Search NASA⌕ Search

Engineering topics

Vera-Ciro, Carlos

Publications and source records attributed to Vera-Ciro, Carlos.

MATCHING THE DARK MATTER PROFILES OF dSph GALAXIES WITH THOSE OF SIMULATED SATELLITES: A TWO-PARAMETER COMPARISON

We compare the dark matter halos’ structural parameters derived for four Milky Way dwarf spheroidal galaxies to those of subhalos found in cosmological N-body simulations. We confirm that estimates of the mass at a single fixed radius are fully consistent with the observations. However, when a second structural parameter such as the logarithmic slope of the dark halo density profile measured close to the half-light radius is included in the comparison, we find little to no overlap between the satellites and the subhalos. Typically the right mass subhalos have steeper profiles at these radii than measurements of the dSph suggest. Using energy arguments we explore if it is possible to solve this discrepancy by invoking baryonic effects. Assuming that feedback from supernovae (SNe) can lead to a reshaping of the halos, we compute the required efficiency and find entirely plausible values for a significant fraction of the subhalos and even as low as 0.1%. This implies that care must be taken not to exaggerate the effect of SNe feedback as this could make the halos too shallow. These results could be used to calibrate and possibly constrain feedback recipes in hydrodynamical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

AUTONOMOUS GAUSSIAN DECOMPOSITION

We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗