Searching for Magnetar Binaries Disrupted by Core-Collapse Supernovae
Description
This repository contains data associated with "Searching for Magnetar Binaries Disrupted by Core-Collapse Supernovae" by Myles B. Sherman, Vikram Ravi, Kareem El-Badry, Kritti Sharma, Stella Ocker, Nikita Kosogorov, Liam Connor, and Jakob Faber. For details on the data format, see the ReadMe.md file.
Abstract: Core-collapse Supernovae (CCSNe) are considered to be the primary magnetar formation channel, with 15 magnetars associated with supernova remnants (SNRs). A large fraction of these should occur in massive stellar binaries that are disrupted by the explosion, meaning that $\sim45\%$ of magnetars should be nearby high-velocity stars. Here we conduct a multi-wavelength search for unbound stars, magnetar binaries, and SNR shells using public optical ($uvgrizy-$bands), infrared ($J-$, $H-$, $K-$, and $K_s-$bands), and radio ($888$\,MHz, $1.4$\,GHz, and $3$\,GHz) catalogs. We use Monte Carlo analyses of candidates to estimate the probability of association with a given magnetar based on their proximity, distance, proper motion, and magnitude. In addition to recovering a proposed magnetar binary, a proposed unbound binary, and 13 of 15 magnetar SNRs, we identify two new candidate unbound systems: an OB star from the \textit{Gaia} catalog we associate with SGR\,J1822.3-1606, and an X-ray pulsar we associate with 3XMM\,J185246.6+003317. Using a Markov-Chain Monte Carlo simulation that assumes all magnetars descend from CCSNe, we constrain the fraction of magnetars with unbound companions to $5\lesssim f_u \lesssim 24\%$, which disagrees with population synthesis results. Alternate formation channels are unlikely to wholly account for the lack of unbound binaries as this would require $31\lesssim f_{nc} \lesssim 66\%$ of magnetars to descend from such channels. Our results support a high fraction ($48\lesssim f_m \lesssim 86\%$) of pre-CCSN mergers, which can amplify fossil magnetic fields to preferentially form magnetars.
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Additional details
- Graduate Research Fellowship Program 2139433
- National Science Foundation
- The DSA: A Fast Radio Burst Localization Machine 1836018
- National Science Foundation
- Submitted
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2024-04-07