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.

Benchmarking thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former model

This study systematically benchmarks various thermostat algorithms in molecular dynamics simulations of a binary Lennard-Jones glass-former, revealing that while Nosé-Hoover chains and Bussi thermostats offer reliable temperature control with time-step dependent energy sampling, the Grønbech-Jensen–Farago Langevin scheme provides the most consistent sampling of both temperature and potential energy despite its higher computational cost and friction-dependent diffusion effects.

Kumpei Shiraishi, Emi Minamitani, Kang Kim2026-04-24🔬 cond-mat

Efficient Implementation of the Spin-Free Renormalized Internally-Contracted Multireference Coupled Cluster Theory

This paper reports an efficient, parallelized, spin-free implementation of the renormalized internally-contracted multireference coupled cluster with singles and doubles (RIC-MRCCSD) method within the ORCA software suite, which achieves computational costs comparable to single-reference CCSD while avoiding high-order reduced density matrices and demonstrating both scalability to large systems and accuracy comparable to various perturbation theories.

Kalman Szenes, Riya Kayal, Kantharuban Sivalingam, Robin Feldmann, Frank Neese, Markus Reiher2026-04-24🔬 physics

Watts-per-Intelligence Part II: Algorithmic Catalysis

This paper establishes a thermodynamic theory of algorithmic catalysis within the watts-per-intelligence framework, proving that task-specific speed-ups are fundamentally limited by the algorithmic mutual information between the substrate and task descriptor, with a minimum thermodynamic cost for information installation that determines the energy-efficient deployment horizon for reusable computational structures.

Elija Perrier2026-04-24🔢 math

Chaos Gated Tunneling Drives Molecular Reactivity in Astrophysical Environments

This paper introduces a chaos-diagnostic framework combining multireference electronic structure theory, Adiabatic Gauge Potentials, and Random Matrix Theory to demonstrate how quantum chaos suppression at transition states enhances proton-transfer tunneling in ultracold astrophysical environments, thereby offering a new metric for refining ion-molecule reaction models in planetary atmospheres.

Saptarshi G. Dastider, K. Prashant, P. Shruti, C. Sudheesh, Jobin Cyriac2026-04-24🔬 physics