[Sabbatical Report]

I spent my AY2014 sabbatical year at the Space Telescope Science Institute (STScI), with plans of completing the analyses of supernova rates for both thermonuclear and corecolliape events in high redshift galaxies from the Multi-cycle Treasury Projects with the Hubble Space Telescope

The Deepest Supernova Search is Realized in the Hubble Ultra Deep Field Survey

The Hubble Ultra Deep Field Survey has not only provided the deepest optical and near infrared views of universe, but has enabled a search for the most distant supernovae to z~2.2. We have found four supernovae by searching spans of integrations of the Ultra Deep Field and the Ultra Deep Field Parallels taken with the Hubble Space Telescope paired with the Advanced Camera for Surveys and the Near Infrared Multi Object Spectrometer. Interestingly, none of these supernovae were at z>1.4, despite the substantially increased sensitivity per unit area to such objects over the Great Observatories Origins Deep Survey. We present the optical photometric data for the four supernovae. We also show that the low frequency of Type Ia supernovae observed at z>1.4 is statistically consistent with current estimates of the global star formation history combined with the non-trivial assembly time of SN Ia progenitors.Comment: 24 pages (6 figures), submitted to the Astronomical Journa

Empirical Delay Time Distributions of Type Ia Supernovae From The Extended GOODS/HST Supernova Survey

Using the Hubble Space Telescope ACS imaging of the GOODS North and South fields during Cycles 11, 12, and 13, we derive empirical constraints on the delay-time distribution function for type Ia supernovae. We extend our previous analysis to the three-year sample of 56 SNe Ia over the range 0.2<z<1.8, using a Markov chain Monte Carlo to determine the best-fit unimodal delay-time distribution function. The test, which ultimately compares the star formation rate density history to the unbinned volumetric SN Ia rate history from the GOODS/HST-SN survey, reveals a SN Ia delay-time distribution that is tightly confined to 3-4 Gyrs (to >95% confidence). This result is difficult to resolve with any intrinsic delay-time distribution function (bimodal or otherwise), in which a substantial fraction (e.g., >10%) of events are ``prompt'', requiring less than approximately 1 Gyr to develop from formation to explosion. The result is, however, strongly motivated by the decline in the number of SNe Ia at z>1.2. Sub-samples of the HST-SN data confined to lower redshifts (z<1) show plausible delay-time distributions that are dominated by prompt events, which is more consistent with results from low-redshift supernova samples and supernova host galaxy properties. Scenarios in which a substantial fraction of z>1.2 supernovae are extraordinarily obscured by dust may partly explain the differences in low-z and high-z results. Other possible resolutions may include environmental dependencies (such as gas-phase metallicity) that affect the progenitor mechanism efficiency, especially in the early universe.Comment: 12 pages, 9 figures, accepted to the Astrophysical Journa

PACMan2: Next Steps in Proposal Review Management

With the start of a new Great Observatories era, there is renewed concern that the demand for these forefront facilities, through proposal pressure, will exceed conventional peer-review management's capacity for ensuring an unbiased and efficient selection. There is need for new methods, strategies, and tools to facilitate those reviews. Here, we describe PACMan2, an updated tool for proposal review management that utilizes machine learning models and techniques to topically categorize proposals and reviewers, to match proposals to reviewers, and to facilitate proposal assignments, mitigating some conflicts of interest. We find that the classifier has cross-validation accuracy of $80.0\pm2.2\%$ on proposals for time on the Hubble Space Telescope and the James Webb Space Telescope.Comment: 10 pages, 7 figure