JAXVacua – String Vacua with JAX

JAXVacua is a Python library for constructing Type IIB flux-vacuum models and numerically finding vacua with JAX-based automatic differentiation. It is intended both as a high-level workflow for sampling flux vacua and as a modular toolkit for period computations, effective field theory evaluation, flux sampling, and post-processing.

The documentation is organised by how users usually approach the package: first the physics and geometry background, then executable tutorials, then the API reference for individual modules.

How to navigate

New to the physics

Start with the introduction chapters. They explain the Type IIB compactification setup, Calabi-Yau input data, periods, moduli stabilisation, and perturbatively flat vacua.

Introduction

New to the code

Use the tutorial catalogue. It separates quickstart, basic usage, vacuum finding, geometry limits, and analysis workflows into a guided sequence of notebooks.

Tutorials

Looking for a module

Go to the API reference when you already know which object or function you need. The module pages include workflow figures and curated member indexes.

JAXVacua

Looking for examples from papers

The application notes connect package workflows to concrete research use cases, including non-SUSY vacua, \(W_0\) distributions, and deep-observation pipelines.

Non-supersymmetric flux vacua

Recommended first path

For a first pass through the documentation, read:

1. Introduction for the conceptual map.

2. Tutorials for executable notebooks.

3. API documentation once you need precise class and function signatures.

The quickstart notebook is the shortest route to a working example. The JAXVacua overview notebook gives a broader end-to-end walkthrough.

Citing JAXVacua

If you find this work useful, please cite:

@article{Dubey:2023dvu,
    author = "Dubey, Abhishek and Krippendorf, Sven and Schachner, Andreas",
    title = "{JAXVacua \textemdash{} a framework for sampling string vacua}",
    eprint = "2306.06160",
    archivePrefix = "arXiv",
    primaryClass = "hep-th",
    doi = "10.1007/JHEP12(2023)146",
    journal = "JHEP",
    volume = "12",
    pages = "146",
    year = "2023"
}

Reference lookup

• Index

• Module Index