917 papers
Computational physics bridges the gap between abstract theory and real-world observation by using powerful computers to solve complex physical problems. This field allows scientists to simulate everything from the collision of subatomic particles to the swirling dynamics of galaxies, offering insights that traditional experiments alone cannot provide.
On Gist.Science, we continuously process every new preprint in this category from arXiv to make these breakthroughs accessible to everyone. Each entry is accompanied by both a clear, plain-language explanation and a detailed technical summary, ensuring that researchers and curious readers alike can grasp the significance of the latest findings without getting lost in dense equations.
Below are the latest papers in computational physics, curated to keep you at the forefront of this rapidly evolving discipline.
This paper presents a topology optimization framework based on time-dependent Ginzburg-Landau theory under the Weyl gauge to inversely design the structural geometries of type-II superconductors with superconductor-dielectric/vacuum interfaces, aiming to enhance flux pinning and current density through optimal defect placement.
This paper presents an open-source implementation and reproducible benchmarks using libROM, Laghos, and MFEM to evaluate the trade-offs between accuracy and computational efficiency of various hyper-reduction methods, such as gappy POD interpolation and the empirical quadrature procedure, across nonlinear diffusion, elasticity, and Lagrangian hydrodynamics problems, ultimately demonstrating that optimal method selection depends on the specific physics and time integration scheme employed.
This paper presents a robust machine learning framework that combines parameter estimation, cosine transform inversion, and constrained neural networks to accurately reconstruct spectral density functions in open quantum systems from noisy time-domain measurements.
This workshop report outlines a comprehensive strategy for advancing sustainability and ethics in ErUM-Data research by integrating technical measures like CO2 reduction and AI governance with cultural shifts in education, funding, and community engagement to embed responsible practices into everyday scientific workflows.
This paper presents a new molecular dynamics simulation using the Fast Multipole Method to efficiently model laser cooling in large 3D Penning trap ion crystals, demonstrating that thousands of ions can be cooled to ultracold temperatures with linear computational scaling, thereby validating their potential for future quantum science experiments.
This paper proposes a novel approach to defining metastable states by optimizing the shape of local domains to maximize a timescale separation metric, utilizing derived analytic expressions for Dirichlet eigenvalue variations and high-dimensional tractability methods to significantly improve upon conventional definitions in molecular simulations.
This paper introduces a fast and flexible probabilistic forecasting framework for dynamical systems that combines flow matching to generate physically consistent initial perturbations with deterministic ODE-based propagation, achieving state-of-the-art accuracy and efficiency compared to diffusion-based baselines.
This paper proposes two explicit, meshless computational electromagnetics methods based on local radial basis function interpolation that, when augmented with hyperviscosity terms, achieve convergence and offer improved numerical dispersion and reduced anisotropy compared to the traditional finite difference time domain method.
This paper presents a data-driven reduced order model that bypasses iterative wavefunction optimization in Kohn-Sham Density Functional Theory by constructing a low-dimensional basis from representative atomic configurations, enabling efficient and accurate Born-Oppenheimer molecular dynamics simulations as demonstrated on a water molecule.
This study demonstrates that monochromatic irradiation of zigzag monolayer WSe nanoribbons, modeled via a tight-binding Floquet framework and density functional theory, significantly enhances the thermoelectric figure of merit ($ZT > 1$) by reshaping electronic band structures and reducing lattice thermal conductivity through anharmonic scattering.