We use Gaussian Process Regression trained on the fluxes of external galaxies to estimate the Milky Way’s UV-to-IR SED.
MaNGA Milky Way Analogs consistently have younger stellar populations at large radii but a wide range of central stellar population ages; about half of the MWAs have central AGN or composite activity.
We use several machine learning algorithms to classify intermediate redshift emission line galaxies using only properties in optical spectra and ugriz photometry.
We develop a data access, exploration, analysis, and visualization toolkit for the SDSS-IV MaNGA survey that seamlessly transitions between locally and remotely-stored data.
We construct an analytic chemical evolution model with a realistic SNIa delay time distribution to probe how model parameters affect equilibrium abundances and the effects of sudden changes to those parameters.
We explore the trade-offs in parameters of chemical evolution models.
A Recalibration of Strong-line Oxygen Abundance Diagnostics via the Direct Method and Implications for the High-redshift Universe
We use direct method metallicities of stacked SDSS galaxies to recalibrate strong line metallicity diagnostics.
The direct method mass-metallicity relation has a steeper slope, a lower turnover mass, and a factor of 2-3 greater dependence on SFR than strong line mass-metallicity relations.
PCA of elemental abundances of bulge stars revealing that the first two components are (1) correlated alpha elements and (2) correlated Na and Ni—two elements that have metallicity-dependent core-collapse supernova yields.
Radiation pressure from the absorption and scattering of starlight by dust grains, which are hydrodynamically coupled to the gas, sets a hard upper limit to the luminosity of star-forming regions.