(Include but not limited to)
Track 1: Condensed Matter Physics and Quantum States
Strongly correlated electron systems and unconventional superconducting mechanisms
High-temperature superconducting materials and superconducting physics
Topological insulators, topological semimetals, and topological superconductors
Quantum Hall effect and topological quantum computing
Low-dimensional materials and two-dimensional van der Waals heterojunction physics
Moore superlattices and twisted electronics
Quantum phase transitions and quantum critical phenomena
Quantum spin liquids and frustrated magnetism
Multiferroic materials and magnetoelectric coupling effects
Magnetic materials and spintronics
Semiconductor physics and nanoscale physics
Non-equilibrium dynamics and statistical physics
Quantum many-body systems and quantum simulation
Soft condensed matter physics and active substances
Heat transport and energy conversion physics
Track 2: Artificial Intelligence and Machine Learning
Machine learning-assisted material discovery and design
Neural network many-body wave functions and variational Monte Carlo
Deep learning quantum Monte Carlo methods
Deep learning density functional theory
AI-driven identification and characterization of topological superconductors
Machine learning for phase transition detection in strongly correlated systems
Quantum artificial intelligence and quantum machine learning
Application of neural networks in the identification of material states in Moore systems
Application of generative models and unsupervised learning in condensed matter physics
Design of neural network architectures with physical priors
Tensor learning and compressed representation of quantum interactions
AI-assisted experimental data analysis and characterization
Track 3: Computational Simulation and Multi-scale Methods
High-precision electronic structure calculation methods
Quantum Monte Carlo and tensor network methods
Machine learning potential functions and cross-scale simulation
Molecular dynamics and dynamical mean-field theory
Multi-scale modeling and cross-scale methods
High-throughput computing and materials genomics methods
High-performance computing and large-scale numerical simulation
Non-equilibrium and time-dependent simulation methods
Finite element and multi-physics field coupling simulation
Computational and simulation of topological states
Numerical methods for strongly correlated electron systems
Intelligent workflow and automation of computational materials and calculation physics and experimental data integration
Construction of material databases and data-driven discovery
......