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 paper introduces a pedagogical computational framework that reconstructs band formation in periodic media by simulating time-domain wave propagation in finite systems, thereby bridging the gap between abstract Bloch theory and intuitive physical concepts like scattering and interference.
This paper introduces HYMOR, an open-source MATLAB and Julia framework that enables global modal, non-modal, and receptivity analyses of high-enthalpy hypersonic flows by employing shock-fitting techniques and real-gas thermochemical models to capture complex physical interactions inaccessible to traditional local methods.
This paper utilizes molecular dynamics simulations of a harmonic lattice to reveal the complex thermalization process, highlighting distinct relaxation rates for velocity components, power-law frequency proliferation, concurrent defect generation, and two-stage out-of-plane fluctuation behaviors driven by broken symmetry.
This paper uses a case study of a physics manuscript co-authored with AI to argue that while Large Language Models can handle structural and syntactic tasks, human authors must remain the ultimate "Principal Investigators" responsible for logical rigor and integrity, necessitating the mandatory publication of full AI interaction transcripts to ensure accountability.
This paper introduces a multi-stage, LLM-assisted workflow that uses rigorous LaTeX specifications as intermediate blueprints to successfully generate a scalable Density-Matrix Renormalization Group (DMRG) engine in under 24 hours, achieving a 100% success rate across 16 foundation models and accurately reproducing complex quantum many-body phenomena.
This paper presents a high-fidelity, interface-resolved meso-scale simulation framework that integrates 5th-order WENO schemes, atomistic-scale grid resolution, and experimentally derived crystal geometries to accurately model shock initiation in plastic-bonded explosives and assess the impact of numerical and material modeling choices on matching experimental data.
This study demonstrates that optimizing nodal surfaces in fixed-node diffusion Monte Carlo using an antisymmetrized geminal power ansatz significantly improves agreement with CCSD(T) for hydrogen-bonded non-covalent interactions while having negligible effects on dispersion-dominated systems, thereby offering a practical solution to resolve discrepancies in the former and clarifying the nature of errors in the latter.
This paper extends neural-network quantum states to solve strongly interacting few-body problems in continuous space, successfully computing Efimov states and reproducing their key physical features for systems ranging from three to six identical bosons and mass-imbalanced fermions.
This paper presents a physics-informed Bayesian optimization framework that embeds multiple scattering LEED forward models to autonomously and efficiently solve the complex inverse problem of quantitative LEED-I(V) analysis for determining surface atomic structures.
This paper introduces HQ-LP-FNO, a hybrid quantum-classical Fourier Neural Operator that utilizes a compact variational quantum circuit mixer to reduce trainable parameters by 15.6% and improve prediction accuracy for three-dimensional laser processing surrogate modeling compared to classical baselines.