Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 92 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 36 tok/s
GPT-5 High 36 tok/s Pro
GPT-4o 113 tok/s
GPT OSS 120B 472 tok/s Pro
Kimi K2 214 tok/s Pro
2000 character limit reached

Constraining Formation Models of Binary Black Holes with Gravitational-Wave Observations (1704.07379v3)

Published 24 Apr 2017 in astro-ph.HE, astro-ph.GA, astro-ph.SR, and gr-qc

Abstract: Gravitational waves (GWs) from binary black hole (BBH) mergers provide a new probe of massive-star evolution and the formation channels of binary compact objects. By coupling the growing sample of BBH systems with population synthesis models, we can begin to constrain the parameters of such models and glean unprecedented knowledge about the inherent physical processes that underpin binary stellar evolution. In this study, we apply a hierarchical Bayesian model to mass measurements from a synthetic GW sample to constrain the physical prescriptions in population models and the relative fraction of systems generated from various channels. We employ population models of two canonical formation scenarios in our analysis --- isolated binary evolution involving a common-envelope phase and dynamical formation within globular clusters --- with model variations for different black hole natal kick prescriptions. We show that solely with chirp mass measurements, it is possible to constrain natal kick prescriptions and the relative fraction of systems originating from each formation channel with $\mathcal{O}(100)$ of confident detections. This framework can be extended to include additional formation scenarios, model parameters, and measured properties of the compact binary.

Citations (140)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube