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thesis-desi-cmb-fli

Repository for a thesis project targeting field-level inference (FLI) on DESI galaxy samples cross-correlated with CMB lensing reconstructions from Planck and ACT.

Thesis vision

  • Construction of a reproducible FLI workflow that ingests DESI galaxy clustering data and CMB lensing maps (Planck PR4, ACT DR6).
  • Delivery of joint cosmological constraints from the cross-correlation of those observables.

Code Attribution

This repository builds upon the benchmark-field-level framework by Hugo Simon.

The cmb_lensing.py module is built upon the implementation by François Lanusse (see repository).

Quick Start

Local development (CPU only):

conda env create -f env/environment.yml
conda activate desi-cmb-fli
pip install -e .
pre-commit install

NERSC Perlmutter (with GPU): See docs/hpc.md for complete setup.

Development

Run tests: pytest Format code: ruff format . Preview docs: mkdocs serve

Git hooks automatically format code on commit. CI runs tests on push.

Pipeline Status

✅ Completed: Initial conditions, gravitational evolution, galaxy bias modeling, CMB lensing modeling, and field-level inference on synthetic galaxy + CMB lensing data

🚧 Next Steps: - Field-level inference on real data (DESI LRG × Planck/ACT κ-maps)

See pipeline.md for detailed implementation roadmap and notebooks/ for interactive demonstrations.

Citation

The project for the FLI × DESI × CMB lensing analysis should be cited using CITATION.cff.

License

MIT (see LICENSE).