🔬 Category

physics.comp-ph

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.

Proton Quantum Effects in H3_3S Electronic Structure: A Multicomponent DFT study via Nuclear-Electronic Orbital Method

This study utilizes Nuclear-Electronic Orbital DFT to demonstrate that while nuclear quantum effects significantly stiffen S-H bonds and alter phonon properties in high-pressure H3_3S, their direct impact on the electronic structure is minimal, indicating that the observed isotope effect on the critical temperature arises primarily from phonon changes rather than electronic modifications.

Jianhang Xu, Aaron M. Schankler, Yosuke Kanai2026-04-07🔬 physics

Policy heterogeneity improves collective olfactory search in 3-D turbulence

This study demonstrates that heterogeneous swarms combining exploratory and exploitative agents outperform homogeneous groups in locating odor sources within 3-D turbulent environments by effectively mitigating signal spatial correlations, offering new insights for both biological collective behavior and bioinspired engineering algorithms.

Lorenzo Piro, Robin A. Heinonen, Maurizio Carbone, Luca Biferale, Massimo Cencini2026-04-06🔬 physics

Towards best practices in low-dimensional semi-supervised latent Bayesian optimization for the design of antimicrobial peptides

This paper investigates the application of low-dimensional semi-supervised latent Bayesian optimization to antimicrobial peptide design, demonstrating that dimensionally-reduced latent spaces enhance interpretability and that strategically organizing latent spaces using both relevant and easily-computable physicochemical properties can improve optimization efficiency.

Jyler Menard, R. A. Mansbach2026-04-06🔬 physics

Open-source implementation of the anti-Hermitian contracted Schrödinger equation for electronic ground and excited states

This paper introduces a new open-source implementation of the anti-Hermitian contracted Schrödinger equation (ACSE) that offers a scalable, accurate, and robust method for simulating all-electron correlation in both ground and excited states of molecular systems, overcoming the limitations of traditional perturbative approaches by utilizing the exact electronic Hamiltonian.

Daniel Gibney, Anthony W Schlimgen, Jan-Niklas Boyn2026-04-06⚛️ quant-ph

Maximizing the magnetic anisotropy of Dy complexes by fine tuning organic ligands: A systematic multireference high-throughput exploration of over 30k molecules

This study employs automated multireference ab initio calculations to systematically screen over 30,000 dysprosium complexes, revealing that fine-tuning organic ligands in pentagonal bipyramidal structures can significantly enhance magnetic anisotropy by up to 100% compared to reference compounds, thereby demonstrating the power of high-throughput computational screening in overcoming chemically non-intuitive design challenges.

Lion Frangoulis, Lorenzo A. Mariano. Vu Ha Anh Nguyen, Zahra Khatibi, Alessandro Lunghi2026-04-06🔬 cond-mat.mtrl-sci

Low-Scaling Many-Body Green's Function Calculations for Molecular Systems via Interacting-Bath Dynamical Embedding Theory

This paper introduces interacting-bath dynamical embedding theory (ibDET), a scalable molecular extension that accurately computes charged excitation energies at the GW and EOM-CCSD levels with significantly reduced computational cost by constructing frequency-dependent bath representations from atom-centered impurities.

Christian Venturella, Jiachen Li, Tianyu Zhu2026-04-06🔬 physics