FLAME: Fitting Lyα absorption lines using machine learning
P. Jalan,
V. Khaire,
M. Vivek
et al.
Abstract:We introduce FLAME, a machine-learning algorithm designed to fit Voigt profiles to H i Lyman-alpha ( absorption lines using deep convolutional neural networks. FLAME integrates two algorithms: the first determines the number of components required to fit absorption lines, and the second calculates the Doppler parameter $b$, the H i column density N$_ HI $, and the velocity separation of individual components. For the current version of FLAME, we trained it on low-redshift forests observed with the far-ultravio… Show more
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