When distant worlds pass between their stars and our telescopes, they leave fingerprints of their atmospheres in the starlight—but extracting these cosmic signatures has traditionally been a computational nightmare. Transmission spectroscopy, the art of reading atmospheric compositions from transit data, typically requires a cumbersome two-step process that fragments analysis and introduces systematic errors.
ExoIris shatters this paradigm by modeling the complete 2D spectroscopic transit time series in one unified framework. Instead of wrestling with separate light curve extractions and spectrum fits, researchers can now jointly analyze datasets from multiple instruments and observation epochs simultaneously. The package delivers remarkable speed—processing typical JWST transmission spectra in tens of minutes on standard desktop hardware—while maintaining the statistical rigor needed for publication-quality results.
Built for the James Webb Space Telescope era, ExoIris empowers both seasoned exoplanet researchers and newcomers to atmospheric science. Its streamlined Python interface makes sophisticated transit analysis accessible to graduate students, while its robust statistical foundation satisfies the demands of high-stakes space telescope programs. As JWST continues revolutionizing our understanding of alien atmospheres, tools like ExoIris ensure that computational bottlenecks won’t limit our cosmic discoveries.
⭐ Stars: 7
💻 Language: Python
🔗 Repository: hpparvi/ExoIris