I'm excited to share Resonant Worlds Explorer an open-source AI platform built to analyze NASA mission data for exoplanet transit detection and atmospheric biosignature discovery.
Traditional machine learning approaches often suffer from numerical floating-point drift when processing continuous stellar light curves and complex chemical equilibrium calculations. Resonant Worlds Explorer pairs deep learning with exact-math pipelines to maintain maximum precision when scoring candidate exoplanets.
Resonant Worlds Explorer processes light curves and spectra from NASA missions (JWST, TESS, Kepler) to detect exoplanets and analyze atmospheric biosignatures. Built with Modulus—our custom AI solver extending Qwen with a Prime Algebra Transformer—the system converts astrophysics and chemical equilibrium equations into exact arithmetic. This eliminates floating-point errors, dramatically reducing false positives in the search for life. Includes live web plots and PDF reports.
