Presaging Doppler beaming discoveries of double white dwarfs during the Rubin LSST era
Gautham Adamane Pallathadka, Yossef Zenati, Nadia L. Zakamska, Ngan H. Nguyen, Anthony L. Piro

TL;DR
This paper demonstrates that the Vera C. Rubin Observatory LSST can detect and characterize double white dwarf binaries through Doppler beaming, providing new insights into binary evolution and gravitational wave sources.
Contribution
It introduces a comprehensive simulation framework predicting LSST's capability to identify Doppler-beamed DWDs, linking observations to binary evolution models.
Findings
LSST can recover at least 287 short-period DWDs.
47 DWDs are detectable by LISA as gravitational wave sources.
Lightcurves enable full orbital characterization.
Abstract
Double white dwarfs (DWDs) are by far the most common compact binaries in the Milky Way, are important low-frequency gravitational-wave sources, and in some cases merge to become Type Ia supernovae. So far, no DWD has been identified solely through relativistic Doppler beaming, even though the beaming amplitude directly relates to the radial velocity semi-amplitude. In this work, we initiate a comprehensive binary population synthesis using SeBa and incorporate the resulting binaries into a tripartite Galaxy model. Our proof-of-concept simulations demonstrate that the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) can reliably recover relatively bright (mag) unequal-mass binaries in compact orbits with P 10-600 minutes with moderate to high inclinations. We find that LSST can detect at least 287 short-period DWDs, of which 47 are…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStellar, planetary, and galactic studies · Gamma-ray bursts and supernovae · Astronomy and Astrophysical Research
