physics.chem-ph papers | Gist.Science

This collection explores the fascinating intersection where the laws of physics meet the complex machinery of chemistry. Here, researchers investigate how quantum mechanics governs molecular bonds, how light interacts with matter at the atomic scale, and how fundamental forces shape chemical reactions. It is a realm where abstract mathematical models collide with tangible substances to reveal the hidden mechanisms driving our material world.

On Gist.Science, we process every new preprint in this category directly from arXiv to make these discoveries accessible to everyone. Whether you are a seasoned expert or a curious reader, you will find both plain-language explanations and detailed technical summaries for each paper. Below are the latest contributions from the community pushing the boundaries of physical chemistry.

Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement

This paper introduces Compositional Probe Decomposition (CPD) to demonstrate that linear disentanglement of geometric and compositional information in atomistic foundation models is primarily driven by task alignment rather than architecture, revealing a significant performance gradient where models trained on specific properties like HOMO-LUMO gaps outperform energy-trained models and exhibit symmetry-dependent information routing.

Joshua Steier2026-03-10🤖 cs.LG

Machine learning the two-electron reduced density matrix in molecules and condensed phases

This paper demonstrates that machine learning models trained to predict the two-electron reduced density matrix (2-RDM) can accurately surrogate correlated wavefunction methods, enabling coupled-cluster-quality electronic structure calculations for large solvated systems at a fraction of the conventional computational cost.

Jessica A. Martinez B., Bhaskar Rana, Xuecheng Shao, Katarzyna Pernal, Michele Pavanello2026-03-10🔬 physics

Scaling Machine Learning Interatomic Potentials with Mixtures of Experts

This paper introduces Mixture-of-Experts (MoE) and Mixture-of-Linear-Experts (MoLE) architectures for Machine Learning Interatomic Potentials, demonstrating that element-wise routing with shared nonlinear experts achieves state-of-the-art accuracy across multiple benchmarks while revealing chemically interpretable specialization aligned with periodic-table trends.

Yuzhi Liu, Duo Zhang, Anyang Peng, Weinan E, Linfeng Zhang, Han Wang2026-03-10🤖 cs.LG

Classically Driven Hybrid Quantum Algorithms with Sequential Givens Rotations for Reduced Measurement Cost

This paper introduces a classically driven hybrid quantum algorithm that reduces measurement overhead in electronic-structure simulations by iteratively transforming the Hamiltonian toward a diagonal form using sequential Givens rotations determined via classical low-dimensional block analysis, thereby minimizing quantum circuit depth and measurement requirements.

Benjamin Mokhtar, Noboru Inoue, Takashi Tsuchimochi2026-03-10⚛️ quant-ph

Triplet-Pair Character of the $2^1A_g$ Dark State of Polyenes

Using DMRG calculations on the Pariser-Parr-Pople model for polyene chains, this study quantifies the triplet-pair population of the $2^1A_g$ dark state, predicting a finite-size scaling value of approximately 75% that confirms its predominantly triplet-pair character and supports its role in singlet fission mechanisms.

Alexandru G. Ichert, William Barford2026-03-10🔬 physics

Bound Trions in Two-Dimensional Monolayers: A Review

This review surveys theoretical and experimental advances in the physics of trions within two-dimensional monolayers, highlighting their enhanced binding energies due to reduced screening and confinement, the impact of environmental and external field factors, and their connections to broader many-body phenomena.

Roman Ya. Kezerashvili2026-03-10⚛️ quant-ph

Hitherto unrecognized intermolecular Coulombic decay mechanism in gases

This paper reveals that interatomic and intermolecular Coulombic decay (ICD), previously thought to be limited to weakly bound systems, can also occur efficiently in atomic and molecular gases despite large inter-unit distances, operating through a distinct mechanism that significantly expands the phenomenon's scope and potential applications.

Alan G. Falkowski, Alexander I. Kuleff, Lorenz S. Cederbaum2026-03-10🔬 physics

Improved SABRE hyperpolarisation using pulse sequences to reduce effective coupling

This paper demonstrates that employing NMR pulse sequences to intentionally slow down polarization transfer, rather than accelerating it, can significantly improve SABRE hyperpolarization yields in systems characterized by high magnetic inequivalence and low chemical exchange rates.

Vitaly P. Kozinenko, Bogdan A. Rodin, James Eills, Ilai Schwartz, Stephan Knecht, Laurynas Dagys2026-03-10🔬 physics

Symmetry-based perturbation theory for electronic structure calculations

This paper introduces a symmetry-based multi-reference perturbation theory (SBPT) that leverages enhanced symmetries in a reference Hamiltonian to significantly reduce computational costs in both classical configuration interaction and quantum computing applications, while offering scalable solutions and improved robustness for various molecular systems.

Hiromichi Nishimura, Nam Nguyen, Tanvi Gujarati, Mario Motta2026-03-10⚛️ quant-ph

NATPS: Nonadiabatic Transition Path Sampling Using Time-Reversible MASH Dynamics

This paper introduces NATPS, a novel method that combines the time-reversible Mapping Approach to Surface Hopping (MASH) dynamics with transition path sampling to efficiently simulate rare nonadiabatic events and provide mechanistic insights into photochemical processes while significantly reducing computational costs compared to brute-force approaches.

Xiran Yang, Madlen Maria Reiner, Brigitta Bachmair, Leticia González, Johannes C. B. Dietschreit, Christoph Dellago2026-03-10🔬 physics

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