87 research outputs found
Intrinsic Alignment as an RSD Contaminant in the DESI Survey
We measure the tidal alignment of the major axes of Luminous Red Galaxies
(LRGs) from the Legacy Imaging Survey and use it to infer the artificial
redshift-space distortion signature that will arise from an
orientation-dependent, surface-brightness selection in the Dark Energy
Spectroscopic Instrument (DESI) survey. Using photometric redshifts to
down-weight the shape-density correlations due to weak lensing, we measure the
intrinsic tidal alignment of LRGs. Separately, we estimate the net polarization
of LRG orientations from DESI's fiber-magnitude target selection to be of order
10^-2 along the line of sight. Using these measurements and a linear tidal
model, we forecast a 0.2% fractional decrease on the quadrupole of the 2-point
correlation function for projected separations of 40-80 Mpc/h. We also use a
halo catalog from the Abacus Summit cosmological simulation suite to reproduce
this false quadrupole.Comment: 13 pages, 13 figures. Submitted to MNRAS. For an accessible summary
of this paper, see https://cmlamman.github.io/doc/fakeRSD_summary.pd
2-point statistics covariance with fewer mocks
We present an approach for accurate estimation of the covariance of 2-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 DESI LRG and ELG samples in the redshift range of z = [0.8, 1.2].
We find that the Mohammad-Percival correction produces a bias in the 2-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 find that our fitted jackknife approach based on 25
mocks is able to 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.
The number of mocks required to obtain an accurate estimation of the covariance
for 2-point correlation function is therefore reduced by a factor of 40-60.Comment: 13 pages, 14 figures, submitted to MNRA
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 buildrealistic 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-bodysimulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxytwo-point clustering measurements – monopole and quadrupole – to a precision required by the DESI Year 1 emission line galaxysample down to non-linear scales, i.e. k 10 Mpc h−1. Furthermore, we compute covariance matrices basedon the resulting FASTPM galaxy clustering – monopole and quadrupole. We study for the first time the effect of fitting on Fourierconjugate (e.g. power spectrum) on the covariance matrix of the Fourier counterpart (e.g. correlation function). We estimate theuncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the differentcovariance matrices. Nevertheless, for most studied scales the scatter is between 2 and 10 per cent. Consequently, using thecurrent pipeline we can precisely reproduce the clustering of N-body simulations and the resulting covariance matrices providerobust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESIdata analyses and their extension for other studies
The DESI One-Percent survey: constructing galaxy-halo connections for ELGs and LRGs using auto and cross correlations
In the current Dark Energy Spectroscopic Instrument (DESI) survey, emission
line galaxies (ELGs) and luminous red galaxies (LRGs) are essential for mapping
the dark matter distribution at . We measure the auto and cross
correlation functions of ELGs and LRGs at from the DESI
One-Percent survey. Following Gao et al. (2022), we construct the galaxy-halo
connections for ELGs and LRGs simultaneously. With the stellar-halo mass
relation (SHMR) for the whole galaxy population (i.e. normal galaxies), LRGs
can be selected directly by stellar mass, while ELGs can also be selected
randomly based on the observed number density of each stellar mass, once the
probability of a satellite galaxy becoming an ELG is
determined. We demonstrate that the observed small scale clustering prefers a
halo mass-dependent model rather than a constant. With this
model, we can well reproduce the auto correlations of LRGs and the cross
correlations between LRGs and ELGs at
. We can also reproduce the auto correlations of ELGs at
( ) in
real (redshift) space. Although our model has only seven parameters, we show
that it can be extended to higher redshifts and reproduces the observed auto
correlations of ELGs in the whole range of , which enables us to
generate a lightcone ELG mock for DESI. With the above model, we further derive
halo occupation distributions (HODs) for ELGs which can be used to produce ELG
mocks in coarse simulations without resolving subhalos.Comment: 27 pages, 16 figures, accepted by Ap
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
April to May 2021, 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
magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface
brightness and color selected BGS Faint sample over . We derive pSMFs
from posteriors of stellar mass, , inferred from DESI photometry and
spectroscopy using the Hahn et al. (2022a; arXiv:2202.01809) PRObabilistic
Value-Added BGS (PROVABGS) Bayesian SED modeling framework. We use a
hierarchical population inference framework that statistically and rigorously
propagates the 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.Comment: 25 pages, 12 figures; data used to generate figures is available at
https://doi.org/10.5281/zenodo.8018936; submitted to Ap
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 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
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
Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for Early DESI data
We present an extended validation of semi-analytical, semi-empirical
covariance matrices for the two-point correlation function (2PCF) on simulated
catalogs representative of Luminous Red Galaxies (LRG) data collected during
the initial two months of operations of the Stage-IV ground-based Dark Energy
Spectroscopic Instrument (DESI). We run the pipeline on multiple extended
Zel'dovich (EZ) mock galaxy catalogs with the corresponding cuts applied and
compare the results with the mock sample covariance to assess the accuracy and
its fluctuations. We propose an extension of the previously developed formalism
for catalogs processed with standard reconstruction algorithms. We consider
methods for comparing covariance matrices in detail, highlighting their
interpretation and statistical properties caused by sample variance, in
particular, nontrivial expectation values of certain metrics even when the
external covariance estimate is perfect. With improved mocks and validation
techniques, we confirm a good agreement between our predictions and sample
covariance. This allows one to generate covariance matrices for comparable
datasets without the need to create numerous mock galaxy catalogs with matching
clustering, only requiring 2PCF measurements from the data itself. The code
used in this paper is publicly available at
https://github.com/oliverphilcox/RascalC.Comment: 19 pages, 1 figure. Code available at
https://github.com/oliverphilcox/RascalC, table and figure data available at
https://dx.doi.org/10.5281/zenodo.775063
The DESI One-Percent Survey: Exploring the Halo Occupation Distribution of Luminous Red Galaxies and Quasi-Stellar Objects with AbacusSummit
We present the first comprehensive Halo Occupation Distribution (HOD)
analysis of the 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 Mpc/h 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 fsat = 11+-1%, a mean halo mass of log10 Mh =
13.40+0.02-0.02, and a linear bias of blin = 1.93+0.06-0.04. For LRGs in 0.6 <
z < 0.8, we find fsat = 14+-1%, log10 Mh = 13.24+0.02-0.02, and blin =
2.08+0.03-0.03. For QSOs, we infer fsat = 3+8-2%, log10 Mh = 12.65+0.09-0.04,
and blin = 2.63+0.37-0.26 in redshift range 0.8 < z < 2.1. Using these fits, we
generate a large suite of high-fidelity galaxy mocks. We also study the
redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealing
significant and interesting trends in mean halo mass, linear bias, and
satellite fraction.Comment: Submitted to MNRAS, comments welcom
Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies
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 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 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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