aqc

hello! i’m currently on a gap year between undergrad (MIT ‘24 physics) and grad school (princeton astrophysics). i’m currently researching at the max planck institute for gravitational physics (albert einstein institute) on a fulbright fellowship, studying dark siren methods for measuring the hubble constant with gravitational wave sources. broadly, my research interests include cosmology, gravity, and astrophysical transients. i’m a 2023 astronaut scholar and a 2023 ligo surf.

in high school, i did the astrophysics olympiad and science olympiad. something i’m still heavily involved in is writing astronomy tests and pedagogical resources for science olympiad. outside of school and research, i think about life, ramble about it sometimes, enjoy playing video games (mostly indie games and VALORANT), and watch a lot of anime.

publications

ApJ

What You Don’t Know Can Hurt You: Use and Abuse of Astrophysical Models in Gravitational-wave Population Analyses
April Qiu Cheng, Michael Zevin, and Salvatore Vitale

The Astrophysical Journal, Oct 2023

Abs NASA ADS arXiv PDF

One of the goals of gravitational-wave astrophysics is to infer the number and properties of the formation channels of binary black holes (BBHs); to do so, one must be able to connect various models with the data. We explore benefits and potential issues with analyses using models informed by population synthesis. We consider 5 possible formation channels of BBHs, as in Zevin et al. (2021b). First, we confirm with the GWTC-3 catalog what Zevin et al. (2021b) found in the GWTC-2 catalog, i.e. that the data are not consistent with the totality of observed BBHs forming in any single channel. Next, using simulated detections, we show that the uncertainties in the estimation of the branching ratios can shrink by up to a factor of 1.7 as the catalog size increases from 50 to 250, within the expected number of BBH detections in LIGO-Virgo-KAGRA’s fourth observing run. Finally, we show that this type of analysis is prone to significant biases. By simulating universes where all sources originate from a single channel, we show that the influence of the Bayesian prior can make it challenging to conclude that one channel produces all signals. Furthermore, by simulating universes where all 5 channels contribute but only a subset of channels are used in the analysis, we show that biases in the branching ratios can be as large as 50% with 250 detections. This suggests that caution should be used when interpreting the results of analyses based on strongly modeled astrophysical sub-populations.