Grab a Byte PyLadies virtual meetup - Amelia's PhD Defense!

In lieu of our regular PyLadies meetup, I invite you to join and support our very own PyLady Amelia at her PhD thesis defense.

Amelia is a PhD candidate in Physics at the University of New Hampshire working with models of neutron star merger outflows. She is also an organizer of PyData Boston.

Abstract:
Binary neutron stars are among the most energetic events in the Universe, emitting strongly across the electromagnetic spectrum and responsible for producing some of the heaviest elements in the periodic table. However, several properties of their UV-O-IR electromagnetic transients (kilonovae) remain uncertain — namely, the relationship between source properties, outflow properties, and observables. In this thesis, I explore several aspects of this “map.” I first compare a suite of BNS outflow models across the full merger horizon to ascertain where they currently place robust constraints on the amount of mass predicted of a given merger. I then apply these models in a parameter estimation context, using them to identify when and how accurately we can extract source properties from mock light curve data. Aligning with the results of my first project, I find that stronger constraints can be placed on source properties for merger configurations for which there exists more simulation data, i.e. (M1, M2)=(1.4, 1.4)M☉. Lastly, I lay the foundation for a parameter estimation pipeline in which a suite of kilonova models can be compared against one another to explore how assumptions about the morphology and composition of the outflows can impact parameter recoverability, particularly when one varies the model employed as reference for PE in a method we refer to as cross-sampling. In doing so, we provide a comprehensive outlook on uncertainties in the BNS-to-kilonova pipeline.