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Published August 2021 | Submitted
Journal Article Open

Bayesian forecasts for dark matter substructure searches with mock pulsar timing data

Abstract

Dark matter substructure, such as primordial black holes (PBHs) and axion miniclusters, can induce phase shifts in pulsar timing arrays (PTAs) measurements due to gravitational effects. In order to gain a more realistic forecast for the detectability of such models of dark matter with PTAs, we propose a Bayesian inference framework to search for phase shifts generated by PBHs and perform the analysis on mock PTA data. For most PBH masses the constraints on the dark matter abundance agree with previous (frequentist) analyses (without mock data) to O(1) factors. This further motivates a dedicated search for PBHs (and dense small scale structures) in the mass range from 10⁻⁸ M☉ to well above 10² M☉ with the Square Kilometer Array. Moreover, with a more optimistic set of timing parameters, future PTAs are predicted to constrain PBHs down to 10⁻¹¹ M☉. Lastly, we discuss the impact of backgrounds, such as Supermassive Black Hole Mergers, on detection prospects, suggesting a future program to separate a dark matter signal from other astrophysical sources.

Additional Information

© 2021 IOP Publishing Ltd and Sissa Medialab. Received 30 April 2021; Accepted 9 July 2021; Published 12 August 2021. VL, TT and KZ are supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0021431 and a Simons Investigator award. SRT acknowledges support from NSF grant AST-#2007993, and a Dean's Faculty Fellowship from Vanderbilt University's College of Arts & Science. The computations presented here were conducted on the Caltech High Performance Cluster, partially supported by a grant from the Gordon and Betty Moore Foundation.

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August 20, 2023
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