:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteur principal:	Wang, Lei
Format:	Preprint
Publié:	2026
Sujets:	Quantum Physics Machine Learning Chemical Physics Computational Physics
Accès en ligne:	https://arxiv.org/abs/2604.25137
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics
par: Holtkamp, Yannick Marcel, et autres
Publié: (2024)

Accurate Computation of Quantum Excited States with Neural Networks
par: Pfau, David, et autres
Publié: (2023)

Parametrized Quantum Circuit Learning for Quantum Chemical Applications
par: Jones, Grier M., et autres
Publié: (2025)

Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
par: Gao, Nicholas, et autres
Publié: (2026)

Symmetry-invariant quantum machine learning force fields
par: Le, Isabel Nha Minh, et autres
Publié: (2023)

On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
par: Gao, Nicholas, et autres
Publié: (2024)

Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
par: Gao, Nicholas, et autres
Publié: (2024)

Integrating Machine Learning and Quantum Circuits for Proton Affinity Predictions
par: Jin, Hongni, et autres
Publié: (2024)

The Convergence Frontier: Integrating Machine Learning and High Performance Quantum Computing for Next-Generation Drug Discovery
par: Ansari, Narjes, et autres
Publié: (2026)

Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics
par: Murdeshwar, Sanya, et autres
Publié: (2026)

Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for Graph Neural Networks Molecular property models
par: Arjona-Medina, Jose, et autres
Publié: (2024)

High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces
par: Shao, Shihao, et autres
Publié: (2024)

Force-Guided Bridge Matching for Full-Atom Time-Coarsened Dynamics of Peptides
par: Yu, Ziyang, et autres
Publié: (2024)

Hybrid Quantum--Classical Machine Learning Potential with Variational Quantum Circuits
par: Willow, Soohaeng Yoo, et autres
Publié: (2025)

Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement
par: Yescas-Ramos, Zuriel Y., et autres
Publié: (2026)

Generative flow-based warm start of the variational quantum eigensolver
par: Zou, Hang, et autres
Publié: (2025)

Using machine learning to map simulated noisy and laser-limited multidimensional spectra to molecular electronic couplings
par: Schultz, Jonathan D., et autres
Publié: (2025)

An Oracle-Free Quantum Algorithm for Nonadiabatic Quantum Molecular Dynamics
par: Courtney, Joshua
Publié: (2026)

FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields
par: Shao, Shihao, et autres
Publié: (2024)

Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation
par: Nys, Jannes, et autres
Publié: (2024)

Variationally Compressing Quantum Circuits to Approximate Nonadiabatic Molecular Quantum Dynamics
par: Courtney, Joshua M., et autres
Publié: (2026)

Geometric Diagnostics of Scrambling-Related Sensitivity in a Bohmian Preparation Space
par: Wiggins, Stephen
Publié: (2026)

Molecular Learning Dynamics
par: Gusev, Yaroslav, et autres
Publié: (2025)

Quantum statistics from classical simulations via generative Gibbs sampling
par: Wang, Weizhou, et autres
Publié: (2026)

Unitary Dynamics for Open Quantum Systems with Density-Matrix Purification
par: Delgado-Granados, Luis H., et autres
Publié: (2024)

Operator Forces For Coarse-Grained Molecular Dynamics
par: Klein, Leon, et autres
Publié: (2025)

Generalized Flow Matching for Transition Dynamics Modeling
par: Wang, Haibo, et autres
Publié: (2024)

Quantum Control of Radical Pair Dynamics beyond Time-Local Optimization
par: Chowdhury, Farhan T., et autres
Publié: (2023)

Benchmarking Data Efficiency in $Δ$-ML and Multifidelity Models for Quantum Chemistry
par: Vinod, Vivin, et autres
Publié: (2024)

BioScore: A Foundational Scoring Function For Diverse Biomolecular Complexes
par: Zhu, Yuchen, et autres
Publié: (2025)

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials
par: Zariquiey, Francesc Sabanés, et autres
Publié: (2025)

Enabling Structure-Only Initialization and Out-of-Distribution Generalization in GNN-based Molecular Dynamics Simulators
par: Shteingolts, S. A., et autres
Publié: (2026)

Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without Data
par: Stupp, Maximilian, et autres
Publié: (2025)

Quantum Simulation of Conical Intersections
par: Wang, Yuchen, et autres
Publié: (2024)

Accurate machine learning force fields via experimental and simulation data fusion
par: Röcken, Sebastien, et autres
Publié: (2023)

chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics
par: Fuchs, Paul, et autres
Publié: (2024)

Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration
par: Fuchs, Paul, et autres
Publié: (2025)

Quantum Simulation of Open Quantum Dynamics via Non-Markovian Quantum State Diffusion
par: Guo, Yukai, et autres
Publié: (2024)

A Novel 4-D Dataset Paradigm for Studying Complete Ligand-Protein Dissociation Dynamics
par: Li, Maodong, et autres
Publié: (2025)

Quantum-Enhanced Sensing of Excited-State Dynamics with Correlated Photons
par: Fan, Jiahao Joel, et autres
Publié: (2025)