Engineering topics

Swanson, M. E.C.

Publications and source records attributed to Swanson, M. E.C..

9 records

DOE OSTI2024

Dark Energy Survey Year 3: Blue Shear

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this blue cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the $\Omega_{m}$ and $S_8$ better agree with the cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The gravitational lensing imprints of DES Y3 superstructures on the CMB: a matched filtering approach

Low-density cosmic voids gravitationally lens the cosmic microwave background (CMB), leaving a negative imprint on the CMB convergence |$\kappa$|⁠. This effect provides insight into the distribution of matter within voids, and can also be used to study the growth of structure. We measure this lensing imprint by cross-correlating the Planck CMB lensing convergence map with voids identified in the Dark Energy Survey Year 3 (DES Y3) data set, covering approximately 4200 deg|$^2$| of the sky. We use two distinct void-finding algorithms: a 2D void-finder that operates on the projected galaxy density field in thin redshift shells, and a new code, Voxel, which operates on the full 3D map of galaxy positions. We employ an optimal matched filtering method for cross-correlation, using the Marenostrum Institut de Ciències de l’Espai N-body simulation both to establish the template for the matched filter and to calibrate detection significances. Using the DES Y3 photometric luminous red galaxy sample, we measure |$A_\kappa$|⁠, the amplitude of the observed lensing signal relative to the simulation template, obtaining |$A_\kappa = 1.03 \pm 0.22$| (⁠|$4.6\sigma$| significance) for Voxel and |$A_\kappa = 1.02 \pm 0.17$| (⁠|$5.9\sigma$| significance) for 2D voids, both consistent with Lambda cold dark matter expectations. We additionally invert the 2D void-finding process to identify superclusters in the projected density field, for which we measure |$A_\kappa = 0.87 \pm 0.15$| (⁠|$5.9\sigma$| significance). The leading source of noise in our measurements is Planck noise, implying that data from the Atacama Cosmology Telescope, South Pole Telescope and CMB-S4 will increase sensitivity and allow for more precise measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dark Energy Survey: Galaxy sample for the baryonic acoustic oscillation measurement from the final dataset

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- z determination. The optimization is performed using a Fisher forecast algorithm, finding the optimal i -magnitude cut to be given by i < 19.64 + 2.894 z ph . 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 < z ph < 1.2 , and its angular mask covers 4 , 273.42 deg 2 to a depth of i = 22.5 . We validate its redshift distributions with three different methods: directional neighborhood fitting algorithm (DNF), which is our primary photo- z estimation; direct calibration with spectroscopic redshifts from VIPERS, which is a spectroscopic galaxy sample that overlaps with our BAO sample and is complete within our selection cuts; 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The dark energy survey supernova program: investigating beyond-ΛCDM

We report constraints on a variety of non-standard cosmological models using the full 5-yr photometrically classified type Ia supernova sample from the Dark Energy Survey (DES-SN5YR). Both Akaike Information Criterion (AIC) and Suspiciousness calculations find no strong evidence for or against any of the non-standard models we explore. When combined with external probes, the AIC and Suspiciousness agree that 11 of the 15 models are moderately preferred over Flat-|$\Lambda$|CDM suggesting additional flexibility in our cosmological models may be required beyond the cosmological constant. We also provide a detailed discussion of all cosmological assumptions that appear in the DES supernova cosmology analyses, evaluate their impact, and provide guidance on using the DES Hubble diagram to test non-standard models. An approximate cosmological model, used to perform bias corrections to the data holds the biggest potential for harbouring cosmological assumptions. We show that even if the approximate cosmological model is constructed with a matter density shifted by |$\Delta \Omega _{\rm m}\sim 0.2$| from the true matter density of a simulated data set the bias that arises is subdominant to statistical uncertainties. Nevertheless, we present and validate a methodology to reduce this bias.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The dark energy survey: detection of weak lensing magnification of supernovae and constraints on dark matter haloes

The residuals of the distance moduli of Type Ia supernovae (SNe Ia) relative to a Hubble diagram fit contain information about the inhomogeneity of the Universe, due to weak lensing magnification by foreground matter. By correlating the residuals of the Dark Energy Survey Year 5 SN Ia sample (DES-SN5YR) with extragalactic foregrounds from the DES Y3 Gold catalogue, we detect the presence of lensing at |$6.0 \sigma$| significance. This is the first detection with a significance level above |$5\sigma$|⁠. Constraints on the effective mass-to-light ratios and radial profiles of dark matter haloes surrounding individual galaxies are also obtained. We show that the scatter of SNe Ia around the Hubble diagram is reduced by modifying the standardization of the distance moduli to include an easily calculable de-lensing (i.e. environmental) term. We use the de-lensed distance moduli to recompute cosmological parameters derived from SN Ia, finding in Flat wcold dark matter a difference of |$\Delta \Omega _{\rm M} = +0.036$| and |$\Delta w = -0.056$| compared to the unmodified distance moduli, a change of |$\sim 0.3\sigma$|⁠. We argue that our modelling of SN Ia lensing will lower systematics on future surveys with higher statistical power. We use the observed dispersion of lensing in DES-SN5YR to constrain |$\sigma _8$|⁠, but caution that the fit is sensitive to uncertainties at small scales. Nevertheless, our detection of SN Ia lensing opens a new pathway to study matter inhomogeneity that complements galaxy–galaxy lensing surveys and has unrelated systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment

Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches are machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims. The goal of this work is to calculate the photo-zs for the Y3 DES Deep Fields catalogue using the DNF machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained with respect to the EAzY template fitting approach on Y3 DES Deep Fields catalogue. Methods. We have emulated -- at brighter magnitude -- the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We have used a principal component analysis to graphically assess incompleteness and to relate it with the performance parameters provided by DNF. Finally, we have applied the results about the incompleteness to the photo-z computation on Y3 DES Deep Fields with DNF and estimated its performance. Results. The photo-zs for the galaxies on DES Deep Fields have been computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. They are available at https://des.ncsa.illinois.edu/releases/y3a2/Y3deepfields. Some techniques have been developed to evaluate the performance in the absence of "true" redshift and to assess completeness. We have studied... (Partial abstract)

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulationbased analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). Here, we implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $νw$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S 8 , Ω m , and the figure-of-merit FoM S8;Ωm , respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Main belt asteroids taxonomical information from dark energy survey data

While proper orbital elements are currently available for more than 1 million asteroids, taxonomical information is still lagging behind. Surveys like SDSS-MOC4 provided preliminary information for more than 100 000 objects, but many asteroids still lack even a basic taxonomy. In this study, we use Dark Energy Survey (DES) data to provide new information on asteroid physical properties. By cross-correlating the new DES data base with other data bases, we investigate how asteroid taxonomy is reflected in DES data. While the resolution of DES data is not sufficient to distinguish between different asteroid taxonomies within the complexes, except for V-type objects, it can provide information on whether an asteroid belongs to the C- or S-complex. Here, machine learning methods optimized through the use of genetic algorithms were used to predict the labels of more than 68 000 asteroids with no prior taxonomic information. Using a high-quality, limited set of asteroids with data on gri slopes and i − z colours, we detected 409 new possible V-type asteroids. Their orbital distribution is highly consistent with that of other known V-type objects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and weak-lensing measurements need efficient software infrastructure to explore an increasingly large parameter space, and account for various cosmological and astrophysical effects. Our software package is designed to model the cluster observables in a wide-field optical survey, including galaxy cluster counts, their averaged weak-lensing masses, or the cluster's averaged weak-lensing radial signals. To ensure maximum efficiency, this software package is developed in C++ in the CosmoSIS software framework, making use of the CUBA integration library. We also implement a testing and validation scheme to ensure the quality of the package. We demonstrate the effectiveness of this development by applying the software to the Dark Energy Survey Year 1 galaxy cluster cosmological data sets, and acquired cosmological constraints that are consistent with the fiducial Dark Energy Survey analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗