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Constraints on the mean free path of ionising photons at $z\sim6$ using limits on individual free paths

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arxiv 2108.12446 v2 pith:Z6BYU7XO submitted 2021-08-27 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords freeindividuallowerconstraintsionisinglimitspathpaths
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abstract

The recent measurement of an ionising mean free path $\lambda_{\text{mfp}}<1$ pMpc at $z=6$ challenges our understanding of the small-scale structure of the intergalactic medium (IGM) at the end of reionisation. We introduce a new method to constrain \mfp at $z=6$ by using lower limits on the individual free paths of ionisation around quasars. Lyman-limit absorbers with a density sufficient to halt ionising photons produce strong absorption in the 6 lowest-energy Lyman transitions, in the absence of which a robust lower limit can be placed on the individual free path. Applying this method to a set of $26$ quasars at $5.5<z<6.5$, we find that $80\%$ of bright quasars ($M_{1450}<-26.5$) require individual free paths larger than $2$ pMpc. We model the relation between opacity $\kappa$ and photo-ionisation rate $\Gamma$ via the parameter $\xi$ such that $\kappa\propto\Gamma^{-\xi}$, and pose joint limits on \mfp and $\xi$. For the nominal value of $\xi=2/3$, we constrain $\lambda_{\text{mfp}}>0.31 \ (0.18)$ pMpc at $2\sigma \ (3\sigma)$: a much tighter lower bound than obtained through traditional stacking methods. Our constraints get significantly stronger for lower values of $\xi$. New constraints on \mfp and $\xi$ are crucial to our understanding of the reionisation-era IGM.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Measuring the Mean Free Path of HI Ionizing Photons at $3.2\leq z\leq4.6$ with DESI Y1 Quasars

    astro-ph.CO 2024-11 conditional novelty 6.0 of 10

    The mean free path of ionizing photons evolves as (1+z)^-4.27 between z=2 and z=5, with a break at z=4.93, based on 12,595 DESI quasar spectra.

  2. Extreme Deconvolution Reimagined: Conditional Densities via Neural Networks and an Application in Quasar Classification

    astro-ph.IM 2024-12 conditional novelty 5.0 of 10

    For quasar-contaminant colors, CondXD produces noise-deconvolved conditional densities that visually match binned extreme deconvolution while training roughly ten times faster.

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