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Identifying and Characterizing Very Low-mass Spectral Blend Binaries with Machine Learning Methods

Authors: Juan Diego Draxl Giannoni, Malina Desai, Adam J. Burgasser, A. Camille Dunning, Christian Aganze, Luke McDermott, Christopher A. Theissen, Daniella C. Bardalez Gagliuffi

Juan Diego Draxl Giannoni et al 2026 The Astronomical Journal 171 .

Provider: AAS Journals

Caption: Figure 1.

J-band S/N vs. spectral type of our empirical spectral sample. Each individual spectrum is plotted and color coded by its assignment to low- (S/N < 50, light blue), mid- (50 ≤ S/N < 100, medium blue), and high-S/N (S/N ≥ 100, dark blue) groups. We show the marginalized distributions of the spectral type along the top axis, and for S/N along the right axis.

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