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Robert Kehoe

Publications and source records attributed to Robert Kehoe.

At least 73 records · Page 4Linked to original sources

Overview of the DESI Milky Way Survey

We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4m telescope at the Kitt Peak National Observatory. Over the next 5 yr DESI MWS will observe approximately seven million stars at Galactic latitudes |b|>20 degrees, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines for deriving radial velocities, atmospheric parameters, and chemical abundances. We use ~500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to ~1 km/s and [Fe/H] accurate to ~0.2 dex for typical stars in our main sample. We find the stellar parameter distributions from ~100 sq. deg of SV observations with >90% completeness on our main sample are in good agreement with expectations from mock catalogs and previous surveys.

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Optimal 1D Ly$α$ Forest Power Spectrum Estimation -- II. KODIAQ, SQUAD & XQ-100

We measure the 1D Ly$\,α$ power spectrum $P_\mathrm{1D}$ from Keck Observatory Database of Ionized Absorption toward Quasars (KODIAQ), The Spectral Quasar Absorption Database (SQUAD) and XQ-100 quasars using the optimal quadratic estimator. We combine KODIAQ and SQUAD at the spectrum level, but perform a separate XQ-100 estimation to control its large resolution corrections in check. Our final analysis measures $P_\mathrm{1D}$ at scales $k<0.1\,$s$\,$km$^{-1}$ between redshifts $z=$ 2.0 -- 4.6 using 538 quasars. This sample provides the largest number of high-resolution, high-S/N observations; and combined with the power of optimal estimator it provides exceptional precision at small scales. These small-scale modes ($k\gtrsim 0.02\,$s$\,$km$^{-1}$), unavailable in Sloan Digital Sky Survey (SDSS) and Dark Energy Spectroscopic Instrument (DESI) analyses, are sensitive to the thermal state and reionization history of the intergalactic medium, as well as the nature of dark matter. As an example, a simple Fisher forecast analysis estimates that our results can improve small-scale cut off sensitivity by more than a factor of 2.

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The effect of quasar redshift errors on Lyman-$α$ forest correlation functions

Using synthetic Lyman-$α$ forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-$α$ correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred $\text{km s}^{-1}\,$ due to the broadness of the emission lines and the intrinsic shifts from other emission lines. We inject Gaussian random redshift errors into the mock quasar catalogues, and measure the auto-correlation and the Lyman-$α$-quasar cross-correlation functions. We find a smearing of the BAO feature in the radial direction, but changes in the peak position are negligible. However, we see a significant unphysical correlation for small separations transverse to the line of sight which increases with the amplitude of the redshift errors. We interpret this contamination as a result of the broadening of emission lines in the measured mean continuum, caused by quasar redshift errors, combined with the unrealistically strong clustering of the simulated quasars on small scales.

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Constraining galaxy-halo connection with high-order statistics

We investigate using three-point statistics in constraining the galaxy-halo connection. We show that for some galaxy samples, the constraints on the halo occupation distribution parameters are dominated by the three-point function signal (over its two-point counterpart). We demonstrate this on mock catalogs corresponding to the Luminous Red Galaxies (LRGs), Emission-Line Galaxies (ELG), and quasars (QSOs) targeted by the Dark Energy Spectroscopic Instrument (DESI) Survey. The projected three-point function for triangle sides less up to 20$h^{-1}$ Mpc measured from a cubic Gpc of data can constrain the characteristic minimum mass of the LRGs with a precision of $0.46$ %. For comparison, similar constraints from the projected two-point function are $1.55$ %. The improvements for the ELGs and QSOs targets are more modest. In the case of the QSOs it is caused by the high shot-noise of the sample, and in the case of the ELGs, this is caused by the range of halo masses of the host halos. The most time-consuming part of our pipeline is the measurement of the three-point functions. We adopt a tabulation method, proposed in earlier works for the two-point function, to reduce significantly the required compute time for the three-point analysis.

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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.

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DESI Bright Galaxy Survey: Final Target Selection, Design, and Validation

Over the next five years, the Dark Energy Spectroscopic Instrument (DESI) will use 10 spectrographs with 5000 fibers on the 4m Mayall Telescope at Kitt Peak National Observatory to conduct the first Stage-IV dark energy galaxy survey. At $z < 0.6$, the DESI Bright Galaxy Survey (BGS) will produce the most detailed map of the Universe during the dark energy dominated epoch with redshifts of >10 million galaxies over 14,000 deg$^2$. In this work, we present and validate the final BGS target selection and survey design. From the Legacy Surveys, BGS will target a $r < 19.5$ magnitude-limited sample (BGS Bright); a fainter $19.5 < r < 20.175$ sample, color-selected to have high redshift efficiency (BGS Faint); and a smaller low-z quasar sample. BGS will observe these targets using exposure times, scaled to achieve uniform completeness, and visit each point on the footprint three times. We use observations from the Survey Validation programs conducted prior to the main survey along with realistic simulations to show that BGS can complete its strategy and make optimal use of `bright' time. We demonstrate that BGS targets have stellar contamination <1% and that their densities do not depend strongly on imaging properties. We also confirm that BGS Bright will achieve >80% fiber assignment efficiency. Finally, we show that BGS Bright and Faint will achieve >95% redshift success rates with no significant dependence on observing conditions. BGS meets the requirements for an extensive range of scientific applications. BGS will yield the most precise Baryon Acoustic Oscillations and Redshift-Space Distortions measurements at $z < 0.4$. It also presents opportunities to exploit new methods that require highly complete and dense galaxy samples (e.g. N-point statistics, multi-tracers). BGS further provides a powerful tool to study galaxy populations and the relations between galaxies and dark matter.

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The DESI $N$-body Simulation Project -- II. Suppressing sample variance with fast simulations

Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim20\Gpchcube$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. \textsc{AbacusSummit} is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\Gpchcube$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-$N$-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k < 0.3\hMpc$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in \textsc{AbacusSummit} suite to extend the effective volume $\sim 20$ times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

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The Robotic Multi-Object Focal Plane System of the Dark Energy Spectroscopic Instrument (DESI)

A system of 5,020 robotic fiber positioners was installed in 2019 on the Mayall Telescope, at Kitt Peak National Observatory. The robots automatically re-target their optical fibers every 10 - 20 minutes, each to a precision of several microns, with a reconfiguration time less than 2 minutes. Over the next five years, they will enable the newly-constructed Dark Energy Spectroscopic Instrument (DESI) to measure the spectra of 35 million galaxies and quasars. DESI will produce the largest 3D map of the universe to date and measure the expansion history of the cosmos. In addition to the 5,020 robotic positioners and optical fibers, DESI's Focal Plane System includes 6 guide cameras, 4 wavefront cameras, 123 fiducial point sources, and a metrology camera mounted at the primary mirror. The system also includes associated structural, thermal, and electrical systems. In all, it contains over 675,000 individual parts. We discuss the design, construction, quality control, and integration of all these components. We include a summary of the key requirements, the review and acceptance process, on-sky validations of requirements, and lessons learned for future multi-object, fiber-fed spectrographs.

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The DESI PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) Mock Challenge

The PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ($M_*$), star formation rate (${\rm SFR}$), stellar metallicity ($Z_{\rm MW}$), and stellar age ($t_{\rm age, MW}$), for >10 million galaxies of the DESI Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, Bayesian inference framework, and methodology of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-GALAXIES semi-analytic model. We compare the inferred galaxy properties to the true galaxy properties of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true $M_*$, ${\rm SFR}$, $Z_{\rm MW}$, and $t_{\rm age, MW}$ of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors. They impose a ${\rm SFR}{>}10^{-1} M_\odot/{\rm yr}$ lower bound on ${\rm SFR}$, a ${\sim}0.3$ dex bias on $\log Z_{\rm MW}$ for galaxies with low spectral signal-to-noise, and $t_{\rm age, MW} < 8\,{\rm Gyr}$ upper bound on stellar age. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and provide a probabilistic value-added galaxy catalog that will extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses.

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Cosmological constraints from the tomographic cross-correlation of DESI Luminous Red Galaxies and Planck CMB lensing

We use luminous red galaxies selected from the imaging surveys that are being used for targeting by the Dark Energy Spectroscopic Instrument (DESI) in combination with CMB lensing maps from the Planck collaboration to probe the amplitude of large-scale structure over $0.4\le z\le 1$. Our galaxy sample, with an angular number density of approximately $500\,\mathrm{deg}^{-2}$ over 18,000 sq.deg., is divided into 4 tomographic bins by photometric redshift and the redshift distributions are calibrated using spectroscopy from DESI. We fit the galaxy autospectra and galaxy-convergence cross-spectra using models based on cosmological perturbation theory, restricting to large scales that are expected to be well described by such models. Within the context of $Λ$CDM, combining all 4 samples and using priors on the background cosmology from supernova and baryon acoustic oscillation measurements, we find $S_8=σ_8(Ω_m/0.3)^{0.5}=0.73\pm 0.03$. This result is lower than the prediction of the $Λ$CDM model conditioned on the Planck data. Our data prefer a slower growth of structure at low redshift than the model predictions, though at only modest significance.

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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.

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Preliminary clustering properties of the DESI BGS bright targets using DR9 Legacy Imaging Surveys

We characterise the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one as explored in Ruiz-Macias et al. (2021). We also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (r $\leq$ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength and slope by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher-order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering-redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterised and validated with the spectroscopic data of Survey Validation.

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Characterising the target selection pipeline for the Dark Energy Spectroscopic Instrument Bright Galaxy Survey

We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main issues faced in the selection of targets for the DESI BGS, such as star-galaxy separation, contamination by fragmented stars and bright galaxies. Our pipeline utilizes a new way to select BGS galaxies using Gaia photometry and we implement geometrical and photometric masks that reduce the number of spurious objects. The resulting catalogue is cross-matched with the Galaxy And Mass Assembly (GAMA) survey to assess the completeness of the galaxy catalogue and the performance of the target selection. We also validate the clustering of the sources in our BGS catalogue by comparing with mock catalogues and the Sloan Digital Sky Survey (SDSS) data. Finally, the robustness of the BGS selection criteria is assessed by quantifying the dependence of the target galaxy density on imaging and other properties. The largest systematic correlation we find is a 7 per cent suppression of the target density in regions of high stellar density.

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The DESI Sky Continuum Monitor System

The Dark Energy Spectroscopic Instrument (DESI) is an ongoing spectroscopic survey to measure the dark energy equation of state to unprecedented precision. We describe the DESI Sky Continuum Monitor System, which tracks the night sky brightness as part of a system that dynamically adjusts the spectroscopic exposure time to produce more uniform data quality and to maximize observing efficiency. The DESI dynamic exposure time calculator (ETC) will combine sky brightness measurements from the Sky Monitor with data from the guider system to calculate the exposure time to achieve uniform signal-to-noise ratio (SNR) in the spectra under various observing conditions. The DESI design includes 20 sky fibers, and these are split between two identical Sky Monitor units to provide redundancy. Each Sky Monitor unit uses an SBIG STXL-6303e CCD camera and supports an eight-position filter wheel. Both units have been completed and delivered to the Mayall Telescope at the Kitt Peak National Observatory. Commissioning results show that the Sky Monitor delivers the required performance necessary for the ETC.

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Preliminary Target Selection for the DESI Quasar (QSO) Sample

The DESI survey will measure large-scale structure using quasars as direct tracers of dark matter in the redshift range $0.9 2.1$. We present two methods to select candidate quasars for DESI based on imaging in three optical ($g, r, z$) and two infrared ($W1, W2$) bands. The first method uses traditional color cuts and the second utilizes a machine-learning algorithm.

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Preliminary Target Selection for the DESI Emission Line Galaxy (ELG) Sample

DESI will precisely constrain cosmic expansion and the growth of structure by collecting $\sim$35 million redshifts across $\sim$80% of cosmic history and one third of the sky to study Baryon Acoustic Oscillations (BAO) and Redshift Space Distortions (RSD). We present a preliminary target selection for an Emission Line Galaxy (ELG) sample, which will comprise about half of all DESI tracers. The selection consists of a $g$-band magnitude cut and a $(g-r)$ vs. $(r-z)$ color box, which we validate using HSC/PDR2 photometric redshifts and DEEP2 spectroscopy. The ELG target density should be $\sim$2400 deg$^{-2}$, with $\sim$65% of ELG redshifts reliably within a redshift range of $0.6<z<1.6$. ELG targeting for DESI will be finalized during a `Survey Validation' phase.

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Preliminary Target Selection for the DESI Luminous Red Galaxy (LRG) Sample

The DESI survey will observe more than 8 million candidate luminous red galaxies (LRGs) in the redshift range $0.3<z<1.0$. Here we present a preliminary version of the DESI LRG target selection developed using Legacy Surveys Data Release 8 $g$, $r$, $z$ and $W1$ photometry. This selection yields a sample with a uniform surface density of ${\sim}\,600$ deg$^{-2}$and very low predicted stellar contamination and redshift failure rates. During DESI Survey Validation, updated versions of this selection will be tested and optimized.

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Preliminary Target Selection for the DESI Milky Way Survey (MWS)

The DESI Milky Way Survey (MWS) will observe $\ge$8 million stars between $16 < r < 19$ mag, supplemented by observations of brighter targets under poor observing conditions. The survey will permit an accurate determination of stellar kinematics and population gradients; characterize diffuse substructure in the thick disk and stellar halo; enable the discovery of extremely metal-poor stars and other rare stellar types; and improve constraints on the Galaxy's 3D dark matter distribution from halo star kinematics. MWS will also enable a detailed characterization of the stellar populations within 100 pc of the Sun, including a complete census of white dwarfs. The target catalog from the preliminary selection described here is public.

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