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Searching for Dark Matter Signals from Local Dwarf Spheroidal Galaxies at Low Radio Frequencies in the GLEAM Survey

By Robin H. W. Cook, Nick Seymour, Kristine Spekkens, Natasha Hurley-Walker, Paul J. Hancock, Martin E. Bell, Joseph R. Callingham, Bi-Qing For, Thomas M. O. Franzen, Bryan M. Gaensler, Luke Hindson, Carole A. Jackson, Melanie Johnston-Hollitt, Anna D. Kapińska, John Morgan, André R. Offringa, Pietro Procopio, Lister Staveley-Smith, Randall B. Wayth, Chen Wu and Qian Zheng


The search for emission from weakly interacting massive particle (WIMP) dark matter annihilation and decay has become a multi-pronged area of research not only targeting a diverse selection of astrophysical objects, but also taking advantage of the entire electromagnetic spectrum. The decay of WIMP particles into standard model particles has been suggested as a possible channel for synchrotron emission to be detected at low radio frequencies. Here, we present the stacking analysis of a sample of 33 dwarf spheroidal (dSph) galaxies with low-frequency (72 - 231 MHz) radio images from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey. We produce radial surface brightness profiles of images centred upon each dSph galaxy with background radio sources masked. We remove ten fields from the stacking due to contamination from either poorly subtracted, bright radio sources or strong background gradients across the field. The remaining 23 dSph galaxies are stacked in an attempt to obtain a statistical detection of any WIMP-induced synchrotron emission in these systems. We find that the stacked radial brightness profile does not exhibit a statistically significant detection above the 95% confidence level of $\sim$1.5 mJy beam$^{-1}$. This novel technique shows the potential of using low-frequency radio images to constrain fundamental properties of particle dark matter.Comment: 11 pages, 7 Figures, Accepted for publication in MNRA

Topics: Astrophysics - Astrophysics of Galaxies
Publisher: 'Oxford University Press (OUP)'
Year: 2020
DOI identifier: 10.1093/mnras/staa726
OAI identifier:

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