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Astrophysics > Cosmology and Nongalactic Astrophysics

Title: Cosmology-independent Photon Mass Limits from Localized Fast Radio Bursts by using Artificial Neural Networks

Abstract: A hypothetical photon mass, $m_{\gamma}$, can produce a frequency-dependent vacuum dispersion of light, which leads to an additional time delay between photons with different frequencies when they propagate through a fixed distance. The dispersion measure--redshift measurements of fast radio bursts (FRBs) have been widely used to constrain the rest mass of the photon. However, all current studies analyzed the effect of the frequency-dependent dispersion for massive photons in the standard $\Lambda$CDM cosmological context. In order to alleviate the circularity problem induced by the presumption of a specific cosmological model based on the fundamental postulate of the masslessness of photons, here we employ a new model-independent smoothing technique, Artificial Neural Network (ANN), to reconstruct the Hubble parameter $H(z)$ function from 34 cosmic-chronometer measurements. By combining observations of 32 well-localized FRBs and the $H(z)$ function reconstructed by ANN, we obtain an upper limit of $m_{\gamma} \le 3.5 \times 10^{-51}\;\rm{kg}$, or equivalently $m_{\gamma} \le 2.0 \times 10^{-15}\;\rm{eV/c^2}$ ($m_{\gamma} \le 6.5 \times 10^{-51}\;\rm{kg}$, or equivalently $m_{\gamma} \le 3.6 \times 10^{-15}\;\rm{eV/c^2}$) at the $1\sigma$ ($2\sigma$) confidence level. This is the first cosmology-independent photon mass limit derived from extragalactic sources.
Comments: 8 pages, 3 figures, 3 tables. Accepted for publication in Chinese Physics Letters. Invited article to special issue "FAST"
Subjects: Cosmology and Nongalactic Astrophysics (astro-ph.CO); High Energy Astrophysical Phenomena (astro-ph.HE); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Phenomenology (hep-ph)
Cite as: arXiv:2404.17154 [astro-ph.CO]
  (or arXiv:2404.17154v1 [astro-ph.CO] for this version)

Submission history

From: Jun-Jie Wei Dr. [view email]
[v1] Fri, 26 Apr 2024 04:55:36 GMT (308kb,D)

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