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Search for dark-photon dark matter in the SuperMAG geomagnetic field dataset

Published 19 Aug 2021 in hep-ph and astro-ph.CO | (2108.08852v2)

Abstract: In our recent companion paper [arXiv:2106.00022], we pointed out a novel signature of ultralight kinetically mixed dark-photon dark matter. This signature is a quasi-monochromatic, time-oscillating terrestrial magnetic field that takes a particular pattern over the surface of the Earth. In this work, we present a search for this signal in existing, unshielded magnetometer data recorded by geographically dispersed, geomagnetic stations. The dataset comes from the SuperMAG Collaboration and consists of measurements taken with one-minute cadence since 1970, with $\mathcal{O}(500)$ stations contributing in all. We aggregate the magnetic field measurements from all stations by projecting them onto a small set of global vector spherical harmonics (VSH) that capture the expected vectorial pattern of the signal at each station. Within each dark-photon coherence time, we use a data-driven technique to estimate the broadband background noise in the data, and search for excess narrowband power in this set of VSH components; we stack the searches in distinct coherence times incoherently. Following a Bayesian analysis approach that allows us to account for the stochastic nature of the dark-photon dark-matter field, we set exclusion bounds on the kinetic mixing parameter in the dark-photon dark-matter mass range $2\times10{-18}\,\text{eV} \lesssim m_{A'} \lesssim 7\times10{-17}\,\text{eV}$ (corresponding to frequencies $6\times 10{-4}\,\text{Hz}\lesssim f_{A'} \lesssim 2\times 10{-2}\,\text{Hz}$). These limits are complementary to various existing astrophysical constraints. Although our main analysis also identifies a number of candidate signals in the SuperMAG dataset, these appear to either fail or be in tension with various additional robustness checks we apply to those candidates. We report no robust and significant evidence for a dark-photon dark-matter signal in the SuperMAG dataset.

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