Efficient reduction of stellar contamination and noise in planetary transmission spectra using neural networks
This work presents a methodology for reducing stellar contamination and instrument-specific noise from exoplanet transmission spectra using neural networks, in particular the so-called Denoising AutoEncoders (DAEs), and demonstrates that DAEs outperform conventional correction methods in computational efficiency while...