1164 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 study demonstrates that reinforcement learning enables inertial particles to efficiently navigate turbulent Rayleigh–Bénard convection by exploiting flow reorganization at high Rayleigh numbers, where fragmented barriers and plume-assisted pathways allow for successful traversal with lower energy consumption compared to constant-heading strategies.
This paper introduces a parametric physics-informed neural network framework that achieves efficient, zero-shot thermal modeling across diverse metal alloys in additive manufacturing without requiring labeled data, retraining, or pre-training, while significantly reducing error and training time compared to non-parametric baselines.
This paper introduces "El Agente Forjador," a multi-agent framework that autonomously generates, validates, and reuses computational tools to significantly improve the accuracy, cost-efficiency, and adaptability of AI-driven scientific discovery in quantum simulation compared to static, hand-curated approaches.
This study utilizes density functional theory to resolve the controversy over the magnetic ground state of rutile RuO by demonstrating that its transition between nonmagnetic and altermagnetic phases is driven by electron correlation and strain-induced volume changes.
This paper presents and analyzes a unified high-order kernel regularization framework that extends to all four Helmholtz boundary integral operators in three dimensions, enabling accurate and efficient solutions to scattering problems through smooth surface integrals without specialized quadrature or singularity handling.
This paper presents a hardware demonstration and resource analysis of Split-Evolution Quantum Phase Estimation (SE-QPE) on a Quantinuum H2 quantum computer, showing that this modified approach for particle-conserving Hamiltonians reduces circuit depth and gate counts by approximately 33% and 25% respectively while maintaining accuracy and enabling error detection.
This paper presents a meshless, spectrally accurate numerical method featuring adaptive reparameterization, gauge dynamics, and specialized quadrature schemes to efficiently and precisely simulate the dynamics of axisymmetric vesicles in viscous media.
This paper presents and validates a sharp-interface Volume-of-Fluid method for simulating phase-change on unstructured polyhedral meshes, demonstrating its ability to eliminate grid-induced anisotropy and accurately model complex flows like turbulent boiling without relying on empirical closure models.
This study investigates the impact of spin-orbit coupling on non-van der Waals 2D materials, identifying SbTlO3 and its Pb-substituted derivative SbPbO3 as robust topological insulators characterized by significant band inversion and confirmed topological edge states.
This study demonstrates that silver toroidal plasmonic nanodimers can significantly enhance the near-infrared emission of heterostructured cadmium-free InP quantum dots by generating intense nanogap hotspots and tunable Purcell factors that effectively convert enhanced decay rates into radiative output.