Examinando por Autor "Grasha, Kathryn"

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    A machine learning approach to galactic emission-line region classification
    (Oxford University Press, 2023) Rhea, Carter L.; Rousseau-Nepton, Laurie; Moumen, Ismael; Prunet, Simon; Hlavacek-Larrondo, Julie; Grasha, Kathryn; Robert, Carmelle; Morisset, Christophe; Stasinska, Grazyna; Vale-Asari, Natalia; Giroux, Justine; Mcleod, Anna; Gendron-Marsolais, Marie-Lou; Wang, Junfeng; Lyman, Joe; Chemin, Laurent
    Diagnostic diagrams of emission-line ratios have been used e xtensiv ely to categorize extragalactic emission regions; ho we ver, these diagnostics are occasionally at odds with each other due to differing definitions. In this work, we study the applicability of supervised machine-learning techniques to systematically classify emission-line regions from the ratios of certain emission lines. Using the Million Mexican Model database, which contains information from grids of photoionization models using cloudy , and from shock models, we develop training and test sets of emission line fluxes for three key diagnostic ratios. The sets are created for three classifications: classic H II regions, planetary nebulae, and supernova remnants. We train a neural network to classify a region as one of the three classes defined abo v e giv en three ke y line ratios that are present both in the SITELLE and MUSE instruments' band-passes: [O III ] λ5007/H β, [N II ] λ6583/H α, ([S II ] λ6717 + [S II ] λ6731)/H α. We also tested the impact of the addition of the [O II ] λ3726, 3729/[O III ] λ5007 line ratio when available for the classification. A maximum luminosity limit is introduced to impro v e the classification of the planetary nebulae. Furthermore, the network is applied to SITELLE observations of a prominent field of M33. We discuss where the network succeeds and why it fails in certain cases. Our results provide a framework for the use of machine learning as a tool for the classification of extragalactic emission regions. Further work is needed to build more comprehensive training sets and adapt the method to additional observational constraints. © 2023 The Author(s).
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    Constraining the LyC escape fraction from LEGUS star clusters with SIGNALS H ii region observations: a pilot study of NGC 628
    (Oxford University Press, 2023-09-01) Teh, Jia Wei; Grasha, Kathryn; Krumholz, Mark R; Battisti, Andrew J; Calzetti, Daniela; Rousseau-Nepton, Laurie; Rhea, Carter; Adamo, Angela; Kennicutt, Robert C; Grebel, Eva K; Cook, David O; Combes, Francoise; Messa, Mateo; Linden, Sean T.; Klessen, Ralf S; Vilchez, Jos M; Fumagalli, Michele; Mcleod, Anna; Smith, Linda J; Chemin, Laurent; Wang, Junfeng; Sabbi, Elena; Sacchi, Elena; Petric, Andreea; Bruna, Lorenza Della; Boselli, Alessandro
    The ionizing radiation of young and massive stars is a crucial form of stellar feedback. Most ionizing (Lyman-continuum; LyC, λ < 912Å) photons are absorbed close to the stars that produce them, forming compact H ii regions, but some escape into the wider galaxy. Quantifying the fraction of LyC photons that escape is an open problem. In this work, we present a seminovel method to estimate the escape fraction by combining broadband photometry of star clusters from the Legacy ExtraGalactic UV Survey (LEGUS) with H ii regions observed by the Star formation, Ionized gas, and Nebular Abundances Legacy Survey (SIGNALS) in the nearby spiral galaxy NGC 628. We first assess the completeness of the combined catalogue, and find that 49 per cent of H ii regions lack corresponding star clusters as a result of a difference in the sensitivities of the LEGUS and SIGNALS surveys. For H ii regions that do have matching clusters, we infer the escape fraction from the difference between the ionizing power required to produce the observed H ii luminosity and the predicted ionizing photon output of their host star clusters; the latter is computed using a combination of LEGUS photometric observations and a stochastic stellar population synthesis code slug (Stochastically Lighting Up Galaxies). Overall, we find an escape fraction of across our sample of 42 H ii regions; in particular, we find H ii regions with high fesc are predominantly regions with low -luminosity. We also report possible correlation between fesc and the emission lines and. © 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.