🧰 NetKetOpen bounties:
- $75 | Add support for a single-file HDF5 log
- $50 | Use colors to signal sampling issues in expectation values
- $100 | Support ladder operators in PauliStrings Operators
- $75 | Implement single-pass statistics estimators for variance and convergence estimators
NetKet uses Machine-Learning ideas to address some hard problems in Quantum Physics, such as finding the ground-state or solving the dynamics of a quantum system, or enhancing a tomographic reconstruction from some experimental data. It is built around neural-network quantum states and provides efficient algorithms for their evaluation and optimization. NetKet is a Python package based on Google's Jax library.
We are welcoming contributors with a Physics or Machine Learning background to work on some algorithmic tasks, those with a quantum computing background to work on our integration with other packages, and those without to work on the structure of the codebase itself.
Open NetKet GitHub issues are here.