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

Journal Article · · Journal of Cosmology and Astroparticle Physics
 [1];  [2];  [3];  [3]
  1. California Institute of Technology (CalTech), Pasadena, CA (United States); OSTI
  2. Vanderbilt University, Nashville, TN (United States)
  3. California Institute of Technology (CalTech), Pasadena, CA (United States)

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. Furthermore, for most PBH masses the constraints on the dark matter abundance agree with previous (frequentist) analyses (without mock data) to $$\mathcal{O}$$(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.

Research Organization:
California Institute of Technology (CalTech), Pasadena, CA (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
SC0021431
OSTI ID:
1853789
Report Number(s):
CALT-TH--2021-016
Journal Information:
Journal of Cosmology and Astroparticle Physics, Journal Name: Journal of Cosmology and Astroparticle Physics Journal Issue: 08 Vol. 2021; ISSN 1475-7516
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English

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