PennyLaneAI/generative-quantum-states

Official code for the paper "Predicting Properties of Quantum Systems with Conditional Generative Models"

40
/ 100
Emerging

Predict properties of quantum systems by training conditional generative models on simulated data. This project takes data from quantum simulations of systems like Heisenberg models or Rydberg atoms and outputs predicted quantum phases or other properties for new systems. It's designed for quantum physicists and researchers who need to efficiently characterize or classify the behavior of quantum systems.

No commits in the last 6 months.

Use this if you need to predict the properties or quantum phases of new quantum systems based on existing simulation data, especially for Heisenberg models or Rydberg atom systems.

Not ideal if you are looking for a general-purpose quantum simulation tool rather than one focused on property prediction using generative models.

quantum-physics quantum-simulation quantum-phase-prediction materials-science condensed-matter
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 17 / 25

How are scores calculated?

Stars

36

Forks

10

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Dec 02, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/PennyLaneAI/generative-quantum-states"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.