1258 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.
The paper introduces **unxt**, a Python package built on the **quax** framework that integrates **astropy.units** with **JAX** to enable seamless, high-performance, unit-aware scientific computing.
This paper presents a comprehensive analysis and the first open-source implementation of phase-shifting dealiasing methods for pseudo-spectral simulations of incompressible Navier-Stokes equations, demonstrating that these techniques can achieve up to a threefold speedup over standard 2/3 truncation with minimal accuracy loss.
This paper provides a rigorous theoretical justification for the noise-cancellation algorithm in interacting Brownian systems by proving that cross-correlations vanish in thermal equilibrium—rendering the method exact—while demonstrating that finite cross-correlations in nonequilibrium systems serve as a distinct fingerprint of non-equilibrium physics requiring specific corrections.
This paper introduces a robust, high-order numerical framework for simulating next-generation solar cells that combines structure-preserving spatial discretization with L-stable implicit Runge-Kutta time integration to accurately model coupled charge, exciton, and ion transport dynamics without empirical parameters.
This paper proposes a two-dimensional multi-phase-field model based on Puck failure theory and a mesh overlay method to accurately predict and simulate various in-plane damage modes in fiber-reinforced composite laminates, demonstrating strong agreement with experimental results across multiple benchmark loading scenarios.
By combining machine learning interatomic potentials with specialized loop updates to overcome high energy barriers and ensure accurate sampling, this study successfully simulates the first-order proton-ordering transition in water ice at 83 K, a result that aligns with experimental values after accounting for nuclear quantum effects.
This study utilizes volume of fluid simulations to investigate droplet impact on random hydrophobic surfaces, revealing that while maximum spreading decreases linearly with increasing roughness and contact time remains constant, the interplay between Weber number and surface roughness governs wetting-bouncing transitions and delays bouncing with larger roughness.
This paper demonstrates that combining highly accurate machine-learned potentials with the quantum thermal bath method provides a computationally efficient and reliable approach for simulating the infrared spectra of protonated water clusters, offering a cost-effective alternative to traditional quantum dynamics techniques.
This study establishes a high-fidelity finite-element model of the Chang'e-7 lander to demonstrate that extreme lunar south-pole thermal cycles, primarily affecting solar array stiffness, cause significant drift in the lander's fundamental resonance frequency (0.64–0.87 Hz), which critically overlaps with the seismic observation window and necessitates specific noise filtering strategies for accurate interior probing.
This paper numerically investigates how external magnetic fields influence the long-range transport of large polarons (solitons) in discrete quasi-one-dimensional systems, demonstrating that the effect depends on both field strength and specific system parameters that define soliton properties, while also examining polarons generated by donor complexes.