:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Zihang, Xie, Hao, Dong, Xinyang, Wang, Lei
Format:	Preprint
Published:	2025
Subjects:	Strongly Correlated Electrons Machine Learning Computational Physics
Online Access:	https://arxiv.org/abs/2507.18540
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Neural Autoregressive Control Variates for the Quantum Monte Carlo Sign Problem
by: Qiao, Bei, et al.
Published: (2026)

Principal deuterium Hugoniot via Quantum Monte Carlo and $Δ$-learning
by: Tenti, Giacomo, et al.
Published: (2023)

Generalized Lanczos method for systematic optimization of neural-network quantum states
by: Wang, Jia-Qi, et al.
Published: (2025)

Machine Learning Force-Field Approach for Itinerant Electron Magnets
by: Zhang, Sheng, et al.
Published: (2025)

Transformer Learning of Chaotic Collective Dynamics in Many-Body Systems
by: Jang, Ho, et al.
Published: (2026)

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems
by: Chern, Gia-Wei, et al.
Published: (2026)

Machine learning nonequilibrium phase transitions in charge-density wave insulators
by: Fan, Yunhao, et al.
Published: (2026)

Graph neural network force fields for adiabatic dynamics of lattice Hamiltonians
by: Fan, Yunhao, et al.
Published: (2026)

Equivariant Neural Networks for Force-Field Models of Lattice Systems
by: Fan, Yunhao, et al.
Published: (2026)

Machine-learning force-field models for dynamical simulations of metallic magnets
by: Chern, Gia-Wei, et al.
Published: (2026)

Efficient Berry Phase Calculation via Adaptive Variational Quantum Computing Approach
by: Mootz, Martin, et al.
Published: (2025)

Fermionic neural Gibbs states
by: Nys, Jannes, 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)

ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation
by: Chen, Zhuo, et al.
Published: (2023)

Analytic Continuation by Feature Learning
by: Zhao, Zhe, et al.
Published: (2024)

Machine learning with tree tensor networks, CP rank constraints, and tensor dropout
by: Chen, Hao, et al.
Published: (2023)

High pressure hydrogen by machine learning and quantum Monte Carlo
by: Tirelli, Andrea, et al.
Published: (2021)

Persistent Ballistic Entanglement Spreading with Optimal Control in Quantum Spin Chains
by: Lu, Ying, et al.
Published: (2023)

Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo
by: Merali, Ejaaz, et al.
Published: (2026)

Variation of Bose surface by Filling in Cooper pair Bose metal
by: Su, Jiahao, et al.
Published: (2025)

Calculation of screened Coulomb interaction parameters for the charge-disproportionated insulator CaFeO$_3$
by: Merkel, Maximilian E., et al.
Published: (2023)

Advancing Natural Orbital Functional Calculations Through Deep Learning-Inspired Techniques for Large-Scale Strongly Correlated Electron Systems
by: Lew-Yee, Juan Felipe Huan, et al.
Published: (2024)

FFT-Accelerated Auxiliary Variable MCMC for Fermionic Lattice Models: A Determinant-Free Approach with $O(N\log N)$ Complexity
by: Kong, Deqian, et al.
Published: (2025)

Tensor Computing Interface: An Application-Oriented, Lightweight Interface for Portable High-Performance Tensor Network Applications
by: Sun, Rong-Yang, et al.
Published: (2025)

Adiabatic Encoding of Pre-trained MPS Classifiers into Quantum Circuits
by: Murota, Keisuke
Published: (2025)

Predicting fermionic densities using a Projected Quantum Kernel method
by: Perciavalle, Francesco, et al.
Published: (2025)

Learning Minimal Representations of Fermionic Ground States
by: Frohnert, Felix, et al.
Published: (2025)

Solving The Quantum Many-Body Hamiltonian Learning Problem with Neural Differential Equations
by: Heightman, Timothy, et al.
Published: (2024)

When can classical neural networks represent quantum states?
by: Yang, Tai-Hsuan, et al.
Published: (2024)

Neural Quantum States in Mixed Precision
by: Solinas, Massimo, et al.
Published: (2026)

Derandomized shallow shadows: Efficient Pauli learning with bounded-depth circuits
by: Van Kirk, Katherine, et al.
Published: (2024)

Tensor networks and efficient descriptions of classical data
by: Lu, Sirui, et al.
Published: (2021)

Learning topological states from randomized measurements using variational tensor network tomography
by: Teng, Yanting, et al.
Published: (2024)

Scalable quantum dynamics compilation via quantum machine learning
by: Zhang, Yuxuan, et al.
Published: (2024)

Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation
by: Nys, Jannes, et al.
Published: (2024)

A Unified Variational Framework for Quantum Excited States
by: Zhang, Shi-Xin, et al.
Published: (2025)

Deep Learning Based Superconductivity: Prediction and Experimental Tests
by: Kaplan, Daniel, et al.
Published: (2024)

Automatic Order Detection and Restoration Through Systematically Improvable Variational Wave Functions
by: Levy, Ryan, et al.
Published: (2023)

Multi-orbital dynamical mean-field theory with a complex-time solver
by: Yu, Yang, et al.
Published: (2025)