Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). We run the pipeline on multiple effective Zel'dovich (EZ) mock galaxy catalogs with the corresponding cuts applied and compare the results with the mock sample covariance to assess the accuracy and its fluctuations. We propose an extension of the previously developed formalism for catalogs processed with standard reconstruction algorithms. We consider methods for comparing covariance matrices in detail, highlighting their interpretation and statistical properties caused by sample variance, in particular, non-trivial expectation values of certain metrics even when the external covariance estimate is perfect. With improved mocks and validation techniques, we confirm a good agreement between our predictions and sample covariance. This allows one to generate covariance matrices for comparable data sets without the need to create numerous mock galaxy catalogs with matching clustering, only requiring 2PCF measurements from the data itself. The code used in this paper is publicly available at https://github.com/oliverphilcox/RascalC

A principal factor analysis to characterize agricultural exposures among Nebraska veterans

Agricultural workers are at an increased risk of developing chronic respiratory disorders. Accurate estimation of long-term agricultural exposures based on questionnaires has been used to improve the validity of epidemiologic investigations and subsequent evaluation of the association between agricultural exposures and chronic diseases. Our aim was to use principal factor analysis (PFA) to distill exposure data into essential variables characterizing long-term agricultural exposures. This is a crosssectional study of veterans between the ages of 40 and 80 years and who worked on a farm for ≥ 2 years. Participant characteristics were: 98.1% were white males with a mean age 65 ± 8 (SD) years and 39.8% had chronic obstructive pulmonary disease. The final model included four factors and explained 16.6% of the variance in the exposure data. Factor 1 was a heterogeneous factor; however, Factor 2 was exclusively composed of exposure to livestock such as hogs, dairy and poultry. Factor 3 included exposures from jobs on or off the farm such as wood dust, mineral dust, asbestos and spray paint. Crop exposure loaded exclusively in Factor 4 and included lifetime hours of exposure and maximum number of acres farmed in the participants’ lifetime. The factors in the final model were interpretable and consistent with farming practices

Fiducial-Cosmology-dependent systematics for the DESI 2024 BAO Analysis

When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorithm. A parameterised template for the model to be fitted is also created based on a (possibly different) fiducial cosmology. This model reliance can be considered a form of data compression, and the data is then analysed allowing that the true answer is different from the fiducial cosmology assumed. In this study, we evaluate the impact of the fiducial cosmology assumed in the BAO analysis of the Dark Energy Spectroscopic Instrument (DESI) survey Data Release 1 (DR1) on the final measurements in DESI 2024 III. We utilise a suite of mock galaxy catalogues with survey realism that mirrors the DESI DR1 tracers: the bright galaxy sample (BGS), the luminous red galaxies (LRG), the emission line galaxies (ELG) and the quasars (QSO), spanning a redshift range from 0.1 to 2.1. We compare the four secondary AbacusSummit cosmologies against DESI's fiducial cosmology (Planck 2018). The secondary cosmologies explored include a lower cold dark matter density, a thawing dark energy universe, a higher number of effective species, and a lower amplitude of matter clustering. The mocks are processed through the BAO pipeline by consistently iterating the grid, template, and reconstruction reference cosmologies. We determine a conservative systematic contribution to the error of $0.1\%$ for both the isotropic and anisotropic dilation parameters $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$. We then directly test the impact of the fiducial cosmology on DESI DR1 data.Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasar

Optimal Reconstruction of Baryon Acoustic Oscillations for DESI 2024

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs.Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasar

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg$^2$ over five years to constrain the cosmic expansion history through precise measurements of Baryon Acoustic Oscillations (BAO). The scientific program for DESI was evaluated during a five month Survey Validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar (MWS), bright galaxy (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the five-year program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a `One-Percent survey' conducted at the conclusion of Survey Validation covering 140 deg$^2$ using the final target selection algorithms with exposures of a depth typical of the main survey. The Survey Validation indicates that DESI will be able to complete the full 14,000 deg$^2$ program with spectroscopically-confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval $z<1.1$, 0.39% over the redshift interval $1.1<z<1.9$, and 0.46% over the redshift interval $1.9<z<3.5$.Comment: 42 pages, 18 figures, accepted by A

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 Construction of Large-scale Structure Catalogs for the Dark Energy Spectroscopic Instrument

We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random\u27 catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes.Accepted (by JCAP) version of supporting publication of DESI 2024II: Sample definitions, characteristics, and two-point clustering statistic

The Beacon Collaborative: A Journey to Excellence

TOPIC The development of the Critical Care Beacon Collaborative to achieve meaningful recognition. CLINICAL RELEVANCE Recognizing nurses for contributions to their work environment and care delivery is important for their professional and personal fulfillment, job satisfaction, and retention; such recognition can occur at the individual, unit, or organizational level. The American Nurses Credentialing Center’s Magnet Recognition Program acknowledges nursing excellence at the organizational level. It would, however, be difficult for an organization to achieve Magnet designation without nursing excellence at the unit level. To recognize excellence at the unit level, the American Association of Critical-Care Nurses developed the Beacon Award in 2003. OBJECTIVE To describe one academic medical center’s journey toward winning Beacon Awards across 8 units within the adult critical care service. CONTENT COVERED The Critical Care Beacon Collaborative resulted in a Beacon Award for each unit and important staff outcomes. This article describes the organization, the process before the Critical Care Beacon Collaborative convened and the desired state, and the methods used to achieve our goal. It also discusses unit- and service-level stakeholder involvement. The successes, lessons learned, sustainability, and growth of the Critical Care Beacon Collaborative are shared to assist readers who aspire to pursue a Beacon Award. (Critical Care Nurse. 2021;41[5]:e17-e25

The Beacon Collaborative: A Journey to Excellence

Topic The development of the Critical Care Beacon Collaborative to achieve meaningful recognition. Clinical Relevance Recognizing nurses for contributions to their work environment and care delivery is important for their professional and personal fulfillment, job satisfaction, and retention; such recognition can occur at the individual, unit, or organizational level. The American Nurses Credentialing Center’s Magnet Recognition Program acknowledges nursing excellence at the organizational level. It would, however, be difficult for an organization to achieve Magnet designation without nursing excellence at the unit level. To recognize excellence at the unit level, the American Association of Critical-Care Nurses developed the Beacon Award in 2003. Objective To describe one academic medical center’s journey toward winning Beacon Awards across 8 units within the adult critical care service. Content Covered The Critical Care Beacon Collaborative resulted in a Beacon Award for each unit and important staff outcomes. This article describes the organization, the process before the Critical Care Beacon Collaborative convened and the desired state, and the methods used to achieve our goal. It also discusses unit- and service-level stakeholder involvement. The successes, lessons learned, sustainability, and growth of the Critical Care Beacon Collaborative are shared to assist readers who aspire to pursue a Beacon Award. </jats:sec

The Molecular Circadian Clock and Alcohol-Induced Liver Injury

Emerging evidence from both experimental animal studies and clinical human investigations demonstrates strong connections among circadian processes, alcohol use, and alcohol-induced tissue injury. Components of the circadian clock have been shown to influence the pathophysiological effects of alcohol. Conversely, alcohol may alter the expression of circadian clock genes and the rhythmic behavioral and metabolic processes they regulate. Therefore, we propose that alcohol-mediated disruption in circadian rhythms likely underpins many adverse health effects of alcohol that cut across multiple organ systems. In this review, we provide an overview of the circadian clock mechanism and showcase results from new studies in the alcohol field implicating the circadian clock as a key target of alcohol action and toxicity in the liver. We discuss various molecular events through which alcohol may work to negatively impact circadian clock-mediated processes in the liver, and contribute to tissue pathology. Illuminating the mechanistic connections between the circadian clock and alcohol will be critical to the development of new preventative and pharmacological treatments for alcohol use disorders and alcohol-mediated organ diseases