netket/netket
Machine learning algorithms for many-body quantum systems
What it solves
NetKet provides tools for studying many-body quantum systems, a complex field of physics where traditional computational methods often struggle to handle the scale of the problem.
How it works
It uses artificial neural networks and machine learning techniques to simulate and analyze these quantum systems. The library is built on JAX, allowing it to leverage hardware acceleration (like GPUs) for high-performance computing.
Who it’s for
It is designed for researchers and scientists studying quantum physics and many-body systems who want to apply machine learning to their research.
Highlights
- Built on JAX for high-performance computation.
- Supports GPU acceleration on Linux.
- Affiliated with NumFOCUS.
- Provides comprehensive tutorials and example scripts for getting started.