{"paper":{"title":"Improving cosmological distance measurements at high redshift using Lyman-Alpha forest BAO reconstruction","arxiv_id":"2610.37664","primary_cat":"astro-ph.CO","submitted_at":"2026-10-27T17:59:31+00:00","version_compiled":"v1"},"notice":"Every quoted sentence is the authors' text from the arXiv listing abstract. Labels and probabilities are the outputs of classifier-1.13.0 on the question bank abstract-p1-20260923, exactly as returned. 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peak.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.09,"main_claim_p":0.02,"quantitative":false,"quantitative_p":0.04,"role_probabilities":{"gap":0.05,"method":0.0,"result":0.0,"background":0.93,"limitation":0.01,"future_work":0.0,"contribution":0.0,"interpretation":0.0}},{"i":2,"p":0.67,"id":"s2","own":true,"role":"contribution","text":"To undo these effects, we extend standard Zel'dovich reconstruction, routinely applied to galaxy surveys, to the Lyman-alpha forest.","hedge":{"p":0.98,"label":"asserted"},"own_p":0.87,"main_claim_p":0.06,"quantitative":false,"quantitative_p":0.04,"role_probabilities":{"gap":0.0,"method":0.33,"result":0.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.67,"interpretation":0.0}},{"i":3,"p":0.9,"id":"s3","own":true,"role":"method","text":"We validate our methodology on large-volume idealized Lyman-alpha forest mocks painted on top of the \\textsc{AbacusSummit} $N$-body simulations, using linear control variates to suppress sample variance and thereby reduce the error bars by a factor of up to $\\approx \\sqrt{50}$.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.96,"main_claim_p":0.08,"quantitative":true,"quantitative_p":0.98,"role_probabilities":{"gap":0.0,"method":0.9,"result":0.06,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.04,"interpretation":0.0}},{"i":4,"p":1.0,"id":"s4","own":true,"role":"result","text":"In fully sampled periodic boxes, reconstruction halves the radial BAO damping scale and reduces the uncertainties on the radial ($\\apar$) and transverse ($\\aperp$) scaling parameters by $\\approx25\\%$ and $\\approx15\\%$, respectively.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.95,"main_claim_p":0.31,"quantitative":true,"quantitative_p":0.99,"role_probabilities":{"gap":0.0,"method":0.0,"result":1.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.0,"interpretation":0.0}},{"i":5,"p":1.0,"id":"s5","own":true,"role":"result","text":"It also reduces the non-linear shift from $\\Delta\\apar=+0.3\\%$ to $+0.10\\pm0.07\\%$, while $\\aperp$ remains unbiased.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.93,"main_claim_p":0.18,"quantitative":true,"quantitative_p":0.99,"role_probabilities":{"gap":0.0,"method":0.0,"result":1.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.0,"interpretation":0.0}},{"i":6,"p":0.51,"id":"s6","own":true,"role":"contribution","text":"To make this approach readily applicable to observational data, we demonstrate the impact of a survey mask with a DESI-like density of $50\\,\\mathrm{deg}^{-2}$.","hedge":{"p":0.99,"label":"asserted"},"own_p":0.89,"main_claim_p":0.03,"quantitative":false,"quantitative_p":0.36,"role_probabilities":{"gap":0.0,"method":0.49,"result":0.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.51,"interpretation":0.0}},{"i":7,"p":0.91,"id":"s7","own":true,"role":"method","text":"For this mask, we compare two approaches to estimate the displacement field: either directly from the Lyman-alpha forest or using an external tracer with a number density of $\\bar n \\simeq 10^{-3}\\,h^3\\mathrm{Mpc}^{-3}$, such as Lyman-break galaxies and Lyman-$\\alpha$ emitters---both key targets for DESI-II.","hedge":{"p":0.87,"label":"asserted"},"own_p":0.8,"main_claim_p":0.04,"quantitative":true,"quantitative_p":0.96,"role_probabilities":{"gap":0.0,"method":0.91,"result":0.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.09,"interpretation":0.0}},{"i":8,"p":1.0,"id":"s8","own":true,"role":"result","text":"Both approaches give comparable gains and reduce the uncertainties on $\\apar$ and $\\aperp$ by $\\approx 27\\%$ and $\\approx 10\\%$, respectively, with mild improvements for futuristic high-density surveys with $160\\,\\mathrm{deg}^{-2}$.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.94,"main_claim_p":0.22,"quantitative":true,"quantitative_p":0.99,"role_probabilities":{"gap":0.0,"method":0.0,"result":1.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.0,"interpretation":0.0}},{"i":9,"p":0.98,"id":"s9","own":true,"role":"result","text":"Correspondingly, the figure of merit improves by factors of $1.66$ for fully sampled boxes, $1.65$ for a DESI-like, and $1.76$ for a high-density survey.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.93,"main_claim_p":0.33,"quantitative":true,"quantitative_p":0.99,"role_probabilities":{"gap":0.0,"method":0.0,"result":0.98,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.0,"interpretation":0.02}}]},"compiled":{"main_claim":{"p":0.47,"text":"Correspondingly, the figure of merit improves by factors of $1.66$ for fully sampled boxes, $1.65$ for a DESI-like, and $1.76$ for a high-density survey.","location":"abstract 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