Short-period double white dwarf (DWD) binaries will be the most prolific source of gravitational waves (GWs) for the Laser Interferometer Space Antenna (LISA). DWDs with GW frequencies below ∼1 mHz will be the dominant contributor to a stochastic foreground caused by overlapping GW signals. Population modeling of Galactic DWDs typically assumes a binary fraction of 50% and a log-uniform zero-age main sequence (ZAMS) orbital period distribution. However, recent observations have shown that the binary fraction of close, solar-type stars exhibits a strong anticorrelation with metallicity that modulates the ZAMS orbital period distribution below 10 4 days. In this study, we perform the first simulation of the Galactic DWD population observable by LISA that incorporates an empirically derived metallicity-dependent binary fraction, using the binary population synthesis suite COSMIC and a metallicity-dependent star formation history. We compare two models: one that assumes a metallicity-dependent binary fraction, and one with a binary fraction of 50%. We repeat our analysis for three different assumptions for Roche-lobe overflow interactions. We find that while metallicity impacts the evolution and intrinsic properties of our simulated DWD progenitor binaries, the LISA-resolvable populations of the two models remain roughly indistinguishable. However, the size of the total Galactic DWD population orbiting in the LISA frequency band is reduced by more than half when accounting for a metallicity-dependent binary fraction for two of our four variations, which also lowers the effective foreground. The LISA population remains unchanged in number for two variations, highlighting the sensitivity of the population to binary evolution prescriptions.
CITATION STYLE
Thiele, S., Breivik, K., Sanderson, R. E., & Luger, R. (2023). Applying the Metallicity-dependent Binary Fraction to Double White Dwarf Formation: Implications for LISA. The Astrophysical Journal, 945(2), 162. https://doi.org/10.3847/1538-4357/aca7be
Mendeley helps you to discover research relevant for your work.