Engineering topics

Schubnell, Michael

Publications and source records attributed to Schubnell, Michael.

At least 37 records · Page 2

DOE OSTI2024

AuriDESI: mock catalogues for the DESI Milky Way Survey

The Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) will explore the assembly history of the Milky Way by characterizing remnants of ancient dwarf galaxy accretion events and improving constraints on the distribution of dark matter in the outer halo. We present mock catalogues that reproduce the selection criteria of MWS and the format of the final MWS data set. These catalogues can be used to test methods for quantifying the properties of stellar halo substructure and reconstructing the Milky Way’s accretion history with the MWS data, including the effects of halo-to-halo variance. The mock catalogues are based on a phase-space kernel expansion technique applied to star particles in the Auriga suite of six high-resolution lambda-cold dark matter magnetohydrodynamic zoom-in simulations. They include photometric properties (and associated errors) used in DESI target selection and the outputs of the MWS spectral analysis pipeline (radial velocity, metallicity, surface gravity, and temperature). They also include information from the underlying simulation, such as the total gravitational potential and information on the progenitors of accreted halo stars. We discuss how the subset of halo stars observable by MWS in these simulations corresponds to their true content and properties. These mock Milky Ways have rich accretion histories, resulting in a large number of substructures that span the whole stellar halo out to large distances and have substantial overlap in the space of orbital energy and angular momentum.

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DOE OSTI2024

Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies

ABSTRACT We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter fNL. Our sample comprises over 12 million targets, covering 14 000 deg2 of the sky, with redshifts in the range 0.2 < z < 1.35. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against simulations with and without fNL and systematics, showing superior performance of the neural network treatment. The neural network with a set of nine imaging property maps passes our systematic null test criteria, and is chosen as the fiducial treatment. Assuming the universality relation, we find $f_{\rm NL} = 34^{+24(+50)}_{-44(-73)}$ at 68 per cent (95 per cent) confidence. We apply a series of robustness tests (e.g. cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. We study how the regression method biases the measured angular power spectrum and degrades the fNL constraining power. The use of the nine maps more than doubles the uncertainty compared to using only the three primary maps in the regression. Our results thus motivate the development of more efficient methods that avoid overcorrection, protect large-scale clustering information, and preserve constraining power. Additionally, our results encourage further studies of fNL with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics and lessen the degradation in the fNL uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Emission line predictions for mock galaxy catalogues: a new differentiable and empirical mapping from DESI

ABSTRACT We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H α, H β, [O ii], and [O iii]) from a galaxy’s rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman’s rank correlation coefficient ρs > 0.87 between predictions and observations for most lines. Using a non-linear dimensionality reduction technique, we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterize and account for biases in the spectroscopic training sets used for training and calibration of photo-z’s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.

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DOE OSTI2024

The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with AbacusSummit

ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 < z < 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

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DOE OSTI2024

Constraining primordial non-Gaussianity from DESI quasar targets and Planck CMB lensing

We detect the cross-correlation between 2.7 million DESI quasar targets across 14,700 deg 2 (180 quasars deg -2 ) and Planck 2018 CMB lensing at ~30σ. We use the cross-correlation on very large scales to constrain local primordial non-Gaussianity via the scale dependence of quasar bias. The DESI quasar targets lie at an effective redshift of 1.51 and are separated into four imaging regions of varying depth and image quality. We select quasar targets from Legacy Survey DR9 imaging, apply additional flux and photometric redshift cuts to improve the purity and reduce the fraction of unclassified redshifts, and use early DESI spectroscopy of 194,000 quasar targets to determine their redshift distribution and stellar contamination fraction (2.6%). Due to significant excess large-scale power in the quasar autocorrelation, we apply weights to mitigate contamination from imaging systematics such as depth, extinction, and stellar density. We use realistic contaminated mocks to determine the greatest number of systematic modes that we can fit, before we are biased by overfitting and spuriously remove real power. We find that linear regression with one to seven imaging templates removed per region accurately recovers the input cross-power, f NL and linear bias. As in previous analyses, our fNL constraint depends on the linear primordial non-Gaussianity bias parameter, b Φ = 2(b - p)δ c assuming universality of the halo mass function. We measure f NL = -26 +45 -40 with p = 1.6 (f NL = -18 +29 -27 with p = 1.0), and find that this result is robust under several systematics tests. Future spectroscopic quasar cross-correlations with Planck lensing can tighten the f NL constraints by a factor of 2 if they can remove the excess power on large scales in the quasar auto power spectrum.

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DOE OSTI2024

The DESI One-percent Survey: Evidence for Assembly Bias from Low-redshift Counts-in-cylinders Measurements

Abstract We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z = 0.1 to 0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey. In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab , which enables the rapid, precise prediction of CiC for any HOD model available in halotools . This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in z ∼ 0.15 samples with limiting absolute magnitude M r < −20.0 and M r < −20.5 samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter M r < −21.0 sample at z ∼ 0.25 (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at z ∼ 0.15. We provide our constraints for each threshold sample’s characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.

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DOE OSTI2024

PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-percent Survey. The One-percent Survey was one of DESI's survey validation programs conducted from 2021 April to May, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the r < 19.5 magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface-brightness- and color-selected BGS Faint sample over z < 0.6. We derive pSMFs from posteriors of stellar mass, M*, inferred from DESI photometry and spectroscopy using the Hahn et al. PRObabilistic Value-Added BGS (PROVABGS) Bayesian spectral energy distribution modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the M* uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS, as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100 × more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.

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DOE OSTI2024

Redshift-dependent RSD bias from intrinsic alignment with DESI Year 1 spectra

ABSTRACT 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 fraction of DESI’s error budget. We provide estimates of the ξ2 signal created by intrinsic alignments that can be used to correct this effect, which is necessary to meet DESI’s forecasted precision on measuring the growth rate of structure. While imaging quality varies across DESI’s footprint, we find no significant difference in this effect between imaging regions in the Legacy Imaging Survey.

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DOE OSTI2024

Long-term follow-up observations of extreme coronal line emitting galaxies

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 (AGNs) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal line features and AGN-like MIR colors and behavior. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability.

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DOE OSTI2024

Changing-look Active Galactic Nuclei from the Dark Energy Spectroscopic Instrument. I. Sample from the Early Data

Changing-look active galactic nuclei (CL AGNs) can be generally confirmed by the emergence (turn-on) or disappearance (turn-off) of broad emission lines (BELs), associated with a transient timescale (about 100 ~ 5000 days) that is much shorter than predicted by traditional accretion disk models. We carry out a systematic CL AGN search by crossmatching the spectra coming from the Dark Energy Spectroscopic Instrument and the Sloan Digital Sky Survey. Following previous studies, we identify CL AGNs based on Hα, Hβ, and Mg ii at z ≤ 0.75 and Mg ii, C iii], and C iv at z > 0.75. We present 56 CL AGNs based on visual inspection and three selection criteria, including 2 Hα, 34 Hβ, 9 Mg ii, 18 C iii], and 1 C iv CL AGN. Eight cases show simultaneous appearances/disappearances of two BELs. We also present 44 CL AGN candidates with significant flux variation of BELs, but remaining strong broad components. In the confirmed CL AGNs, 10 cases show additional CL candidate features for different lines. In this paper, we find: (1) a 24:32 ratio of turn-on to turn-off CL AGNs; (2) an upper-limit transition timescale ranging from 330 to 5762 days in the rest frame; and (3) the majority of CL AGNs follow the bluer-when-brighter trend. Our results greatly increase the current CL census (~30%) and would be conducive to exploring the underlying physical mechanism.

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DOE OSTI2024

The DESI One-Percent Survey: A Concise Model for the Galactic Conformity of Emission-line Galaxies

Galactic conformity is the phenomenon whereby a galaxy of a certain physical property is correlated with its neighbors of the same property, implying a possible causal relationship. Here, the observed auto correlations of emission-line galaxies (ELGs) from the highly complete DESI One-Percent Survey exhibit a strong clustering signal on small scales, providing clear evidence for the conformity effect of ELGs. Building upon the original subhalo abundance-matching (SHAM) method developed by Gao et al., we propose a concise conformity model to improve the ELG–halo connection. In this model, the number of satellite ELGs is boosted by a factor of ~5 in the halos whose central galaxies are ELGs. We show that the mean ELG satellite number in such central halos is still smaller than 1 and that the model does not significantly increase the overall satellite fraction. With this model, we can well recover the ELG auto correlations to the smallest scales explored with the current data (i.e., r p > 0.03 Mpc h –1 in real space and at s > 0.3 Mpc h –1 in redshift space), while the cross correlations between luminous red galaxies and ELGs are nearly unchanged. Although our SHAM model has only eight parameters, we further verify that it can accurately describe the ELG clustering in the entire redshift range from z = 0.8 to 1.6. We therefore expect that this method can be used to generate high-quality ELG lightcone mocks for DESI.

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DOE OSTI2023

DESI Survey Validation Data in the COSMOS/Hyper Suprime-Cam Field: Cool Gas Trace Main-sequence Star-forming Galaxies at the Cosmic Noon

We present the first result in exploring the gaseous halo and galaxy correlation using the Dark Energy Spectroscopic Instrument survey validation data in the Cosmic Evolution Survey (COSMOS) and Hyper Suprime-Cam field. We obtain multiphase gaseous halo properties in the circumgalactic medium by using 115 quasar spectra (signal-to-noise ratio > 3). We detect Mg ii absorption at redshift 0.6 < z < 2.5, C iv absorption at 1.6 < z < 3.6, and H i absorption associated with the Mg ii and C iv. By crossmatching the COSMOS2020 catalog, we identify the Mg ii and C iv host galaxies in 10 quasar fields at 0.9< z < 3.1. We find that within the impact parameter of 250 kpc, a tight correlation is seen between the strong Mg ii equivalent width and the host galaxy star formation rate. The covering fraction f c of the strong Mg ii selected galaxies, which is the ratio of the absorbing galaxy in a certain galaxy population, shows significant evolution in the main-sequence galaxies and marginal evolution in all the galaxy populations within 250 kpc at 0.9 < z < 2.2. The f c increase in the main-sequence galaxies likely suggests the coevolution of strong Mg ii absorbing gas and the main-sequence galaxies at the cosmic noon. Furthermore, Mg ii and C iv absorbing gas is detected out of the galaxy virial radius, tentatively indicating the feedback produced by the star formation and/or the environmental effects.

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DOE OSTI2023

DESI mock challenge: constructing DESI galaxy catalogues based on FastPM simulations

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large-scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must build realistic simulations and robust covariance matrices. We build galaxy catalogues by applying a halo occupation distribution (HOD) model upon the FastPM simulations, such that the resulting galaxy clustering reproduces high-resolution N-body simulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxy two-point clustering measurements – monopole and quadrupole – to a precision required by the DESI Year 1 emission line galaxy sample down to non-linear scales, i.e. $k\lt 0.5\, h\, \mathrm{Mpc}^{-1}$ or $s\gt 10\, \mathrm{Mpc}\, h^{-1}$. Furthermore, we compute covariance matrices based on the resulting FastPM galaxy clustering – monopole and quadrupole. We study for the first time the effect of fitting on Fourier conjugate (e.g. power spectrum) on the covariance matrix of the Fourier counterpart (e.g. correlation function). We estimate the uncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the different covariance matrices. Nevertheless, for most studied scales the scatter is between 2 and 10 per cent. Consequently, using the current pipeline we can precisely reproduce the clustering of N-body simulations and the resulting covariance matrices provide robust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESI data analyses and their extension for other studies.

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DOE OSTI2023

DESI luminous red galaxy samples for cross-correlations

We present two galaxy samples, selected from DESI Legacy Imaging Surveys (LS) DR9, with approximately 20,000 square degrees of coverage and spectroscopic redshift distributions designed for cross-correlations such as with CMB lensing, galaxy lensing, and the Sunyaev-Zel'dovich effect. The first sample is identical to the DESI Luminous Red Galaxy (LRG) sample, and the second sample is an extended LRG sample with 2–3 times the DESI LRG density. We present the improved photometric redshifts, tomographic binning and their spectroscopic redshift distributions and imaging systematics weights, and magnification bias coefficients. The catalogs and related data products will be made publicly available. The cosmological constraints using this sample and Planck lensing maps are presented in a companion paper. Here, we also make public the new set of general-purpose photometric redshifts trained using DESI spectroscopic redshifts, which are used in this work, for all galaxies in LS DR9.

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DOE OSTI2023

The two-point correlation function covariance with fewer mocks

We present FITCOV an approach for accurate estimation of the covariance of two-point correlation functions that requires fewer mocks than the standard mock-based covariance. This can be achieved by dividing a set of mocks into jackknife regions and fitting the correction term first introduced in Mohammad & Percival (2022), such that the mean of the jackknife covariances corresponds to the one from the mocks. This extends the model beyond the shot-noise limited regime, allowing it to be used for denser samples of galaxies. We test the performance of our fitted jackknife approach, both in terms of accuracy and precision, using lognormal mocks with varying densities and approximate EZmocks mimicking the Dark Energy Spectroscopic Instrument LRG and ELG samples in the redshift range of z = [0.8, 1.1]. We find that the Mohammad–Percival correction produces a bias in the two-point correlation function covariance matrix that grows with number density and that our fitted jackknife approach does not. We also study the effect of the covariance on the uncertainty of cosmological parameters by performing a full-shape analysis. We demonstrate that our fitted jackknife approach based on 25 mocks can recover unbiased and as precise cosmological parameters as the ones obtained from a covariance matrix based on 1000 or 1500 mocks, while the Mohammad–Percival correction produces uncertainties that are twice as large.

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DOE OSTI2023

GTC Follow-up Observations of Very Metal-poor Star Candidates from DESI

Abstract The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of ∼10, improving the sample statistics to study the early chemical evolution of the Milky Way and the nature of the first stars. In this paper we report follow-up observations with high signal-to-noise ratio of nine metal-poor stars identified during the DESI commissioning with the Optical System for Imaging and Low-Resolution Integrated Spectroscopy (OSIRIS) instrument on the 10.4 m Gran Telescopio Canarias. The analysis of the data using a well-vetted methodology confirms the quality of the DESI spectra and the performance of the pipelines developed for the data reduction and analysis of DESI data.

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DOE OSTI2023

Mitigating the noise of DESI mocks using analytic control variates

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological N-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). The power of control variates stems from utilizing inexpensive but highly correlated surrogates of the statistics one wishes to measure. The stronger the correlation between the surrogate and the statistic of interest, the larger the variance reduction delivered by the method. We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements offer a factor of 5-10 improvement in the measurement error compared with the raw measurements. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis.

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DOE OSTI2023

The DESI One-Percent survey: exploring the Halo Occupation Distribution of Emission Line Galaxies with AbacusSummit simulations

The One-Percent survey of the Dark Energy Spectroscopic Instrument collected ~ 270k emission line galaxies (ELGs) at 0.8 < z < 1.6. The high completeness of the sample allowed the clustering to be measured down to scales never probed before, 0.04 Mpc/h in rp for the projected 2-point correlation function (2PCF) and 0.17 Mpc/h in galaxy pair separation s for the 2PCF monopole and quadrupole. The most striking feature of the measurements is a strong signal at the smallest scales, below 0.2 Mpc/h in rp and 1 Mpc/h in s. We analyse these data in the halo occupation distribution framework. We consider different distributions for central galaxies, a standard power law for satellites with no condition on the presence of a central galaxy and explore several extensions of these models. For all considered models, the mean halo mass of the sample is found to be log10 $\langle$Mh$\rangle$ ~ 11.9. We obtain a satellite mean occupation function which agrees with physically motivated ELG models only if we introduce central-satellite conformity, meaning that the satellite occupation is conditioned by the presence of central galaxies of the same type. To achieve in addition a good modelling of the clustering between 0.1 and 1 Mpc/h in rp, we allow for ELG positioning outside of the halo virial radius and find 0.5% of ELGs residing in the outskirts of halos. Furthermore, the satellite velocity dispersion inside halos is found to be ~ 30% larger than that of the halo dark matter particles. These are the main findings of our work. Here we investigate assembly bias as a function of halo concentration, local density or local density anisotropies and observe no significant change in our results. We split the data sample in two redshift bins and report no significant evolution with redshift. Lastly, changing the cosmology in the modelling impacts only slightly our results.

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