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Published October 1, 2021 | Published + Accepted Version
Journal Article Open

Prospects of Gravitational Wave Detections from Common Envelope Evolution with LISA

Abstract

Understanding common envelope (CE) evolution is an outstanding problem in binary evolution. Although the CE phase is not driven by gravitational wave (GW) emission, the inspiraling binary emits GWs that passively trace CE dynamics. Detecting this GW signal would provide direct insight into gas-driven physics. Even a non-detection might offer invaluable constraints. We investigate the prospects of detection of a Galactic CE by LISA. While the dynamical phase of the CE is likely sufficiently loud for detection, it is short and thus rare. We focus instead on the self-regulated phase that proceeds on a thermal timescale. Based on population-synthesis calculations and the (unknown) signal duration in the LISA band, we expect ∼0.1–100 sources in the Galaxy during the mission duration. We map the GW observable parameter space of frequency f_(GW) and its derivative f˙_(GW), remaining agnostic on the specifics of the inspiral and find that signals with signal-to-noise ratios > 10 are possible if the CE stalls at separations such that f_(GW) ≳ 2 × 10⁻³ Hz. We investigate the possibility of misidentifying the signal with other known sources. If the second derivative f¨_(GW) can also be measured, the signal can be distinguished from other sources using a GW braking index. Alternatively, coupling LISA with electromagnetic observations of peculiar red giant stars and/or infrared and optical transients, might allow for the disentangling of a Galactic CE from other Galactic and extragalactic GW sources.

Additional Information

© 2021. The American Astronomical Society. Received 2021 January 28; revised 2021 June 30; accepted 2021 July 1; published 2021 October 4. Portions of this study were performed during the LISA Sprint at the Center for Computational Astrophysics of the Flatiron Institute, supported by the Simons Foundation. M.R. thanks S. Justham and Y. F. Jiang for helpful discussions early on during this project and K. Breivik for guidance in using COSMIC and helpful feedback. We thank T. Littenberg for useful discussions on LISA parameter estimation. Software: COSMIC (Breivik et al. 2020), ipython/jupyter (Pérez & Granger 2007), matplotlib (Hunter 2007), NumPy (van der Walt et al. 2011).

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Published - Renzo_2021_ApJ_919_128.pdf

Accepted Version - 2102.00078.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023