Michael Schubnell

We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10−3 (2.6σ) using third-order map moments and p = 3 × 10−11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify …

FitCov estimates the covariance of two-point correlation functions in a way that requires fewer mocks than the standard mock-based covariance. Rather than using an analytically fixed correction to some terms that enter the jackknife covariance matrix, the code fits the correction to a mock-based covariance obtained from a small number of mocks. The fitted jackknife covariance remains unbiased, an improvement over other methods, performs well both in terms of precision (unbiased constraints) and accuracy (similar uncertainties), and requires significant less computational power. In addition, FitCov can be easily implemented on top of the standard jackknife covariance computation.

In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within \texttt{velocileptors} modeling pipeline when fitting mock data from the \texttt{AbacusSummit} N-body simulations. We compare the constraints obtained from parameter compression methods to the direct fitting (Full-Modeling) approaches of modeling the galaxy power spectra, and show that the ShapeFit extension to the traditional template method is consistent with the Full-Modeling method within the standard CDM parameter space. We show the dependence on scale cuts when fitting the different redshift bins using the ShapeFit and Full-Modeling methods. We test the ability to jointly fit data from multiple redshift bins as well as joint analysis of the pre-reconstruction power spectrum with the post-reconstruction BAO correlation function signal. We further demonstrate the behavior of the model when opening up the parameter space beyond CDM and also when combining likelihoods with external datasets, namely the Planck CMB priors. Finally, we describe different parametrization options for the galaxy bias, counterterm, and stochastic parameters, and employ the halo model in order to physically motivate suitable priors that are necessary to ensure the stability of the perturbation theory.

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 probabilitites, 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 …

In this paper we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y6 data. The definition is based on a color and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.6, while ensuring a high-quality photo- determination. The optimization is performed using a Fisher forecast algorithm, finding the optimal -magnitude cut to be given by <19.64+2.894. For the optimal sample, we forecast an increase in precision in the BAO measurement of 25% with respect to the Y3 analysis. Our BAO sample has a total of 15,937,556 galaxies in the redshift range 0.6<<1.2, and its angular mask covers 4,273.42 deg to a depth of =22.5. We validate its redshift distributions with three different methods: directional neighborhood fitting algorithm (DNF), which is our primary photo- estimation; direct calibration with spectroscopic redshifts from VIPERS; and clustering redshift using SDSS galaxies. The fiducial redshift distribution is a combination of these three techniques performed by modifying the mean and width of the DNF distributions to match those of VIPERS and clustering redshift. In this paper we also describe the methodology used to mitigate the effect of observational systematics, which is analogous to the one used in the Y3 analysis. This paper is one of the two dedicated to the analysis of the BAO signal in DES Y6. In its companion paper, we present the angular diameter distance constraints obtained through the fitting to the BAO scale.

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman- (Ly) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over Ly forest spectra and their correlation with the spatial distribution of more than quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon (), we measure the expansion at with 2\% precision, km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters.

In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at 0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters and between every pair of HOD models. We do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3 detection of HOD systematic for in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3 detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in for both Fourier and configuration spaces; and of 0.09% in for Fourier space.

In 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.

We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being a SN Ia, we find 1635 DES SN in the redshift range that pass quality selection criteria and can be used to constrain cosmological parameters. This quintuples the number of high-quality SNe compared to the previous leading compilation of Pantheon+, and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints we combine the DES supernova data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning . Using SN data alone and including systematic uncertainties we find in a flat CDM model, and in a flat CDM model. For a flat CDM model, we find $(\Omega_{\rm M},w_0,w_a)=(0.495^{+0.033}_{-0.043},-0.36^{+0.36}_{-0.30},-8.8^{+3.7}_{-4.5})$, consistent with a constant equation of state to within . Including Planck CMB data, SDSS BAO data, and DES -point data gives . In all cases dark energy is consistent with a cosmological constant to within . In our analysis, systematic errors on …

Extremely metal-poor galaxies (XMPGs) at relatively low redshift are excellent laboratories for studying galaxy formation and evolution in the early universe. Much effort has been spent on identifying them from large-scale spectroscopic surveys or spectroscopic follow-up observations. Previous work has identified a few hundred XMPGs. In this work, we obtain a large sample of 223 XMPGs at z< 1 from the early data of the Dark Energy Spectroscopic Instrument (DESI). The oxygen abundance is determined using the direct T e method based on the detection of the [O iii] λ4363 line. The sample includes 95 confirmed XMPGs based on the oxygen abundance uncertainty; the remaining 128 galaxies are regarded as XMPG candidates. These XMPGs are only 0.01% of the total DESI observed galaxies. Their coordinates and other properties are provided in the paper. The most XMPGs have an oxygen abundance of∼ 1 …

The Dark Energy Spectroscopic Instrument (DESI) cosmology survey includes a Bright Galaxy Survey (BGS) which will yield spectra for over ten million bright galaxies (r<20.2 AB mag). The resulting sample will be valuable for both cosmological and astrophysical studies. However, the star/galaxy separation criterion implemented in the nominal BGS target selection algorithm excludes quasar host galaxies in addition to bona fide stars. While this excluded population is comparatively rare (~3-4 per square degrees), it may hold interesting clues regarding galaxy and quasar physics. Therefore, we present a target selection strategy that was implemented to recover these missing active galactic nuclei (AGN) from the BGS sample. The design of the selection criteria was both motivated and confirmed using spectroscopy. The resulting BGS-AGN sample is uniformly distributed over the entire DESI footprint. According to DESI survey validation data, the sample comprises 93% quasi-stellar objects (QSOs), 3% narrow-line AGN or blazars with a galaxy contamination rate of 2% and a stellar contamination rate of 2%. Peaking around redshift z=0.5, the BGS-AGN sample is intermediary between quasars from the rest of the BGS and those from the DESI QSO sample in terms of redshifts and AGN luminosities. The stacked spectrum is nearly identical to that of the DESI QSO targets, confirming that the sample is dominated by quasars. We highlight interesting small populations reaching z>2 which are either faint quasars with nearby projected companions or very bright quasars with strong absorption features including the Lyman-apha forest, metal absorbers …

We present the angular diameter distance measurement obtained with the Baryonic Acoustic Oscillation feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6<<1.2, with an effective redshift at =0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to = 19.510.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by Planck CDM via the BAO shift parameter . To achieve this, the BAO shift is measured with three different methods, Angular Correlation Function (ACF), Angular Power Spectrum (APS), and Projected Correlation Function (PCF) obtaining 0.9520.023, 0.9620.022, and 0.9550.020, respectively, which we combine to 0.9570.020, including systematic errors. When compared with the CDM model that best fits Planck data, this measurement is found to be 4.3% and 2.1 below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at >0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position and it is shown to be robust against analysis choices, data removal, redshift calibrations and observational systematics.

We estimate the redshift-dependent, anisotropic clustering signal in the Dark Energy Spectroscopic Instrument (DESI) Year 1 Survey created by tidal alignments of Luminous Red Galaxies (LRGs) and a selection-induced galaxy orientation bias. To this end, we measured the correlation between LRG shapes and the tidal field with DESI’s Year 1 redshifts, as traced by LRGs and Emission-Line Galaxies. We also estimate the galaxy orientation bias of LRGs caused by DESI’s aperture-based selection, and find it to increase by a factor of seven between redshifts 0.4−1.1 due to redder, fainter galaxies falling closer to DESI’s imaging selection cuts. These effects combine to dampen measurements of the quadrupole of the correlation function (ξ2) caused by structure growth on scales of 10–80 h−1 Mpc by about 0.15 per cent for low redshifts (0.4 < z < 0.6) and 0.8 per cent for high (0.8 < z < 1.1), a significant …

The large-scale structure of the Universe that we recognize today under the form of groups and clusters of galaxies, filaments, sheets, and voids is the result of gravitational instability of small density fluctuations generated at very early times. The statistical properties of these seeds are still unclear. More importantly, the nature of the physical mechanisms responsible for their generation is beyond the grasp of modern physics. Within the standard cosmological model, the inflationary paradigm is taken as the most successful and plausible scenario for the production of the primordial density field. Nevertheless, also within the numerous inflationary theories, current astronomical observations do not allow to select a preferable model. In the last few years, the study and quantification of primordial non-Gaussian signals have emerged as the most powerful tool to test and discriminate among competing scenarios for the generation of the primordial density fluctuations.In general, departure of the statistical distribution of the matter density perturbations from a perfect Gaussian can happen because of fundamental physical mechanisms in the primordial Universe, because of non-linear gravitational evolution, and/or because of astrophysical processes acting at later times. The distribution of matter in the Universe at low redshift, result of the non-linear gravitational growth of structure, is highly non-Gaussian even for perfectly-Gaussian initial conditions. The effect of a possible primordial non-Gaussianity could thus be seen as an additional component. To understand and disentangle those different contributions is a challenge which involves an increasingly …

DESI aims to provide one of the tightest constraints on cosmological parameters by analyzing the clustering of more than thirty million galaxies. However, obtaining such constraints requires special care in validating the analysis methods, and efforts to reduce the computational time required through techniques such as data compression and emulation. In this work, we perform a precision validation of the PyBird power spectrum modelling code with both a traditional, but emulated, Full-Modelling approach and the model-independent Shapefit compression approach. Using cubic simulations, which accurately reproduce the clustering and precision of the DESI survey, we find that the cosmological constraints from Shapefit and Full-Modelling are consistent with each other at the level. Both Shapefit and Full-Modelling are also consistent with the true CDM simulation cosmology, even when including the hexadecapole, down to a scale . For extended models such as the CDM and the CDM models, we find including the hexadecapole can significantly improve the constraints and reduce the systematic errors with the same . Furthermore, we also show that the constraints on cosmological parameters with the correlation function evaluated from PyBird down to are unbiased, and consistent with the constraints from the power spectrum.

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation used in the mocks. Importantly, we find a close agreement (<~ 5% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, in particular, relevant to the broad current and future analyses of DESI data.

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman- 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 . DESI BAO data alone are consistent with the standard flat CDM cosmological model with a matter density . Paired with a BBN prior and the robustly measured acoustic angular scale from the CMB, DESI requires km/s/Mpc. In conjunction with CMB anisotropies from Planck and CMB lensing data from Planck and ACT, we find and km/s/Mpc. Extending the baseline model with a constant dark energy equation of state parameter , DESI BAO alone require . In models with a time-varying dark energy equation of state parametrized by and , combinations of DESI with CMB or with SN~Ia individually prefer and . This preference is 2.6 for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the CDM model at the , or levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat CDM model with the sum of neutrino mass free, combining the DESI and CMB data yields an upper limit eV at 95% confidence for a  …

Cosmological analyses of samples of photometrically identified type Ia supernovae (SNe Ia) depend on understanding the effects of ‘contamination’ from core-collapse and peculiar SN Ia events. We employ a rigorous analysis using the photometric classifier SuperNNova on state-of-the-art simulations of SN samples to determine cosmological biases due to such ‘non-Ia’ contamination in the Dark Energy Survey (DES) 5-yr SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8 to 3.5 per cent, with a classification efficiency of 97.7–99.5 per cent. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension BBC (‘BEAMS with Bias Correction’), we produce a redshift-binned Hubble diagram marginalized over contamination and corrected for selection effects, and use it to constrain the dark …

Cosmological analyses using galaxy clusters in optical/NIR photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for {\it all} galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89\% membership accuracy with a mild dependency on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass--cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities () as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation. These results indicate the potential of Copacabana and to be used in cosmological analyses of optically selected clusters in the future.

We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the non-recurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines consistent with power law decay. The remaining two objects had been classified as active galactic nuclei (AGN) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up …