1,860 research outputs found

    Halo Occupation Distribution of Emission Line Galaxies: fitting method with Gaussian Processes

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    The halo occupation distribution (HOD) framework is an empirical method to describe the connection between dark matter halos and galaxies, which is constrained by small scale clustering data. Efficient fitting procedures are required to scan the HOD parameter space. This paper describes such a method based on Gaussian Processes to iteratively build a surrogate model of the posterior of the likelihood surface from a reasonable amount of likelihood computations, typically two orders of magnitude less than standard Monte Carlo Markov chain algorithms. Errors in the likelihood computation due to stochastic HOD modelling are also accounted for in the method we propose. We report results of reproducibility, accuracy and stability tests of the method derived from simulation, taking as a test case star-forming emission line galaxies, which constitute the main tracer of the Dark Energy Spectroscopic Instrument and have so far a poorly constrained galaxy-halo connection from observational data

    Constraining ΜΛ\nu \LambdaCDM with density-split clustering

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    The dependence of galaxy clustering on local density provides an effective method for extracting non-Gaussian information from galaxy surveys. The two-point correlation function (2PCF) provides a complete statistical description of a Gaussian density field. However, the late-time density field becomes non-Gaussian due to non-linear gravitational evolution and higher-order summary statistics are required to capture all of its cosmological information. Using a Fisher formalism based on halo catalogues from the Quijote simulations, we explore the possibility of retrieving this information using the density-split clustering (DS) method, which combines clustering statistics from regions of different environmental density. We show that DS provides more precise constraints on the parameters of the ΜΛ\nu \LambdaCDM model compared to the 2PCF, and we provide suggestions for where the extra information may come from. DS improves the constraints on the sum of neutrino masses by a factor of 88 and by factors of 5, 3, 4, 6, and 6 for Ωm\Omega_m, Ωb\Omega_b, hh, nsn_s, and σ8\sigma_8, respectively. We compare DS statistics when the local density environment is estimated from the real or redshift-space positions of haloes. The inclusion of DS autocorrelation functions, in addition to the cross-correlation functions between DS environments and haloes, recovers most of the information that is lost when using the redshift-space halo positions to estimate the environment. We discuss the possibility of constructing simulation-based methods to model DS clustering statistics in different scenarios.Comment: Submitted to MNRAS. Source code for all figures in the paper is provided in the caption

    Combined full shape analysis of BOSS galaxies and eBOSS quasars using an iterative emulator

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    Standard full-shape clustering analyses in Fourier space rely on a fixed power spectrum template, defined at the fiducial cosmology used to convert redshifts into distances, and compress the cosmological information into the Alcock-Paczynski parameters and the linear growth rate of structure. In this paper, we propose an analysis method that operates directly in the cosmology parameter space and varies the power spectrum template accordingly at each tested point. Predictions for the power spectrum multipoles from the TNS model are computed at different cosmologies in the framework of ΛCDM\Lambda \rm{CDM}. Applied to the final eBOSS QSO and LRG samples together with the low-z DR12 BOSS galaxy sample, our analysis results in a set of constraints on the cosmological parameters Ωcdm\Omega_{\rm cdm}, H0H_0, σ8\sigma_8, Ωb\Omega_{\rm b} and nsn_s. To reduce the number of computed models, we construct an iterative process to sample the likelihood surface, where each iteration consists of a Gaussian process regression. This method is validated with mocks from N-body simulations. From the combined analysis of the (e)BOSS data, we obtain the following constraints: σ8=0.877±0.049\sigma_8=0.877\pm 0.049 and Ωm=0.304−0.010+0.016\Omega_{\rm m}=0.304^{+0.016}_{-0.010} without any external prior. The eBOSS quasar sample alone shows a 3.1σ3.1\sigma discrepancy compared to the Planck prediction.Comment: 13 pages, 7 figure

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

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    The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next 5 yr. 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 multilayer 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 extended Baryon Oscillation Spectroscopic Survey (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 that 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.This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under contract no. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under contract no. AST-0950945 to the NSF’s National Optical–Infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology, Mexico; the Ministry of Economy of Spain, and by the DESI Member Institutions. ADM was supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0019022

    The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: Growth rate of structure measurement from cosmic voids

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    We present a void clustering analysis in configuration-space using the completed Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 samples. These samples consist of Luminous Red Galaxies (LRG) combined with the high redshift tail of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) DR12 CMASS galaxies (called as LRG+CMASS sample), Emission Line Galaxies (ELG) and quasars (QSO). We build void catalogues from the three eBOSS DR16 samples using a ZOBOV-based algorithm, providing 2,814 voids, 1,801 voids and 4,347 voids in the LRG+CMASS, ELG and QSO samples, respectively, spanning the redshift range 0.6<z<2.20.6<z<2.2. We measure the redshift space distortions (RSD) around voids using the anisotropic void-galaxy cross-correlation function and we extract the distortion parameter ÎČ\beta. We test the methodology on realistic simulations before applying it to the data, and we investigate all our systematic errors on these mocks. We find ÎČLRG(z=0.74)=0.415±0.087\beta^{\rm LRG}(z=0.74)=0.415\pm0.087, ÎČELG(z=0.85)=0.665±0.125\beta^{\rm ELG}(z=0.85)=0.665\pm0.125 and ÎČQSO(z=1.48)=0.313±0.134\beta^{\rm QSO}(z=1.48)=0.313\pm0.134, for the LRG+CMASS, ELG and QSO sample, respectively. The quoted errors include systematic and statistical contributions. In order to convert our measurements in terms of the growth rate fσ8f\sigma_8, we use consensus values of linear bias from the eBOSS DR16 companion papers~\citep{eBOSScosmo}, resulting in the following constraints: fσ8(z=0.74)=0.50±0.11f\sigma_8(z=0.74)=0.50\pm0.11, fσ8(z=0.85)=0.52±0.10f\sigma_8(z=0.85)=0.52\pm0.10 and fσ8(z=1.48)=0.30±0.13f\sigma_8(z=1.48)=0.30\pm0.13. Our measurements are consistent with other measurements from eBOSS DR16 using conventional clustering techniques.Comment: 17 pages, 8 figure

    Efficient CRISPR/Cas9-mediated editing of trinucleotide repeat expansion in myotonic dystrophy patient-derived iPS and myogenic cells

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    International audienceCRISPR/Cas9 is an attractive platform to potentially correct dominant genetic diseases by gene editing with unprecedented precision. In the current proof-of-principle study, we explored the use of CRISPR/Cas9 for gene-editing in myotonic dys-trophy type-1 (DM1), an autosomal-dominant muscle disorder, by excising the CTG-repeat expansion in the 3-untranslated-region (UTR) of the human myotonic dystrophy protein kinase (DMPK) gene in DM1 patient-specific induced pluripotent stem cells (DM1-iPSC), DM1-iPSC-derived myogenic cells and DM1 patient-specific myoblasts. To eliminate the pathogenic gain-of-function mutant DMPK transcript , we designed a dual guide RNA based strategy that excises the CTG-repeat expansion with high efficiency , as confirmed by Southern blot and single molecule real-time (SMRT) sequencing. Correction efficiencies up to 90% could be attained in DM1-iPSC as confirmed at the clonal level, following ribonucle-oprotein (RNP) transfection of CRISPR/Cas9 components without the need for selective enrichment. Expanded CTG repeat excision resulted in the disappearance of ribonuclear foci, a quintessential cellular phenotype of DM1, in the corrected DM1-iPSC, DM1-iPSC-derived myogenic cells and DM1 myoblasts. Consequently, the normal intracellular localization of the muscleblind-like splicing regulator 1 (MBNL1) was restored, resulting in the normalization of splicing pattern of SERCA1. This study validates the use of CRISPR/Cas9 for gene editing of repeat expansions

    The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey : pairwise-inverse probability and angular correction for fibre collisions in clustering measurements

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    HJS is supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Number DE-SC0014329. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 693024).The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected wp(rp) and the redshift-space multipole Ο(ℓ = 0, 2, 4)(s) correlation functions down to 0.1h−1Mpc⁠, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales s≳20h−1Mpcs≳20h−1Mpc for Οℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to ∌0.1h−1Mpc scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.Publisher PDFPeer reviewe

    The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the Halo Occupation Distribution model for Emission Line Galaxies

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    We study the modelling of the Halo Occupation Distribution (HOD) for the eBOSS DR16 Emission Line Galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both NFW and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, wpw_p, captures most of the effects from the PDF and satellites profile. The quadrupole, Ο2\xi_2, captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. We fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.Comment: Data available here: http://popia.ft.uam.es/eBOSS_ELG_OR_mocks. A description of eBOSS and links to all associated publications can be found here: https://www.sdss.org/surveys/eboss/ ; 24 pages, 17 Figures; Published in MNRAS 25 Sep 202

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

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    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 square degrees 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 log-normal simulations with and without fNL and systematics, showing superior performance of the neural network treatment in reducing remaining systematics. Assuming the universality relation, we find fNL =47−11(−22)+14(+29)= 47^{+14(+29)}_{-11(-22)} at 68\%(95\%) confidence. With a more aggressive treatment, including regression against the full set of imaging maps, our maximum likelihood value shifts slightly to fNL∌50 \sim 50 and the uncertainty on fNL increases due to the removal of large-scale clustering information. We apply a series of robustness tests (e.g., cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. Despite extensive efforts to mitigate systematics, our measurements indicate fNL > 0 with a 99.9 percent confidence level. This outcome raises concerns as it could be attributed to unforeseen systematics, including calibration errors or uncertainties associated with low-\ell systematics in the extinction template. Alternatively, it could suggest a scale-dependent fNL model--causing significant non-Gaussianity around large-scale structure while leaving cosmic microwave background scales unaffected. Our results encourage further studies of fNL with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics.Comment: 19 pages, 15 figures, 6 tables (Appendix excluded). Submitted to MNRA
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