Quantum Systems
ML for quantum computing and quantum physics — error correction, state tomography, variational algorithms, and quantum simulation.
Machine learning intersects with quantum physics in several ways: quantum circuits as ML models, ML for quantum control and error mitigation, ML surrogates for many-body quantum systems, and neural quantum states for representing wavefunctions.
Tools
Quantum Machine Learning
PennyLane
Cross-platform quantum machine learning framework
Qiskit Machine Learning
QML algorithms and primitives in Qiskit
TensorFlow Quantum
Quantum-classical hybrid ML models
Neural Quantum States & Many-Body
NetKet
ML for many-body quantum systems with neural quantum states
FermiNet
Neural network ansatz for fermionic wavefunctions
Resources
Related
- For quantum chemistry (DFT, force fields), see Quantum Chemistry.
- For ML-based interatomic potentials for quantum materials, see Neural Network Potentials.