78 citations · 261 across the 35 of their papers we have counts for
5 papers · 1 filter
Updates to LUCI: A New Fitting Paradigm Using Mixture Density Networks
Carter L. Rhea, Julie Hlavacek-Larrondo, Laurie Rousseau-Nepton +1
LUCI is an general-purpose spectral line-fitting pipeline which natively integrates machine learning algorithms to initialize fit functions. LUCI currently uses point-estimates obt…
A Machine Learning Approach to Integral Field Unit Spectroscopy Observations: III. Disentangling Multiple Components in Hii regions
Carter Lee Rhea, Laurie Rousseau-Nepton, Simon Prunet +7
In the first two papers of this series (Rhea et al. 2020; Rhea et al. 2021), we demonstrated the dynamism of machine learning applied to optical spectral analysis by using neural n…
LUCI: A Python package for SITELLE spectral analysis
Carter Lee Rhea, Julie Hlavacek-Larrondo, Laurie Rousseau-Nepton +2
High-resolution optical integral field units (IFUs) are rapidly expanding our knowledge of extragalactic emission nebulae in galaxies and galaxy clusters. By studying the spectra o…
A Data-driven Approach to X-ray Spectral Fitting: Quasi-Deconvolution
Carter Lee Rhea, Julie Hlavacek-Larrondo, Ralph Kraft +2
X-ray spectral fitting of astronomical sources requires convolving the intrinsic spectrum or model with the instrumental response. Standard forward modeling techniques have proven…
A Machine Learning Approach to Integral Field Unit Spectroscopy Observations: II. HII Region LineRatios
Carter Rhea, Laurie Rousseau-Nepton, Simon Prunet +5
In the first paper of this series (Rhea et al. 2020), we demonstrated that neural networks can robustly and efficiently estimate kinematic parameters for optical emission-line spec…