FLARES iterative line-selection algorithm achieves 1.122 m/s RV RMS using 24 lines on 383 days of NEID solar data, better than full list or CCF.
S., Naylor, T., Haywood, R
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Deep neural networks using temperature-based spectral representations recover planetary Doppler signals with amplitudes of at least 25 cm/s from HARPS-N solar spectra under cross-validation.
The diagnostic separates granulation-sensitive and stable lines in late-G and K dwarfs, with FeI lines showing lower velocity sensitivity than FeII as effective temperature decreases, making solar line selections non-portable.
citing papers explorer
-
Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection
Deep neural networks using temperature-based spectral representations recover planetary Doppler signals with amplitudes of at least 25 cm/s from HARPS-N solar spectra under cross-validation.