Constraining primordial non-Gaussianity with DESI 2024 LRG and QSO samples
E Chaussidon, C Yèche, A de Mattia, C Payerne… - arXiv preprint arXiv …, 2024 - arxiv.org
E Chaussidon, C Yèche, A de Mattia, C Payerne, P McDonald, AJ Ross, S Ahlen, D Bianchi…
arXiv preprint arXiv:2411.17623, 2024•arxiv.orgWe analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar
(QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument
(DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter $ f_ {\rm
NL}^{\rm loc} $ via the large-scale scale-dependent bias in the power spectrum using
$1,631,716 $ LRGs ($0.6< z< 1.1$) and $1,189,129 $ QSOs ($0.8< z< 3.1$). This new
measurement takes advantage of the enormous statistical power at large scales of DESI …
(QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument
(DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter $ f_ {\rm
NL}^{\rm loc} $ via the large-scale scale-dependent bias in the power spectrum using
$1,631,716 $ LRGs ($0.6< z< 1.1$) and $1,189,129 $ QSOs ($0.8< z< 3.1$). This new
measurement takes advantage of the enormous statistical power at large scales of DESI …
We analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar (QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter via the large-scale scale-dependent bias in the power spectrum using LRGs () and QSOs (). This new measurement takes advantage of the enormous statistical power at large scales of DESI DR1 data, surpassing the latest data release (DR16) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). For the first time in this kind of analysis, we use a blinding procedure to mitigate the risk of confirmation bias in our results. We improve the model of the radial integral constraint proposing an innovative correction of the window function. We also carefully test the mitigation of the dependence of the target selection on the photometry qualities by incorporating an angular integral constraint contribution to the window function, and validate our methodology with the blinded data. Finally, combining the two samples, we measure at confidence, where we assume the universality relation for the LRG sample and a recent merger model for the QSO sample about the response of bias to primordial non-Gaussianity. Adopting the universality relation for the PNG bias in the QSO analysis leads to at confidence. This measurement is the most precise determination of primordial non-Gaussianity using large-scale structure to date, surpassing the latest result from eBOSS by a factor of .
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