903 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 introduces a highly efficient and accurate machine learning surrogate model based on a trimmed SchNet architecture to predict many-body dispersion interactions in polymer melts, enabling their practical incorporation into large-scale molecular simulations while capturing key physical features and generalizing across diverse polymer systems.
This memorial review article honors Wolfgang Helfrich by exploring how continuum elastic theories and liquid crystal principles govern the diverse morphologies of biomembranes, revealing that shapes like spheres, cylinders, and tori form a geometric group independent of specific membrane equations.
This paper introduces a sparse convex-relaxation framework using a Müntz–Szász/Jacobi dictionary to estimate effective local scaling exponents from short, boundary-anchored velocity profiles, demonstrating its utility as a finite-scale geometric diagnostic that reveals directional anisotropy and vorticity-aligned roughness structures in turbulent flows without requiring external calibration.
This paper introduces "The Closure Challenge," a standardized open-source benchmark comprising curated datasets, evaluation code, and specific test cases designed to establish a common metric for evaluating and advancing machine learning models in Reynolds-averaged Navier-Stokes turbulence modeling.
This paper introduces a numerical tensor-network method based on the process tensor to compute full counting statistics of charge transport in interacting one-dimensional quantum systems, successfully benchmarking the approach on the XXZ spin chain to recover known transport exponents and confirm the breakdown of Kardar-Parisi-Zhang universality in higher-order cumulants at the isotropic point.
This paper revisits Majorana's method of converting the second-order Thomas-Fermi equation into a first-order one, applying it to both neutral and weakly ionized atoms to efficiently recalculate and validate key atomic physics quantities against previous numerical results.
This paper demonstrates the flexibility and modularity of the deal.II library's multigrid infrastructure by solving stationary Stokes, transient Stokes, and incompressible Navier-Stokes equations using various adaptive strategies, including hp-adaptivity, space-time finite elements, and monolithic solvers.
This paper demonstrates that using INT8-based emulation via the SCILIB-Accel tool can accelerate FP64 electronic structure calculations on modern GPUs without code modifications, achieving simultaneous improvements in performance and accuracy through tunable precision strategies.
This paper proposes a hard-constrained neural Riemann solver (HCNRS) that enforces five physical constraints—positivity, consistency, mirror symmetry, Galilean invariance, and scaling invariance—to accurately approximate exact Riemann solvers for fluid dynamics while overcoming the conservation errors and symmetry breaking issues found in unconstrained neural approaches.
This paper presents an open-source, third-party-free GPU-accelerated Path Integral Molecular Dynamics (PIMD) code that enables efficient, first-principles simulations of large-scale identical particle systems, successfully modeling up to 40,000 bosons and offering a promising solution to the Fermion sign problem for tens of thousands of fermions.