arXiv physics.comp-ph Computational Physics

Antonino Emanuele Scurria: Backpropagation as Physical Relaxation: Exact Gradients in Finite Time https://arxiv.org/abs/2602.02281 https://arxiv.org/pdf/2602.02281 https://arxiv.org/html/2602.02281

Alec Dektor, Eugene Dumitrescu, Chao Yang: Sampling two-dimensional isometric tensor network states https://arxiv.org/abs/2602.02245 https://arxiv.org/pdf/2602.02245 https://arxiv.org/html/2602.02245

Andong Hu, Luca Pennati, Stefano Markidis, Ivy Peng: Enabling AI Deep Potentials for Ab Initio-quality Molecular Dynamics Simulations in GROMACS https://arxiv.org/abs/2602.02234 https://arxiv.org/pdf/2602.02234 https://arxiv.org/html/2602.02234

Zishuo Lan, Junjie Li, Lei Wang, Jincheng Wang: FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates https://arxiv.org/abs/2602.01941 https://arxiv.org/pdf/2602.01941 https://arxiv.org/html/2602.01941

Hiroaki Nishikawa: A Flux-Correction Form of the Third-Order Edge-Based Scheme for a General Numerical Flux Function https://arxiv.org/abs/2602.01938 https://arxiv.org/pdf/2602.01938 https://arxiv.org/html/2602.01938

Bettina G. Keller: Internal Trajectories and Observation Effects in Langevin Splitting Schemes https://arxiv.org/abs/2602.01923 https://arxiv.org/pdf/2602.01923 https://arxiv.org/html/2602.01923

Deepak Gautam, Bhooshan Paradkar: Multigrid Poisson Solver for Complex Geometries Using Finite Difference Method https://arxiv.org/abs/2602.01888 https://arxiv.org/pdf/2602.01888 https://arxiv.org/html/2602.01888

Josef Musil: Third-Order Geometric-Volume Conservation in Cahn--Hilliard Models https://arxiv.org/abs/2602.01497 https://arxiv.org/pdf/2602.01497 https://arxiv.org/html/2602.01497

Maximilian L. D. D. Pellner, Georgi Gary Rozenman: Phase Dynamics of Self-Accelerating Bose-Einstein Condensates https://arxiv.org/abs/2602.01406 https://arxiv.org/pdf/2602.01406 https://arxiv.org/html/2602.01406

Stuart Ferguson, Petros Wallden: Methods for non-variational heuristic quantum optimisation https://arxiv.org/abs/2602.01353 https://arxiv.org/pdf/2602.01353 https://arxiv.org/html/2602.01353

Olaf Yunus Laitinen Imanov: Multi-Fidelity Physics-Informed Neural Networks with Bayesian Uncertainty Quantification and Adaptive Residual Learning for Efficient Solution of Parametric Partia... https://arxiv.org/abs/2602.01176 https://arxiv.org/pdf/2602.01176 https://arxiv.org/html/2602.01176

Murtaza Vefadar: From Block Diagrams to Bloch Spheres: Graphical Quantum Circuit Simulation in LabVIEW https://arxiv.org/abs/2602.00643 https://arxiv.org/pdf/2602.00643 https://arxiv.org/html/2602.00643

Md Amran Hossan Mojamder, Zhihang Xu, Min Wang, Ilya Timofeyev: Parametrization of subgrid scales in long-term simulations of the shallow-water equations using machine learning and convex lim... https://arxiv.org/abs/2602.00378 https://arxiv.org/pdf/2602.00378 https://arxiv.org/html/2602.00378

Frederik Zysk, Ana Vila Verde, Naveen K. Kaliannan, Kristof Karhan, Thomas D. K\"uhne: Predicting the hydrogen bond strength from water reorientation dynamics at short timescales https://arxiv.org/abs/2602.00311 https://arxiv.org/pdf/2602.00311 https://arxiv.org/html/2602.00311

Jiaming Li, Hong Liang, Meng Lian, Chuang Zhang, Jiangrong Xu: Semi-implicit Lax-Wendroff kinetic scheme for electron-phonon coupling https://arxiv.org/abs/2602.01220 https://arxiv.org/pdf/2602.01220 https://arxiv.org/html/2602.01220

Haotong Bai, Wenjia Xie, Yixin Yang, Ping Yi, Mingbo Sun: An Oscillation-Free Real Fluid Quasi-Conservative Finite Volume Method for Transcritical and Phase-Change Flows https://arxiv.org/abs/2602.00658 https://arxiv.org/pdf/2602.00658 https://arxiv.org/html/2602.00658

[2026-02-03 Tue (UTC), 2 new articles found for physicscomp-ph Computational Physics]

Kawshik Nath, Bibekananda Nath, Ahmed Zubair: High-Efficiency Hexagonal Nanowire MAPbI3 Perovskite Solar Cell with Broadband Light Trapping https://arxiv.org/abs/2601.23191 https://arxiv.org/pdf/2601.23191 https://arxiv.org/html/2601.23191

Alessandro Pignedoli, Atreya Majumdar, Karin Everschor-Sitte: Leveraging Interactions for Efficient Swarm-Based Brownian Computing https://arxiv.org/abs/2601.22874 https://arxiv.org/pdf/2601.22874 https://arxiv.org/html/2601.22874

Shenyi Zhang, Lei Zhang, Yutian Ke, Jinhai Zhang: Sculpting of Martian brain terrain reveals the drying of ancient Mars https://arxiv.org/abs/2601.22606 https://arxiv.org/pdf/2601.22606 https://arxiv.org/html/2601.22606

Siu A. Chin: Understanding the sign problem from an exact Path Integral Monte Carlo model of interacting harmonic fermions https://arxiv.org/abs/2601.22559 https://arxiv.org/pdf/2601.22559 https://arxiv.org/html/2601.22559

Zhao, Xu, Li, Gao, Zhou, Liu, Chen, Cheng, Meng, Wu, Wang, Chen, Feng: Synthesis of Monolayer Ice on a Hydrophobic Metal Surface https://arxiv.org/abs/2601.22460 https://arxiv.org/pdf/2601.22460 https://arxiv.org/html/2601.22460

Mihai Marciu: Revisiting the energy-momentum squared gravity https://arxiv.org/abs/2601.22333 https://arxiv.org/pdf/2601.22333 https://arxiv.org/html/2601.22333

[2026-02-02 Mon (UTC), no new articles found for physicscomp-ph Computational Physics]

Anand Babu, Rog\'erio Almeida Gouv\^ea, Pierre Vandergheynst, Gian-Marco Rignanese: MEIDNet: Multimodal generative AI framework for inverse materials design https://arxiv.org/abs/2601.22009 https://arxiv.org/pdf/2601.22009 https://arxiv.org/html/2601.22009

M. I. Ayzatsky: Description of electromagnetic fields in inhomogeneous accelerating sections. IV couplers https://arxiv.org/abs/2601.21809 https://arxiv.org/pdf/2601.21809 https://arxiv.org/html/2601.21809

Chiara Ribaldone, Jacques Kontak Desmarais: Model density approach to Ewald summations https://arxiv.org/abs/2601.21776 https://arxiv.org/pdf/2601.21776 https://arxiv.org/html/2601.21776

Krah, Lin, Wilhelm, Bacchini, Nave, Grandgirard, Schneider: A Hybrid semi-Lagrangian Flow Mapping Approach for Vlasov Systems: Combining Iterative and Compositional Flow Maps https://arxiv.org/abs/2601.21668 https://arxiv.org/pdf/2601.21668 https://arxiv.org/html/2601.21668

Mingzhong Lu, Yufeng Song, Qiyuan Shi, Ming Li, Youjin Deng: High-precision Dynamic Monte Carlo Study of Rigidity Percolation https://arxiv.org/abs/2601.21399 https://arxiv.org/pdf/2601.21399 https://arxiv.org/html/2601.21399

Martin Callsen, Tai-Ting Lee, Mei-Yin Chou: Dynamically training machine-learning-based force fields for strongly anharmonic materials https://arxiv.org/abs/2601.21311 https://arxiv.org/pdf/2601.21311 https://arxiv.org/html/2601.21311