the simulation process. In this...
Poster
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K.-J. Bathe 2002: Finite Element Procedures M. Maeder, R. D'Auria, E. Grasso, G. Petrone b, S. De Rosa, M. Klaerner, L. Kroll, S. Marburg Numerical analysis of sound radiation from rotating discs Journal of Sound and Vibration 468 (2020) 115085 Radu Cimpeanu a, Anton Martinsson b , Matthias Heil A parameter-free perfectly matched layer formulat...
Article
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The Schwinger model is one of the simplest gauge theories. It is known that a topological term of the model leads to the infamous sign problem in the classical Monte Carlo method. In contrast to this, recently, quantum computing in Hamiltonian formalism has gained attention. In this work, we estimate the resources needed for quantum computers to co...
Article
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The study of belt-shaped nanostructures is one of the areas of interest in the current computational physics scenario. Over the years, many topological structures have been synthesized using a diverse array of techniques. Due to their price and more affordable synthesis, carbon structures are of great interest to the technological industry. Since n...