Optimization Pathways for Exoplanet Atmospheric Spectroscopy Detection

Abstract

Earth is currently facing severe environmental degradation, including pollution, climate anomalies, and the depletion of natural resources, which have prompted humanity to look beyond our planet for potential habitable worlds. Exoplanets within the habitable zone, such as K2-18b, may possess liquid water, a stable atmosphere, and organic molecules that could sustain life. The James Webb Space Telescope (JWST) has provided groundbreaking observations through transit spectroscopy revealing the presence of water vapor and possible biosignatures such as dimethyl sulfide (DMS), a compound commonly associated with biological processes on Earth. However, JWST’s data accuracy is still hindered by three major challenges: thermal and instrumental noise, stellar activity interference including flares and starspots, and limited spectral databases that fail to fully replicate cosmic conditions. To address these limitations, deep learning methods can improve signal extraction, HRCCS technology can enhance spectral precision, and quantum computing simulations can generate more realistic atmospheric spectra. Future interdisciplinary integration will advance exoplanetary research toward reliable life detection.