Precision Cosmology with Photometrically-Classified Supernovae

Type 1a supernovae can be used as a tool to measure distances to galaxies at high redshift. Surveys of such supernovae therefore allow astronomers to determine cosmological parameters. This project makes use of imaging surveys to make improvements in photometric classification of supernovae and to construct a framework for accurately characterizing the resulting uncertainties on cosmological model parameters.

The Principal Investigator will establish a new mentoring program for physics majors at the University of Pennsylvania. This program will help create a cultural shift within the department and increase awareness of issues related to inclusivity and diversity.

Cosmological parameter measurements with present and future supernova surveys will rely on photometric Type Ia supernova (SN Ia) classification with or without spectroscopic redshifts of the host galaxies. The PI will conduct a research program to make improvements in photometric classification and to construct a framework for accurately characterizing the systematic uncertainties on cosmological model parameters.

The project focuses on quantifying the systematic uncertainties due to (1) photometric misclassification of SN candidates and (2) mis-association of their host galaxies. Data from the Dark Energy Survey will be used to characterize the non-SN Ia population. This will be used to help improve photometric classifiers as well as place robust uncertainties on misclassification rates versus redshift, which is essential for precision cosmology.

The methodology will be applied to help make further improvements with the Vera Rubin Observatory. The PI will establish a mentoring and support program for Physics majors at the University of Pennsylvania. The mentors will consist of graduate students, who will be trained through the PI and other teaching resources at Penn.

Undergraduate students will be paired with a mentor, who will guide them through the process of finding a research advisor, making realistic decisions about their career paths, and for those interested, help them with the graduate-school application process.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.