DESI-RCA is a Python command-line and guided-menu tool for post-pipeline residual-covariance advisory analysis and traceable reporting for DESI spectral products. It prepares controlled spectral matrices from DESI coadd products, constructs residual diagnostic products, computes spectrum-by-spectrum residual-correlation diagnostics, evaluates null controls, and produces conservative advisory decisions focused on stacking caution and residual-covariance risk.

The tool builds on the residual-covariance diagnostic methodology demonstrated in the peer-reviewed Astronomy and Computing article by F. Javier Martinez Sanchez, "Forensic Characterization of Correlated Residuals in Large Spectroscopic Pipelines: A Case Study of SDSS/BOSS Data" (Astronomy and Computing, 57, 101155, 2026; DOI: https://doi.org/10.1016/j.ascom.2026.101155), and adapts that RCA-style approach to DESI spectral products.

DESI-RCA preserves DESI metadata when available, including fiber, petal, spectrograph, tile, night, arm, survey, observing programme, and target-class information. This enables metadata-aware and fiber-aware residual-covariance inspection while avoiding causal claims about instrumental origin.
DESI-RCA is part of the broader FRANJAMAR-RCA ecosystem of Residual Covariant Advisor tools, which also includes JWST-RCA, EUCLID-RCA, and RUBIN-RCA. The common RCA philosophy is to provide post-pipeline residual-covariance diagnostics, null controls, stacking-caution advisories, traceable reports, and reproducible verification packages, while adapting ingestion and metadata handling to each survey or instrument.

Outputs include PDF reports, visual diagnostic summaries, machine-readable manifests, SHA-256 fingerprints, report packages, and package-verification results. DESI-RCA does not replace the DESI pipeline, certify DESI data products, validate cosmological conclusions, or claim pipeline failure. Its purpose is to make residual-covariance structure visible, reproducible, and auditable for selected DESI spectral subsets.