arXiv subjects

Jeffrey A. Newman

Publications and source records attributed to Jeffrey A. Newman.

At least 73 records · Page 4Linked to original sources

arXiv2022

A Spectroscopic Road Map for Cosmic Frontier: DESI, DESI-II, Stage-5

In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential.

astro-ph.CO↗

arXiv2022

A Long Time Ago in a Galaxy Far, Far Away: A Candidate z ~ 12 Galaxy in Early JWST CEERS Imaging

We report the discovery of a candidate galaxy with a photo-z of z~12 in the first epoch of the JWST Cosmic Evolution Early Release Science (CEERS) Survey. Following conservative selection criteria we identify a source with a robust z_phot = 11.8^+0.3_-0.2 (1-sigma uncertainty) with m_F200W=27.3, and >7-sigma detections in five filters. The source is not detected at lambda < 1.4um in deep imaging from both HST and JWST, and has faint ~3-sigma detections in JWST F150W and HST F160W, which signal a Ly-alpha break near the red edge of both filters, implying z~12. This object (Maisie's Galaxy) exhibits F115W-F200W > 1.9 mag (2-sigma lower limit) with a blue continuum slope, resulting in 99.6% of the photo-z PDF favoring z > 11. All data quality images show no artifacts at the candidate's position, and independent analyses consistently find a strong preference for z > 11. Its colors are inconsistent with Galactic stars, and it is resolved (r_h = 340 +/- 14 pc). Maisie's Galaxy has log M*/Msol ~ 8.5 and is highly star-forming (log sSFR ~ -8.2 yr^-1), with a blue rest-UV color (beta ~ -2.5) indicating little dust though not extremely low metallicity. While the presence of this source is in tension with most predictions, it agrees with empirical extrapolations assuming UV luminosity functions which smoothly decline with increasing redshift. Should followup spectroscopy validate this redshift, our Universe was already aglow with galaxies less than 400 Myr after the Big Bang.

astro-ph.GA↗

arXiv2022

Photometric Redshifts from SDSS Images with an Interpretable Deep Capsule Network

Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on $ugriz$ images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of $\sim$400,000 Sloan Digital Sky Survey (SDSS) galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets ($r\leq17.8$ and $z_{\mathrm{spec}}\leq0.4$) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a 2-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g., size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g., magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1 .

astro-ph.IM↗

arXiv2022

Target Selection and Validation of DESI Emission Line Galaxies

The Dark Energy Spectroscopic Instrument (DESI) will precisely constrain cosmic expansion and the growth of structure by collecting $\sim$40 million extra-galactic redshifts across $\sim$80\% of cosmic history and one third of the sky. The Emission Line Galaxy (ELG) sample, which will comprise about one-third of all DESI tracers, will be used to probe the Universe over the $0.6 < z < 1.6$ range, which includes the $1.1<z<1.6$ range, expected to provide the tightest constraints. We present the target selection of the DESI SV1 Survey Validation and Main Survey ELG samples, which relies on the Legacy Surveys imaging. The Main ELG selection consists of a $g$-band magnitude cut and a $(g-r)$ vs.\ $(r-z)$ color box, while the SV1 selection explores extensions of the Main selection boundaries. The Main ELG sample is composed of two disjoint subsamples, which have target densities of about 1940 deg$^{-2}$ and 460 deg$^{-2}$, respectively. We first characterize their photometric properties and density variations across the footprint. Then we analyze the DESI spectroscopic data obtained since December 2020 during the Survey Validation and the Main Survey up to December 2021. We establish a preliminary criterion to select reliable redshifts, based on the \oii~flux measurement, and assess its performance. Using that criterion, we are able to present the spectroscopic efficiency of the Main ELG selection, along with its redshift distribution. We thus demonstrate that the the main selection with higher target density sample should provide more than 400 deg$^{-2}$ reliable redshifts in both the $0.6<z<1.1$ and the $1.1<z<1.6$ ranges.

astro-ph.CO↗

arXiv2022

Target Selection and Validation of DESI Quasars

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Explorer (WISE). These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a Random Forest algorithm and selects quasars in the magnitude range 16.5 99% purity for a nominal effective exposure time of ~1000s. With a 310 per sq. deg. target density, the main selection allows DESI to select more than 200 QSOs per sq. deg. (including 60 quasars with z>2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.

astro-ph.CO↗

arXiv2022

Photometric Redshifts for Next-Generation Surveys

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these datasets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photo-$z$'s to the next generation of surveys: - Gains in $performance$ -- i.e., the precision of redshift estimates for individual galaxies -- could greatly enhance studies of galaxy evolution and some probes of cosmology. - Improvements in $characterization$ -- i.e., the accurate recovery of redshift $distributions$ of galaxies in the presence of uncertainty on individual redshifts -- are urgently needed for cosmological measurements with next-generation surveys. - To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts which make high-fidelity photo-$z$'s possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions will need to improve by roughly an order of magnitude compared to the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed.

astro-ph.CO↗

arXiv2022

How well do local relations predict gas-phase metallicity gradients? Results from SDSS-IV MaNGA

Gas-phase metallicity gradients in galaxies provide important clues to those galaxies' formation histories. Using SDSS-IV MaNGA data, we previously demonstrated that gas metallicity gradients vary systematically and significantly across the galaxy mass--size plane: at stellar masses beyond approximately $10^{10}$ $\mathrm{M_\odot}$, more extended galaxies display steeper gradients (in units of $\mathrm{dex/R_e}$) at a given stellar mass. Here, we set out to develop a physical interpretation of these findings by examining the ability of local $\sim$kpc-scale relations to predict the gradient behaviour along the mass--size plane. We find that local stellar mass surface density, when combined with total stellar mass, is sufficient to reproduce the overall mass--size trend in a qualitative sense. We further find that we can improve the predictions by correcting for residual trends relating to the recent star formation histories of star-forming regions. However, we find as well that the most extended galaxies display steeper average gradients than predicted, even after correcting for residual metallicity trends with other local parameters. From these results, we argue that gas-phase metallicity gradients can largely be understood in terms of known local relations, but we also discuss some possible physical causes of discrepant gradients.

astro-ph.GA↗

arXiv2022

Snowmass2021: Opportunities from Cross-survey Analyses of Static Probes

Cosmological data in the next decade will be characterized by high-precision, multi-wavelength measurements of thousands of square degrees of the same patches of sky. By performing multi-survey analyses that harness the correlated nature of these datasets, we will gain access to new science, and increase the precision and robustness of science being pursued by each individual survey. However, effective application of such analyses requires a qualitatively new level of investment in cross-survey infrastructure, including simulations, associated modeling, coordination of data sharing, and survey strategy. The scientific gains from this new level of investment are multiplicative, as the benefits can be reaped by even present-day instruments, and can be applied to new instruments as they come online.

hep-ex↗

arXiv2022

Snowmass2021 Cosmic Frontier White Paper: Enabling Flagship Dark Energy Experiments to Reach their Full Potential

A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data from other telescopes. This white paper focuses in particular on the compelling benefits of ground-based spectroscopic and photometric observations to complement the Vera C. Rubin Observatory, as well as smaller programs in aid of a DESI-2 experiment and CMB-S4. These additional data sets will both improve dark energy constraints from these flagship projects beyond what would possible on their own and open completely new windows into fundamental physics. For example, additional photometry and single-object spectroscopy will provide necessary follow-up information for supernova and strong lensing cosmology, while highly-multiplexed spectroscopy both from smaller facilities over wide fields and from larger facilities over narrower regions of sky will yield more accurate photometric redshift estimates for weak lensing and galaxy clustering measurements from the Rubin Observatory, provide critical spectroscopic host galaxy redshifts for supernova Hubble diagrams, provide improved understanding of limiting astrophysical systematic effects, and enable new measurements that probe the nature of gravity. A common thread is that access to complementary data from a range of telescopes/instruments would have a substantial impact on the rate of advance of dark energy science in the coming years.

astro-ph.CO↗

arXiv2022

Snowmass2021 Cosmic Frontier White Paper: Rubin Observatory after LSST

The Vera C. Rubin Observatory will begin the Legacy Survey of Space and Time (LSST) in 2024, spanning an area of 18,000 square degrees in six bands, with more than 800 observations of each field over ten years. The unprecedented data set will enable great advances in the study of the formation and evolution of structure and exploration of physics of the dark universe. The observations will hold clues about the cause for the accelerated expansion of the universe and possibly the nature of dark matter. During the next decade, LSST will be able to confirm or dispute if tensions seen today in cosmological data are due to new physics. New and unexpected phenomena could confirm or disrupt our current understanding of the universe. Findings from LSST will guide the path forward post-LSST. The Rubin Observatory will still be a uniquely powerful facility even then, capable of revealing further insights into the physics of the dark universe. These could be obtained via innovative observing strategies, e.g., targeting new probes at shorter timescales than with LSST, or via modest instrumental changes, e.g., new filters, or through an entirely new instrument for the focal plane. This White Paper highlights some of the opportunities in each scenario from Rubin observations after LSST.

astro-ph.CO↗

arXiv2022

Re-calibrating Photometric Redshift Probability Distributions Using Feature-space Regression

Many astrophysical analyses depend on estimates of redshifts (a proxy for distance) determined from photometric (i.e., imaging) data alone. Inaccurate estimates of photometric redshift uncertainties can result in large systematic errors. However, probability distribution outputs from many photometric redshift methods do not follow the frequentist definition of a Probability Density Function (PDF) for redshift -- i.e., the fraction of times the true redshift falls between two limits $z_{1}$ and $z_{2}$ should be equal to the integral of the PDF between these limits. Previous works have used the global distribution of Probability Integral Transform (PIT) values to re-calibrate PDFs, but offsetting inaccuracies in different regions of feature space can conspire to limit the efficacy of the method. We leverage a recently developed regression technique that characterizes the local PIT distribution at any location in feature space to perform a local re-calibration of photometric redshift PDFs. Though we focus on an example from astrophysics, our method can produce PDFs which are calibrated at all locations in feature space for any use case.

astro-ph.IM↗

arXiv2022

Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era

Large simulation efforts are required to provide synthetic galaxy catalogs for ongoing and upcoming cosmology surveys. These extragalactic catalogs are being used for many diverse purposes covering a wide range of scientific topics. In order to be useful, they must offer realistically complex information about the galaxies they contain. Hence, it is critical to implement a rigorous validation procedure that ensures that the simulated galaxy properties faithfully capture observations and delivers an assessment of the level of realism attained by the catalog. We present here a suite of validation tests that have been developed by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). We discuss how the inclusion of each test is driven by the scientific targets for static ground-based dark energy science and by the availability of suitable validation data. The validation criteria that are used to assess the performance of a catalog are flexible and depend on the science goals. We illustrate the utility of this suite by showing examples for the validation of cosmoDC2, the extragalactic catalog recently released for the LSST DESC second Data Challenge.

astro-ph.CO↗

arXiv2022

Angular clustering properties of the DESI QSO target selection using DR9 Legacy Imaging Surveys

The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next five years. The aim of this work is to validate the quasar selection by studying the impact of imaging systematics as well as stellar and galactic contaminants, and to develop a procedure to mitigate them. Density fluctuations of quasar targets are found to be related to photometric properties such as seeing and depth of the Data Release 9 of the DESI Legacy Imaging Surveys. To model this complex relation, we explore machine learning algorithms (Random Forest and Multi-Layer Perceptron) as an alternative to the standard linear regression. Splitting the footprint of the Legacy Imaging Surveys into three regions according to photometric properties, we perform an independent analysis in each region, validating our method using eBOSS EZ-mocks. The mitigation procedure is tested by comparing the angular correlation of the corrected target selection on each photometric region to the angular correlation function obtained using quasars from the Sloan Digital Sky Survey (SDSS)Data Release 16. With our procedure, we recover a similar level of correlation between DESI quasar targets and SDSS quasars in two thirds of the total footprint and we show that the excess of correlation in the remaining area is due to a stellar contamination which should be removed with DESI spectroscopic data. We derive the Limber parameters in our three imaging regions and compare them to previous measurements from SDSS and the 2dF QSO Redshift Survey.

astro-ph.CO↗

arXiv2021

CLIMBER: Galaxy-Halo Connection Constraints from Next-Generation Surveys

In the coming decade, a new generation of massively multiplexed spectroscopic surveys, such as PFS, WAVES, and MOONS, will probe galaxies in the distant universe in vastly greater numbers than was previously possible. In this work, we generate mock catalogs for each of these three planned surveys to help quantify and optimize their scientific output. To assign photometry into the UniverseMachine empirical model, we develop the Calibrating Light: Illuminating Mocks By Empirical Relations (CLIMBER) procedure using UltraVISTA photometry. Using the published empirical selection functions for each aforementioned survey, we quantify the mass completeness of each survey. We compare different targeting strategies by varying the area and targeting completeness, and quantify how these survey parameters affect the uncertainty of the two-point correlation function. We demonstrate that the PFS and MOONS measurements will be primarily dominated by cosmic variance, not shot noise, motivating the need for increasingly large survey areas. On the other hand, the WAVES survey, which covers a much larger area, will strike a good balance between cosmic variance and shot noise. For a fixed number of targets, a 5% increased survey area (and $\sim$5% decreased completeness) would decrease the uncertainty of the correlation function at intermediate scales by 0.15%, 1.2%, and 1.1% for our WAVES, PFS, and MOONS samples, respectively. Meanwhile, for a fixed survey area, 5% increased targeting completeness improves the same constraints by 0.7%, 0.25%, and 0.1%. All of the utilities used to construct our mock catalogs and many of the catalogs themselves are publicly available.

astro-ph.CO↗

arXiv2021

Constraining the Milky Way's Ultraviolet to Infrared SED with Gaussian Process Regression

Improving our knowledge of global Milky Way (MW) properties is critical for connecting the detailed measurements only possible from within our Galaxy to our understanding of the broader galaxy population. We train Gaussian Process Regression (GPR) models on SDSS galaxies to map from galaxy properties (stellar mass, apparent axis ratio, star formation rate, bulge-to-total ratio, disk scale length, and bar vote fraction) to UV (GALEX $FUV/NUV$), optical (SDSS $ugriz$) and IR (2MASS $JHKs$ and WISE $W1/W2/W3/W4$) fluxes and uncertainties. With these models we estimate the photometric properties of the MW, resulting in a full UV-to-IR spectral energy distribution (SED) as it would be measured externally, viewed face-on. We confirm that the Milky Way lies in the green valley in optical diagnostic diagrams, but show for the first time that the MW is in the star-forming region in standard UV and IR diagnostics -- characteristic of the population of red spiral galaxies. Although our GPR method predicts one band at a time, the resulting MW UV--IR SED is consistent with SEDs of local spirals with characteristics broadly similar to the MW, suggesting that these independent predictions can be combined reliably. Our UV--IR SED will be invaluable for reconstructing the MW's star formation history using the same tools employed for external galaxies, allowing comparisons of results from \textit{in situ} measurements to those from the methods used for extra-galactic objects.

astro-ph.GA↗

arXiv2021

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: BAO and RSD measurements from the anisotropic power spectrum of the Quasar sample between redshift 0.8 and 2.2

We measure the clustering of quasars of the final data release (DR16) of eBOSS. The sample contains $343\,708$ quasars between redshifts $0.8\leq z\leq2.2$ over $4699\,\mathrm{deg}^2$. We calculate the Legendre multipoles (0,2,4) of the anisotropic power spectrum and perform a BAO and a Full-Shape (FS) analysis at the effective redshift $z{\rm eff}=1.480$. The errors include systematic errors that amount to 1/3 of the statistical error. The systematic errors comprise a modelling part studied using a blind N-Body mock challenge and observational effects studied with approximate mocks to account for various types of redshift smearing and fibre collisions. For the BAO analysis, we measure the transverse comoving distance $D_{\rm M}(z_{\rm eff})/r_{\rm drag}=30.60\pm{0.90}$ and the Hubble distance $D_{\rm H}(z_{\rm eff})/r_{\rm drag}=13.34\pm{0.60}$. This agrees with the configuration space analysis, and the consensus yields: $D_{\rm M}(z_{\rm eff})/r_{\rm drag}=30.69\pm{0.80}$ and $D_{\rm H}(z_{\rm eff})/r_{\rm drag}=13.26\pm{0.55}$. In the FS analysis, we fit the power spectrum using a model based on Regularised Perturbation Theory, which includes Redshift Space Distortions and the Alcock-Paczynski effect. The results are $D_{\rm M}(z_{\rm eff})/r_{\rm drag}=30.68\pm{0.90}$ and $D_{\rm H}(z_{\rm eff})/r_{\rm drag}=13.52\pm{0.51}$ and we constrain the linear growth rate of structure $f(z_{\rm eff})σ_8(z_{\rm eff})=0.476\pm{0.047}$. Our results agree with the configuration space analysis. The consensus analysis of the eBOSS quasar sample yields: $D_{\rm M}(z_{\rm eff})/r_{\rm drag}=30.21\pm{0.79}$, $D_{\rm H}(z_{\rm eff})/r_{\rm drag}=3.23\pm{0.47}$ and $f(z_{\rm eff})σ_8(z_{\rm eff})=0.462\pm{0.045}$ and is consistent with a flat $Λ{\rm CDM}$ cosmological model using Planck results.

astro-ph.CO↗

arXiv2021

The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy.

astro-ph.CO↗

arXiv2021

The Clustering of DESI-like Luminous Red Galaxies Using Photometric Redshifts

We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging dataset, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of $0.4 < z < 0.9$ over 5655 deg$^2$. We have developed new photometric redshift (photo-$z$) estimates using the Legacy Survey DECam and WISE photometry, with $σ_{\mathrm{NMAD}} = 0.02$ precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalog, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N-body catalogs, and present a new technique for finding best-fit parameters in this situation. Accompanying this paper we have released the Photometric Redshifts for the Legacy Surveys (PRLS) catalog of photo-$z$'s obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 dataset. This catalog provides accurate photometric redshifts for objects with $z < 21$ over more than 16,000 deg$^2$ of sky.

astro-ph.CO↗