Machine-learning emulator for reionization-era kSZ science
A fast emulator for the kinetic Sunyaev-Zel'dovich power spectrum
reionemu helps turn simulation outputs into trainable datasets, emulator models,
and reusable workflows for exploring reionization parameter space without rerunning expensive simulations.
What the package covers¶
Simulation to dataset
Condense raw outputs, compute flat-sky power spectra, and assemble training-ready HDF5 datasets.
Training workflows
Build dataloaders, train deterministic or MC-dropout emulators, and evaluate validation performance with reusable utilities.
Search and tuning
Run Ray Tune experiments to explore architecture and optimizer choices for the deterministic four-parameter emulator.
Experiment artifacts
Save JSON manifests, configs, results, normalizers, and model checkpoints for reproducible emulator runs.
Start here¶
- Getting Started outlines what to include for installation, verification, and contributor setup.
- API Overview gives you a structure for documenting the public surface area.
Repository layout¶
- Core package:
src/reionemu/ - Scripts and HPC workflows:
scripts/ - Research notebooks:
notebooks/ - Documentation source:
docs/