:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dong, Xinyang, Xie, Hao, Chen, Yixiao, Liang, Wenshuo, Zhang, Linfeng, Wang, Lei, Wang, Han
Format:	Preprint
Published:	2025
Subjects:	Computational Physics
Online Access:	https://arxiv.org/abs/2501.09590
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Variational Free Energy Calculation of Hydrogen Hugoniot
by: Li, Zihang, et al.
Published: (2025)

Nonlocal free-energy density functional for warm dense matter
by: Ma, Cheng, et al.
Published: (2024)

Interpretable descriptors enable prediction of hydrogen-based superconductors at moderate pressures
by: Chen, Jiawei, et al.
Published: (2025)

Equivariant neural network for Green's functions of molecules and materials
by: Dong, Xinyang, et al.
Published: (2023)

First principles simulations of dense hydrogen
by: Bonitz, Michael, et al.
Published: (2024)

Bounding free energy difference with flow matching
by: Zhao, Lu, et al.
Published: (2023)

Deep Potentials for Materials Science
by: Wen, Tongqi, et al.
Published: (2022)

Symmetry adaptation for self-consistent many-body calculations
by: Dong, Xinyang, et al.
Published: (2024)

η-ensemble path integral Monte Carlo approach to the free energy of the warm dense electron gas and the uniform electron liquid
by: Dornheim, Tobias, et al.
Published: (2024)

Direct free energy calculation from ab initio path integral Monte Carlo simulations of warm dense matter
by: Dornheim, Tobias, et al.
Published: (2024)

Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo Study
by: Chai, Shengdu, et al.
Published: (2025)

Ground state phases of the two-dimension electron gas with a unified variational approach
by: Smith, Conor, et al.
Published: (2024)

GW space-time method: Energy band-gap of solid hydrogen
by: Azadi, Sam, et al.
Published: (2020)

Ab initio density functional theory approach to warm dense hydrogen: from density response to electronic correlations
by: Moldabekov, Zhandos A., et al.
Published: (2025)

Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models
by: Li, Shuo-Hui, et al.
Published: (2026)

A variational method for the simulation of hydrogen diffusion in metals
by: Andrés, Eva M., et al.
Published: (2024)

Multi-Task Fine-Tuning Enables Robust Out-of-Distribution Generalization in Atomistic Models
by: Zhang, Chengqian, et al.
Published: (2026)

A COMSOL framework for predicting hydrogen embrittlement -- Part I: coupled hydrogen transport
by: Díaz, A., et al.
Published: (2025)

Scaling Machine Learning Interatomic Potentials with Mixtures of Experts
by: Liu, Yuzhi, et al.
Published: (2026)

Deep learning quantum Monte Carlo for solids
by: Qian, Yubing, et al.
Published: (2024)

RiD-kit: Software package designed to do enhanced sampling using reinforced dynamics
by: Fan, Jiahao, et al.
Published: (2024)

Deep neural networks for the prediction of the optical properties and the free-form inverse design of metamaterials
by: Gahlmann, Timo, et al.
Published: (2022)

Deep learning generative model for crystal structure prediction
by: Luo, Xiaoshan, et al.
Published: (2024)

Thermal disorder and phonon softening in the ferroelectric phase transition of lead titanate
by: Xie, Pinchen, et al.
Published: (2024)

Crystal structure prediction with nuclear quantum and finite-temperature effects via deep free energy learning
by: Wang, Xiaoyang, et al.
Published: (2026)

Accelerated Inchworm Method with Tensor-Train Bath Influence Functional
by: Wang, Geshuo, et al.
Published: (2025)

Computational predictions of hydrogen-assisted fatigue crack growth
by: Cui, C., et al.
Published: (2024)

Ab initio evaluation of the electron-ion energy transfer rate in a non-equilibrium warm dense metal
by: Zhang, Jia, et al.
Published: (2024)

DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution
by: Li, Tiancheng, et al.
Published: (2026)

Superatomic hydrogen: achieving effective aggregation of hydrogen atoms at pressures lower than that of metallic hydrogen
by: Fan, Jia, et al.
Published: (2025)

Deep Learning Sheds Light on Integer and Fractional Topological Insulators
by: Li, Xiang, et al.
Published: (2025)

Computational uncertainties in lattice thermal conductivity prediction of crystalline solids
by: Srivastava, Yagyank, et al.
Published: (2025)

Finding dense sub-lattices as low-energy states of a Hamiltonian
by: Barberà-Rodríguez, Júlia, et al.
Published: (2023)

Development and large-scale benchmarks of a protein--ligand absolute binding free energy toolkit
by: Liu, Yu, et al.
Published: (2026)

Computational predictions of weld structural integrity in hydrogen transport pipelines
by: Mandal, T. K., et al.
Published: (2024)

The OpenLAM Challenges
by: Peng, Anyang, et al.
Published: (2025)

Modelling lined rock caverns subject to hydrogen embrittlement and cyclic pressurisation in fractured rock masses
by: Zhao, Chenxi, et al.
Published: (2025)

Accurate and thermodynamically consistent hydrogen equation of state for planetary modeling with flow matching
by: Xie, Hao, et al.
Published: (2025)

Modelling hydrogen integration in energy system models: Best practices for policy insights
by: Bah, Muhammad Maladoh, et al.
Published: (2025)

Advancing Universal Deep Learning for Electronic-Structure Hamiltonian Prediction of Materials
by: Yin, Shi, et al.
Published: (2025)