24 research outputs found
The Early Data Release of the Dark Energy Spectroscopic Instrument
\ua9 2024. The Author(s). Published by the American Astronomical Society. The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra
The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019
The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019
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DESI 2024 II: sample definitions, characteristics, and two-point clustering statistics
Abstract:
We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include matched sets of synthetic reference `randoms' and weights that account for variations in the observed density of the samples due to experimental design and varying instrument performance. We detail how we correct for variations in observational completeness, the input `target' densities due to imaging systematics, and the ability to confidently measure redshifts from DESI spectra. We then summarize how remaining uncertainties in the corrections can be translated to systematic uncertainties for particular analyses.
We describe the weights added to maximize the signal-to-noise of DESI DR1 2-point clustering measurements.
We detail measurement pipelines applied to the LSS catalogs that obtain 2-point clustering measurements in configuration and Fourier space.
The resulting 2-point measurements depend on window functions and normalization constraints particular to each sample, and we present the corrections required to match models to the data.
We compare the configuration- and Fourier-space 2-point clustering of the data samples to that recovered from simulations of DESI DR1 and find they are, generally, in statistical agreement to within 2% in the inferred real-space over-density field.
The LSS catalogs, 2-point measurements, and their covariance matrices will be released publicly with DESI DR1
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Characterization of DESI fiber assignment incompleteness effect on 2-point clustering and mitigation methods for DR1 analysis
We present an in-depth analysis of the fiber assignment incompleteness in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). This incompleteness is caused by the restricted mobility of the robotic fiber positioner in the DESI focal plane, which limits the number of galaxies that can be observed at the same time, especially at small angular separations. As a result, the observed clustering amplitude is suppressed in a scale-dependent manner, which, if not addressed, can severely impact the inference of cosmological parameters. We discuss the methods adopted for simulating fiber assignment on mocks and data. In particular, we introduce the fast fiber assignment (FFA) emulator, which was employed to obtain the power spectrum covariance adopted for the DR1 full-shape analysis. We present the mitigation techniques, organised in two classes: measurement stage and model stage. We then use high fidelity mocks as a reference to quantify both the accuracy of the FFA emulator and the effectiveness of the different measurement-stage mitigation techniques. This complements the studies conducted in a parallel paper for the model-stage techniques, namely the θ-cut approach. We find that pairwise inverse probability (PIP) weights with angular upweighting recover the “true” clustering in all the cases considered, in both Fourier and configuration space. Notably, we present the first ever power spectrum measurement with PIP weights from real data
Validating the Galaxy and Quasar Catalog-Level Blinding Scheme for the DESI 2024 analysis
International audienceIn the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount -- a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks, as well as on data by applying a second blinding layer to perform a battery of sanity checks. We find that the blinding strategy alters the data vector in a controlled way such that the BAO and RSD analysis choices do not need any modification before and after unblinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys
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Production of alternate realizations of DESI fiber assignment for unbiased clustering measurement in data and simulations
A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them. In SDSS this manifested solely as the collision of physical fibers and plugs placed in plates. In DESI, there is the additional constraint of the robotic positioner which controls each fiber being limited to a finite patrol radius. A number of approximate methods have previously been proposed to correct the galaxy clustering statistics for these effects, but these generally fail on small scales. To accurately correct the clustering we need to upweight pairs of galaxies based on the inverse probability that those pairs would be observed (Bianchi & Percival 2017). This paper details an implementation of that method to correct the Dark Energy Spectroscopic Instrument (DESI) survey for incompleteness. To calculate the required probabilities, we need a set of alternate realizations of DESI where we vary the relative priority of otherwise identical targets. These realizations take the form of alternate Merged Target Ledgers (AMTL), the files that link DESI observations and targets. We present the method used to generate these alternate realizations and how they are tracked forward in time using the real observational record and hardware status, propagating the survey as though the alternate orderings had been adopted. We detail the first applications of this method to the DESI One-Percent Survey (SV3) and the DESI year 1 data. We include evaluations of the pipeline outputs, estimation of survey completeness from this and other methods, and validation of the method using mock galaxy catalogs.</p
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DESI 2024 VI: cosmological constraints from the measurements of baryon acoustic oscillations
Abstract:
We present cosmological results from the measurement of baryon acoustic oscillations (BAO)
in galaxy, quasar and Lyman-α forest tracers from the first year of observations from the
Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO
provide robust measurements of the transverse comoving distance and Hubble rate, or their
combination, relative to the sound horizon, in seven redshift bins from over 6 million
extragalactic objects in the redshift range 0.1 < z < 4.2. To mitigate confirmation bias, a blind
analysis was implemented to measure the BAO scales. DESI BAO data alone are consistent with the
standard flat ΛCDM cosmological model with a matter density Ωm=0.295±0.015. Paired with a
baryon density prior from Big Bang Nucleosynthesis and the robustly measured acoustic angular
scale from the cosmic microwave background (CMB), DESI requires H
0=(68.52±0.62) km s-1 Mpc-1. In
conjunction with CMB anisotropies from Planck and CMB lensing data from Planck and ACT, we
find Ωm=0.307± 0.005 and H
0=(67.97±0.38) km s-1 Mpc-1. Extending the baseline model with a
constant dark energy equation of state parameter w, DESI BAO alone require
w=-0.99+0.15
-0.13. In models with a time-varying dark energy equation of state
parametrised by w
0 and wa
, combinations of DESI with CMB or with type Ia supernovae (SN Ia)
individually prefer w
0 > -1 and wa
< 0. This preference is 2.6σ for the DESI+CMB
combination, and persists or grows when SN Ia are added in, giving results discrepant with the
ΛCDM model at the 2.5σ, 3.5σ or 3.9σ levels for the addition of the
Pantheon+, Union3, or DES-SN5YR supernova datasets respectively. For the flat ΛCDM model with
the sum of neutrino mass ∑ mν
free, combining the DESI and CMB data yields an upper limit
∑ mν
< 0.072 (0.113) eV at 95% confidence for a ∑ mν
> 0 (∑ mν
> 0.059) eV
prior. These neutrino-mass constraints are substantially relaxed if the background dynamics are
allowed to deviate from flat ΛCDM
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DESI 2024 V: Full-Shape galaxy clustering from galaxies and quasars
We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range 0.1 < z < 2.1 divided into six redshift bins over a ∼ 7,500 square degree footprint, from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). By fitting the full power spectrum, we extend previous DESI DR1 baryon acoustic oscillation (BAO) measurements to include redshift-space distortions and signals from the matter-radiation equality scale. For the first time, this Full-Shape analysis is blinded at the catalogue-level to avoid confirmation bias and the systematic errors are accounted for at the two-point clustering level, which automatically propagates them into any cosmological parameter. When analysing the data in terms of compressed model-agnostic variables, we obtain a combined precision of 4.7% on the amplitude of the redshift space distortion (RSD) signal reaching a similar precision with just one year of DESI data than with twenty years of observation from the previous generation survey. We also analyse the data to directly constrain the cosmological parameters within the ΛCDM model using perturbation theory and combine this information with the reconstructed DESI DR1 galaxy BAO. Using a Big Bang Nucleosynthesis Gaussian prior on the baryon density parameter, ωb , and a weak Gaussian prior on the spectral index, ns , we constrain the matter density is Ω m = 0.296±0.010 and the Hubble constant H 0 = (68.63 ± 0.79)[km s-1Mpc-1]. Additionally, we measure the amplitude of clustering σ 8 = 0.841±0.034. The DESI DR1 galaxy clustering results are in agreement with the ΛCDM model based on general relativity with parameters consistent with those from Planck. The cosmological interpretation of these results in combination with DESI DR1 Ly-α forest data and external datasets are presented in the companion paper [1]
