2022
DOI: 10.1093/mnras/stac1224
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Updated bounds on axion-like particles from X-ray observations

Abstract: In this work we revisit five different point sources within or behind galaxy clusters in order to constrain the coupling constant between axion-like particles (ALPs) and photons. We use three distinct machine learning (ML) techniques and compare our results with a standard χ2 analysis. For the first time we apply approximate Bayesian computation to searches for ALPs and find consistently good performance across ML classifiers. Further, we apply more realistic 3D magnetic field simulations of galaxy clusters an… Show more

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Cited by 13 publications
(16 citation statements)
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“…The intensity modulation is difficult to observe unless there are reasons that the change in intensity varies rapidly with frequency. Such spectral modulations are indeed expected from a variety of extragalactic 𝑋-ray sources (see, e.g., [201][202][203][204] and references therein).…”
Section: Axion-induced Spectral Modulation From Extragalactic Sourcesmentioning
confidence: 81%
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“…The intensity modulation is difficult to observe unless there are reasons that the change in intensity varies rapidly with frequency. Such spectral modulations are indeed expected from a variety of extragalactic 𝑋-ray sources (see, e.g., [201][202][203][204] and references therein).…”
Section: Axion-induced Spectral Modulation From Extragalactic Sourcesmentioning
confidence: 81%
“…This is not a realistic picture of what 𝑃 𝛾→𝛾 may look like, since it approximates the cluster as a single domain, but it illustrates the oscillatory features that arise due to the sin term in (114). With multiple domains, the oscillations at keV frequencies can become even more frequent (see, e.g., [201][202][203][204]). The axion-photon coupling 𝑔 𝑎𝛾𝛾 controls the strength of the oscillations.…”
Section: Axion-induced Spectral Modulation From Extragalactic Sourcesmentioning
confidence: 96%
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“…This will be the subject of a future publication. We highlight that training the CNN on residuals from fitting synthetic data-rather than on spectra-could also help improve the CNN's performance (see Schallmoser et al 2021).…”
Section: ( ) |mentioning
confidence: 99%