PIRSA:22110110

No peaks without valleys: learning about massive stars from the masses of merging black holes

APA

van Son, L. (2022). No peaks without valleys: learning about massive stars from the masses of merging black holes. Perimeter Institute for Theoretical Physics. https://pirsa.org/22110110

MLA

van Son, Lieke. No peaks without valleys: learning about massive stars from the masses of merging black holes. Perimeter Institute for Theoretical Physics, Nov. 24, 2022, https://pirsa.org/22110110

BibTex

          @misc{ scivideos_PIRSA:22110110,
            doi = {10.48660/22110110},
            url = {https://pirsa.org/22110110},
            author = {van Son, Lieke},
            keywords = {Strong Gravity},
            language = {en},
            title = {No peaks without valleys: learning about massive stars from the masses of merging black holes},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2022},
            month = {nov},
            note = {PIRSA:22110110 see, \url{https://scivideos.org/pirsa/22110110}}
          }
          

Lieke van Son Harvard University

Talk numberPIRSA:22110110
Source RepositoryPIRSA
Collection

Abstract

Gravitational wave observations are revealing new features in the mass distribution of merging binary black holes (BBHs). The BBHs we observe today are relics of massive stars that lived in the early Universe, and we aim to use their properties to help reveal the lives and deaths of their stellar ancestors.   

In this talk, I will discuss which of the observed features are robust, and if/how we can use them to constrain the uncertain progenitor physics. I will focus on the lowest mass BHs, just above the edge of NS formation because we find they I) contain crucial information about the most common formation pathway, II) are least affected by uncertainties in the cosmic star formation, and III) shine new light on the much-disputed mass-gap between neutron stars and black holes.

Zoom link:  https://pitp.zoom.us/j/91476126992?pwd=QXdENmErYklaYTdLcDZNTVBXamlXdz09