Browsing by Autor "Andrei Cuceu"

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Clustering of DESI galaxies split by thermal Sunyaev-Zeldovich effect
(2025) M. Rashkovetskyi; Daniel J. Eisenstein; J. Aguilar; S. P. Ahlen; Abhijeet Anand; D. Bianchi; David Brooks; F. J. Castander; T. Claybaugh; Andrei Cuceu
The thermal Sunyaev-Zeldovich (tSZ) effect is associated with galaxy clusters - extremely large and dense structures tracing the dark matter with a higher bias than isolated galaxies. We propose to use the tSZ data to separate galaxies from redshift surveys into distinct subpopulations corresponding to different densities and biases independently of the redshift survey systematics. Leveraging the information from different environments, as in density-split and density-marked clustering, is known to tighten the constraints on cosmological parameters, like <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>Ω</mml:mi> <mml:mi>m</mml:mi> </mml:msub> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>σ</mml:mi> <mml:mn>8</mml:mn> </mml:msub> </mml:math> and neutrino mass. We use data from the Dark Energy Spectroscopic Instrument (DESI) and the Atacama Cosmology Telescope (ACT) in their region of overlap to demonstrate informative tSZ splitting of Luminous Red Galaxies (LRGs). We discover a significant increase in the large-scale clustering of DESI LRGs corresponding to detections starting from 1-2 sigma in the ACT DR6 + Planck tSZ Compton- <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>y</mml:mi> </mml:math> map, below the cluster candidate threshold (4 sigma). We also find that such galaxies have higher line-of-sight coordinate (and velocity) dispersions and a higher number of close neighbors than both the full sample and near-zero tSZ regions. We produce simple simulations of tSZ maps that are intrinsically consistent with galaxy catalogs and do not include systematic effects, and find a similar pattern of large-scale clustering enhancement with tSZ effect significance. Moreover, we observe that this relative bias pattern remains largely unchanged with variations in the galaxy-halo connection model in our simulations. This is promising for future cosmological inference from tSZ-split clustering with semi-analytical models. Thus, we demonstrate that valuable cosmological information is present in the lower signal-to-noise regions of the thermal Sunyaev-Zeldovich map, extending far beyond the individual cluster candidates.
Construction of the damped <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>Ly</mml:mi> <mml:mi>α</mml:mi> </mml:mrow> </mml:math> absorber catalog for DESI DR2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mrow> <mml:mrow> <mml:mi>Ly</mml:mi> <mml:mi>α</mml:mi> </mml:mrow> </mml:mrow> </mml:mrow> </mml:math> BAO
(American Physical Society, 2025) A. Brodzeller; Molly Wolfson; D. Martínez Santos; Ming-Feng Ho; T. Tan; Matthew M. Pieri; Andrei Cuceu; M. Karim; J. Aguilar; S. P. Ahlen
We present the Damped <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mrow> <a:mi>Ly</a:mi> <a:mi>α</a:mi> </a:mrow> </a:math> Toolkit for automated detection and characterization of damped <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"> <c:mrow> <c:mi>Ly</c:mi> <c:mi>α</c:mi> </c:mrow> </c:math> absorbers (DLAs) in quasar spectra. Our method uses quasar spectral templates with and without absorption from intervening DLAs to reconstruct observed quasar forest regions. The best-fitting model determines whether a DLA is present while estimating the redshift and column density. With an optimized quality cut on detection significance ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"> <e:mi mathvariant="normal">Δ</e:mi> <e:msubsup> <e:mi>χ</e:mi> <e:mi>r</e:mi> <e:mn>2</e:mn> </e:msubsup> <e:mo>></e:mo> <e:mn>0.03</e:mn> </e:math> ), the technique achieves an estimated 80% purity and 79% completeness when evaluated on simulated spectra with <h:math xmlns:h="http://www.w3.org/1998/Math/MathML" display="inline"> <h:mi mathvariant="normal">S</h:mi> <h:mo>/</h:mo> <h:mrow> <h:mi mathvariant="normal">N</h:mi> <h:mo stretchy="false">></h:mo> <h:mn>2</h:mn> </h:mrow> </h:math> that are free of broad absorption lines (BALs). We provide a catalog containing candidate DLAs from the DLA Toolkit detected in DESI DR1 quasar spectra, of which 21 719 were found in <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"> <m:mi mathvariant="normal">S</m:mi> <m:mo>/</m:mo> <m:mrow> <m:mi mathvariant="normal">N</m:mi> <m:mo stretchy="false">></m:mo> <m:mn>2</m:mn> </m:mrow> </m:math> spectra with predicted <r:math xmlns:r="http://www.w3.org/1998/Math/MathML" display="inline"> <r:mrow> <r:msub> <r:mrow> <r:mi>log</r:mi> </r:mrow> <r:mn>10</r:mn> </r:msub> <r:mo stretchy="false">(</r:mo> <r:msub> <r:mrow> <r:mi>N</r:mi> </r:mrow> <r:mrow> <r:mi mathvariant="monospace">HI</r:mi> </r:mrow> </r:msub> <r:mo stretchy="false">)</r:mo> <r:mo>></r:mo> <r:mn>20.3</r:mn> </r:mrow> </r:math> and detection significance <w:math xmlns:w="http://www.w3.org/1998/Math/MathML" display="inline"> <w:mi mathvariant="normal">Δ</w:mi> <w:msubsup> <w:mi>χ</w:mi> <w:mi>r</w:mi> <w:mn>2</w:mn> </w:msubsup> <w:mo>></w:mo> <w:mn>0.03</w:mn> </w:math> . We compare the Damped <z:math xmlns:z="http://www.w3.org/1998/Math/MathML" display="inline"> <z:mrow> <z:mi>Ly</z:mi> <z:mi>α</z:mi> </z:mrow> </z:math> Toolkit to two alternative DLA finders based on a convolutional neural network and Gaussian process models. We present a strategy for combining these three techniques to produce a high-fidelity DLA catalog from DESI DR2 for the <bb:math xmlns:bb="http://www.w3.org/1998/Math/MathML" display="inline"> <bb:mrow> <bb:mi>Ly</bb:mi> <bb:mi>α</bb:mi> </bb:mrow> </bb:math> forest baryon acoustic oscillation measurement. The combined catalog contains 41 152 candidate DLAs with <db:math xmlns:db="http://www.w3.org/1998/Math/MathML" display="inline"> <db:mrow> <db:msub> <db:mrow> <db:mi>log</db:mi> </db:mrow> <db:mn>10</db:mn> </db:msub> <db:mo stretchy="false">(</db:mo> <db:msub> <db:mrow> <db:mi>N</db:mi> </db:mrow> <db:mrow> <db:mi mathvariant="monospace">HI</db:mi> </db:mrow> </db:msub> <db:mo stretchy="false">)</db:mo> <db:mo>></db:mo> <db:mn>20.3</db:mn> </db:mrow> </db:math> from quasar spectra with <ib:math xmlns:ib="http://www.w3.org/1998/Math/MathML" display="inline"> <ib:mi mathvariant="normal">S</ib:mi> <ib:mo>/</ib:mo> <ib:mrow> <ib:mi mathvariant="normal">N</ib:mi> <ib:mo stretchy="false">></ib:mo> <ib:mn>2</ib:mn> </ib:mrow> </ib:math> . We estimate this sample to be approximately 85% pure and 79% complete when BAL quasars are excluded.
Modelling the impact of quasar redshift errors on the full-shape analysis of correlations in the Lyman-α forest
(Oxford University Press, 2025) C. Gordon; Andrei Cuceu; Andreu Font-Ribera; H. K. Herrera-Alcantar; Jessica Nicole Aguilar Steven Ahlen; D. Bianchi; David H. Brooks; T. Claybaugh; Shaun Cole; Axel de la Macorra
ABSTRACT In preparation for the first cosmological measurements from the full shape of the Lyman-$\alpha$ (Ly $\alpha$) forest from Dark Energy Spectroscopic Instrument (DESI), we must carefully model all relevant systematics that might bias our analysis. It has been shown that random quasar redshift errors produce a smoothing effect on the mean quasar continuum in the Ly $\alpha$ forest region. This, in turn, gives rise to spurious features in the Ly $\alpha$ autocorrelation and its cross-correlation with quasars. Using synthetic data sets based on the DESI survey, we confirm that the impact on baryon acoustic oscillation measurements is small, but that a bias is introduced to parameters which depend on the full shape of our correlations. We combine a model of this contamination in the cross-correlation with a new model we introduce here for the autocorrelation. These are parametrized by three parameters, which, when included in a joint fit to both correlation functions, successfully eliminate any impact of redshift errors on our full-shape constraints. We also present a strategy for removing this contamination from real data, by removing $\sim$0.3 per cent of correlating pairs.