1190 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 despite fundamentally different interaction origins—metallic-like isotropic potentials versus entropic forces from hard polyhedra—two distinct particle systems exhibit identical complex crystallization pathways and local structural evolution because their interactions are effectively similar when mapped to an equivalent pairwise potential.
This paper introduces a physically consistent multiphysics Deep Energy Method that couples fourth-order phase-field fracture mechanics with piezoresistive self-sensing to predict crack evolution and its corresponding electrical resistance signatures in conductive composites without artificially assigning the electric field a role in driving fracture.
FermiLink is a unified, open-source AI agent framework that decouples package knowledge from simulation workflows to enable autonomous, high-fidelity scientific simulations across diverse domains, successfully reproducing over half of benchmarked figures and generating research-grade results on complex, undocumented problems.
By combining infrared spectroscopy of hydrated pyrene anions with machine-learning simulations, this study reveals that electron dynamics within the aromatic cloud actively modulate water vibrational signals, offering new insights into water-aromatic interactions across various chemical environments.
This paper challenges the century-old Lindemann-Hinshelwood mechanism by demonstrating that barrierless termolecular reactions, such as ion-atom recombination, are fundamentally governed by direct three-body dynamics rather than sequential bimolecular encounters, a finding that resolves long-standing theory-experiment discrepancies and establishes a new framework for understanding these processes across various scientific fields.
This paper investigates a discrete-time quantum walk where a detector is periodically removed and randomly relocated, revealing that while both unrestricted (Model 1) and restricted (Model 2) relocation schemes mimic a semi-infinite walk for long intervals, they exhibit distinct spreading behaviors and quantum-enhanced occupation probability ratios in the rapid-relocation regime.
This review examines various particle-based numerical strategies for modeling anisotropic magnetic colloids, analyzing how different representations capture key physical mechanisms like dipole-particle misalignment and steric constraints while highlighting emerging machine learning approaches to improve predictive efficiency.
This paper proposes a non-gradient-based optimization framework that integrates Gaussian random functions and genetic algorithms to generate smooth, stress-concentration-free functionally graded lattice structures, overcoming the abrupt transitions typical of conventional genetic algorithm implementations.
This paper introduces SA-DSVN, a dual-stream 3D convolutional network that significantly improves structural defect detection in cosmic-ray muon tomography by fusing scattering kinematics with secondary electromagnetic shower multiplicities, achieving superior performance over conventional methods through a cloud-native simulation framework.
This study demonstrates that grafting flexible side chains onto metal-organic frameworks acts as a structural switch to dismantle the phonon gas model by inducing strong resonant hybridization and steric crowding, which critically dampens phonon lifetimes and drives a transition from crystalline to glass-like thermal transport.