Imprints of quasar duty cycle on the 21cm signal from the Epoch of Reionization
Florian Bolgar (1), Evan Eames (1), Cl\'ement Hottier (2), Benoit, Semelin (1) ((1) LERMA, Observatoire de Paris, Sorbonne Universit\'e, PSL, research university, (2) GEPI, Observatoire de Paris, Universit\'e PSL)

TL;DR
This paper models quasar emissions during the Epoch of Reionization to understand their impact on the 21-cm signal, revealing potential observable imprints of quasar duty cycles in 21-cm tomography.
Contribution
It introduces a new model for quasar luminosity functions during the EoR and explores their effects on the 21-cm signal, including duty cycle imprints and Ly-alpha contributions.
Findings
Radio-loud quasars can imprint duty cycle signatures on 21-cm tomography.
Typical quasars have negligible effects in SKA observations, but brighter quasars may produce detectable patterns.
The collective quasar effect on the 21-cm power spectrum is significant at low k, with potential observability in tomography.
Abstract
Quasars contribute to the 21-cm signal from the Epoch of Reionization (EoR) primarily through their ionizing UV and X-ray emission. However, their radio continuum and Lyman-band emission also regulates the 21-cm signal in their direct environment, potentially leaving the imprint of their duty cycle. We develop a model for the radio and UV luminosity functions of quasars from the EoR, and constrain it using recent observations. Our model is consistent with the z~7.5 quasar from Banados et al 2017, and also predicts only a few quasars suitable for 21-cm forest observations (10mJy) in the sky. We exhibit a new effect on the 21-cm signal observed against the CMB: a radio-loud quasar can leave the imprint of its duty cycle on the 21-cm tomography. We apply this effect in a cosmological simulation and conclude that the effect of typical radio-loud quasars is most likely negligible in an SKA…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
