arXiv subjects

Zhejie Ding

Publications and source records attributed to Zhejie Ding.

18 recordsLinked to original sources

arXiv2026

The Effect of Slitless Spectroscopic Redshift Uncertainty and Interlopers on BAO Measurements from CSST-like Samples

The baryon acoustic oscillations (BAO) is a vital probe to measure cosmological distances and constrain dark energy. The ongoing and near-future space-based telescopes, including the Chinese Space Station Survey Telescope (CSST), will perform galaxy redshift surveys using slitless spectroscopy. Due to the relatively low spectral resolution and observational effects, there will be uncertainties and interloper contamination in measured redshifts. In this study, we consider the Gaussian-distributed redshift uncertainty and [O III]-H$β$ interlopers in the CSST-like slitless spectroscopic redshift (spec-z) samples, which are simulated using the approximate $N$-body code FastPM. We study the effect of spec-z errors on BAO before and after density field reconstruction. Both the redshift uncertainty and interlopers can damp the BAO signal, and the latter can further induce oscillations in the broadband shape of the power spectrum. We model the interloper effect on the propagator, i.e. the cross-correlation between the observed and initial density fields, as well as on the BAO power spectrum. We study the influence of the spec-z errors on the fitted anisotropic BAO parameters $α_{\perp}$ and $α_{\parallel}$. The resulting systematic bias on $α_{\perp}$ and $α_{\parallel}$ is mild, mostly within $0.1$ per cent and $0.2$ per cent, respectively. Even with the spec-z errors, BAO reconstruction can still significantly reduce the systematic bias and statistical errors on the $α$ parameters. Furthermore, we vary the redshift uncertainty and study the reconstruction performance.

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arXiv2026

Weak Evolution of Cosmic Atomic Hydrogen over the Past 4.5 Billion Years

The cosmic star formation rate density (CSFRD) has declined sharply toward the present day, but the roles of the atomic and molecular gas reservoirs remain uncertain. We measure the cosmic HI density, $Ω_{\mathrm{HI}}$, over $0<z<0.41$ by combining HI spectra from the Five-hundred-meter Aperture Spherical Telescope with optical spectroscopy from the Dark Energy Spectroscopic Instrument for $\sim2.5$ million galaxies across $\sim12,000\,{\rm deg}^2$. We measure a raw decrease in $Ω_{\mathrm{HI}}$ by a factor of $1.35\pm0.10$ over the past 4.5 Gyr. Even after applying the conservative systematic corrections from our forward model, the inferred decline is only $1.12\pm0.10$ -- still far weaker than the CSFRD decline (a factor of 2.46). The molecular gas density, in contrast, is known to evolve more closely with star formation. At fixed stellar mass, the average HI gas fraction evolves by less than 0.2 dex, showing that the weak evolution is present across the galaxy population. These quantitative differences rule out rapid depletion of galaxy HI as the primary driver of the late-time CSFRD decline, and provide a stringent benchmark for models of gas accretion, phase conversion and star-formation regulation.

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arXiv2026

Optimization of Tessellation-based Statistics: Void Statistics

Tessellation methods are extensively employed in the analyses of cosmic large-scale structure (LSS). However, these techniques are highly sensitive to perturbations in both densities and positions of points, often leading to substantial rearrangements of tessellation configurations. As a result, considerable additional statistical errors are introduced in various tessellation-based statistics, thereby weakening their cosmological constraints. In this work, we identify this issue and propose an efficacious measurement scheme through subsampling and averaging to enhance the stabilities of tessellation-based statistics. As a case study, we apply the new scheme to measure multiple primary void statistics [i.e., void size function (VSF), void two-point correlation function (VTCF), and void power spectrum (VPS)] in two distinct classes of voids, based on Delaunay and Voronoi tessellations, respectively. We notice that the statistical uncertainties in void statistics can be predominantly attributed to tessellation instabilities. Through rigorous testing, we demonstrate that the proposed method can substantially eliminate these scatters to deeply mine the statistical power of void statistics. Specifically, we find that our method can dramatically boost the signal-to-noise ratios (SNRs) of void Baryon Acoustic Oscillations (BAOs) and significantly improve the constraining power of void statistics on cosmological parameters. These findings showcase enormous application potentials of our new method in maximizing extraction of cosmological information from galaxy surveys. Importantly, our method is simple yet highly potent with broad applicability, hopefully evolving into a standard framework for measuring tessellation-based statistics in the future.

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arXiv2025

DESI DR1 Lyα 1D power spectrum: The Fast Fourier Transform estimator measurement

We present the one-dimensional Lyman-$α$ forest power spectrum measurement derived from the data release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI). The measurement of the Lyman-$α$ forest power spectrum along the line of sight from high-redshift quasar spectra provides information on the shape of the linear matter power spectrum, neutrino masses, and the properties of dark matter. In this work, we use a Fast Fourier Transform (FFT)-based estimator, which is validated on synthetic data in a companion paper. Compared to the FFT measurement performed on the DESI early data release, we improve the noise characterization with a cross-exposure estimator and test the robustness of our measurement using various data splits. We also refine the estimation of the uncertainties and now present an estimator for the covariance matrix of the measurement. Furthermore, we compare our results to previous high-resolution and eBOSS measurements. In another companion paper, we present the same DR1 measurement using the Quadratic Maximum Likelihood Estimator (QMLE). These two measurements are consistent with each other and constitute the most precise one-dimensional power spectrum measurement to date, while being in good agreement with results from the DESI early data release.

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arXiv2025

DarkAI: Reconstructing the density, velocity and tidal field of dark matter from a DESI-like bright galaxy sample

Reconstructing the mass density, velocity, and tidal (MTV) fields of dark matter from galaxy surveys is essential for advancing our understanding of the LSS of the Universe. In this work, we present a machine learning-based framework using a UNet convolutional neural network to reconstruct the MTV fields from mock samples of the DESI bright galaxy survey within the redshift range $0.1 < z < 0.4$. Our approach accounts for realistic observational effects, including geometric selection, flux-limited data, and redshift space distortion (RSD) effects, thereby improving the fidelity of the reconstructed fields. Testing on mock galaxy catalogs generated from the Jiutian N-body simulation, our method achieves significant accuracy level. The reconstructed density field exhibits strong consistency with the true field, effectively eliminating most RSD effects and achieving a cross-correlation power spectrum coefficient greater than 0.985 on scales with $k < 0.1 \, h \, \mathrm{Mpc}^{-1}$. The velocity field reconstruction accurately captures large-scale coherent flows and small-scale turbulent features, exhibiting slopes of grid-to-grid relationships close to unity and scatter below $\sim$100 $\mathrm{km} \, \mathrm{s}^{-1}$. Additionally, the tidal field is reconstructed without bias, successfully recovering the features of the large-scale cosmic web, including clusters, filaments, sheets, and voids. Our results confirm that the proposed framework effectively captures the large-scale distribution and dynamics of dark matter while addressing key systematic challenges. These advancements provide a reliable and robust tool for analyzing current and future galaxy surveys, paving the way for new insights into cosmic structure formation and evolution.

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arXiv2025

Analytical and EZmock covariance validation for the DESI 2024 results

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full Shape, two approaches are usually considered. First: analytical estimates of the covariance matrix use Gaussian approximations and (nonlinear) clustering measurements to estimate the matrix, which allows a relatively fast and computationally cheap way to generate matrices that adapt to an arbitrary clustering measurement. On the other hand, sample covariances are an empirical estimate of the matrix based on en ensemble of clustering measurements from fast and approximate simulations. While more computationally expensive due to the large amount of simulations and volume required, these allow us to take into account systematics that are impossible to model analytically. In this work we compare these two approaches in order to enable DESI's key analyses. We find that the configuration space analytical estimate performs satisfactorily in BAO analyses and its flexibility in terms of input clustering makes it the fiducial choice for DESI's 2024 BAO analysis. On the contrary, the analytical computation of the covariance matrix in Fourier space does not reproduce the expected measurements in terms of Full Shape analyses, which motivates the use of a corrected mock covariance for DESI's Full Shape analysis.

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arXiv2025

Studying baryon acoustic oscillations using photometric redshifts from the DESI Legacy Imaging survey DR9

Context.The Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Survey DR9 (DR9 hereafter), with its extensive dataset of galaxy locations and photometric redshifts, presents an opportunity to study baryon acoustic oscillations (BAOs) in the region covered by the ongoing spectroscopic survey with DESI. Aims. We aim to investigate differences between different parts of the DR9 footprint. Furthermore, we want to measure the BAO scale for luminous red galaxies within them. Our selected redshift range of 0.6 to 0.8 corresponds to the bin in which a tension between DESI Y1 and eBOSS was found. Methods. We calculated the anisotropic two-point correlation function in a modified binning scheme to detect the BAOs in DR9 data. We then used template fits based on simulations to measure the BAO scale in the imaging data. Results. Our analysis reveals the expected correlation function shape in most of the footprint areas, showing a BAO scale consistent with Planck's observations. Aside from identified mask-related data issues in the southern region of the South Galactic Cap, we find a notable variance between the different footprints. Conclusions. We find that this variance is consistent with the difference between the DESI Y1 and eBOSS data, and it supports the argument that that tension is caused by sample variance. Additionally, we also uncovered systematic biases not previously accounted for in photometric BAO studies. We emphasize the necessity of adjusting for the systematic shift in the BAO scale associated with typical photometric redshift uncertainties to ensure accurate measurements.

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arXiv2025

Cosmological distance forecasts for the CSST Galaxy Survey using BAO peaks

The measurement of cosmological distances using baryon acoustic oscillations (BAO) is crucial for studying the universe's expansion. The Chinese Space Station Telescope (CSST) galaxy redshift survey, with its vast volume and sky coverage, provides an opportunity to address key challenges in cosmology. However, redshift uncertainties in galaxy surveys can degrade both angular and radial distance estimates. In this study, we forecast the precision of BAO distance measurements using mock CSST galaxy samples, applying a two-point correlation function (2PCF) wedge approach to mitigate redshift errors. We simulate redshift uncertainties of $σ_0 = 0.003$ and $σ_0 = 0.006$, representative of expected CSST errors, and examine their effects on the BAO peak and distance scaling factors, $α_\perp$ and $α_\parallel$, across redshift bins within $0.0 < z \leqslant 1.0$. The wedge 2PCF method proves more effective in detecting the BAO peak compared to the monopole 2PCF, particularly for $σ_0 = 0.006$. Constraints on the BAO peaks show that $α_\perp$ is well constrained around 1.0, regardless of $σ_0$, with precision between 1% and 3% across redshift bins. In contrast, $α_\parallel$ measurements are more sensitive to increases in $σ_0$. For $σ_0 = 0.003$, the results remain close to the fiducial value, with uncertainties ranging between 4% and 9%; for $σ_0 = 0.006$, significant deviations from the fiducial value are observed. We also study the ability to measure parameters $(Ω_m, H_0r_\mathrm{d})$ using distance measurements, proving robust constraints as a cosmological probe under CSST-like redshift uncertainties.

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arXiv2024

The role of LRG1 and LRG2's monopole in inferring the DESI 2024 BAO cosmology

The Dark Energy Spectroscopic Instrument (DESI) collaboration recently released its first year of data (DR1) on baryon acoustic oscillations (BAO) in galaxy, quasar, and Lyman-$α$ forest tracers. When combined with CMB and SNIa data, DESI BAO results suggest potential thawing behavior in dark energy. Cosmological analyses utilize comoving distances along ($D_H$) and perpendicular to ($D_M$) the line of sight. Notably, there are $1\sim2σ$ deviations in $D_M$ and $D_H$ from Planck cosmology values in the luminous red galaxies (LRG) bins LRG1 and LRG2.This study examines the role of LRG1 and LRG2 in diverging DESI 2024 BAO cosmology from Planck cosmology. We use angle-averaged distance $D_V$ and the ratio $F_{\rm AP}=D_M/D_H$, which are more directly related to the measured monopole and quadrupole components of the galaxy power spectrum or correlation function, instead of the officially adopted $D_M$ and $D_H$. This transformation aims to isolate the influence of monopoles in LRG1 and LRG2 on deviations from $w=-1$. Our findings indicate that removing the $D_V$ data point in LRG2 aligns DESI + CMB + SNIa data compilation with $w=-1$ within a $2σ$ contour and reduces the $H_0$ discrepancy from the Planck 2018 results from $0.63σ$ to $0.31σ$. Similarly, excluding the $D_V$ data point from LRG1 shifts the $w_0/w_a$ contour toward $w=-1$, although no intersection occurs. This highlights the preference of both LRG1 and LRG2 BAO monopole components for the thawing dark energy model, with LRG2 showing a stronger preference. We provide the $D_V$ and $F_{\rm AP}$ data and their covariance alongside this paper.

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arXiv2024

The effective volume of supernovae samples and sample variance

The source of the tension between local SN Ia based Hubble constant measurements and those from the CMB or BAO+BBN measurements is one of the most interesting unknowns of modern cosmology. Sample variance forms a key component of the error on the local measurements, and will dominate the error budget in the future as more SNe Ia are observed. Many methods have been proposed to estimate sample variance in many contexts, and we compared results from a number of approximate methods to estimates from N-body simulations in a previous paper, confirming that sample variance for the Pantheon SNe Ia sample does not solve the Hubble tension. We now extend this analysis to include the more accurate analytic method based on calculating correlations between the radial peculiar velocities of SNe Ia, comparing this technique with results from numerical simulations. We consider the dependence of these errors on the linear power spectrum and how non-linear velocities contribute to the error. Using this technique, and matching sample variance errors from more approximate methods, we can define an effective volume for SNe Ia samples, finding that the Pantheon sample is equivalent to a top-hat sphere of radius $\sim220~h^{-1}$Mpc. We use this link between sample-variance errors to compute $ΔH_{0}$ for idealised surveys with particular angular distributions of SNe Ia. For example, a half-sky survey at the Pantheon depth has the potential to suppress the sample variance of $H_{0}$ to $\sim0.1$ km s$^{-1}$Mpc$^{-1}$, a significant improvement compared with the current result. Finally, we consider the strength of large-scale velocity power spectrum required to explain the Hubble tension using sample variance, finding it requires an extreme model well beyond that allowed by other observations.

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arXiv2023

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 \textsc{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. $k<0.5\,h\mathrm{Mpc}$ or $s>10\,\mathrm{Mpc}/h$. Furthermore, we compute covariance matrices based on the resulting \textsc{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 two to ten 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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arXiv2023

Fisher forecast for the BAO measurements from the CSST spectroscopic and photometric galaxy clustering

The China Space Station Telescope (CSST) is a forthcoming Stage IV galaxy survey. It will simultaneously undertake the photometric redshift (photo-z) and slitless spectroscopic redshift (spec-z) surveys mainly for weak lensing and galaxy clustering studies. The two surveys cover the same sky area and overlap on the redshift range. At $z>1$, due to the sparse number density of the spec-z sample, it limits the constraints on the scale of baryon acoustic oscillations (BAO). By cross-correlating the spec-z sample with the high density photo-z sample, we can effectively enhance the constraints on the angular diameter distances $D_A(z)$ from the BAO measurement. Based on the Fisher matrix, we forecast a $\geq$ 30 per cent improvement on constraining $D_A(z)$ from the joint analysis of the spec-z and cross galaxy power spectra at $1.0<z<1.2$. Such improvement is generally robust against different systematic effects including the systematic noise and the redshift success rate of the spec-z survey, as well as the photo-z error. We also show the BAO constraints from other Stage-IV spectroscopic surveys for the comparison with CSST. Our study can be a reference for the future BAO analysis on real CSST data. The methodology can be applied to other surveys with spec-z and photo-z data in the same survey volume.

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arXiv2022

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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arXiv2019

Detecting Baryon Acoustic Oscillations in Dark Matter from Kinematic Weak Lensing Surveys

We investigate the feasibility of extracting Baryon Acoustic Oscillations (BAO) from cosmic shear tomography. We particularly focus on the BAO scale precision that can be achieved by future spectroscopy-based, kinematic weak lensing (KWL) surveys \citep[e.g.,][]{Huff13} in comparison to the traditional photometry-based weak lensing surveys. We simulate cosmic shear tomography data of such surveys with a few simple assumptions to focus on the BAO information, extract the spacial power spectrum, and constrain the recovered BAO feature. Due to the small shape noise and the shape of the lensing kernel, we find that a Dark Energy Task Force Stage IV version of such KWL survey can detect the BAO feature in dark matter by $3$-$σ$ and measure the BAO scale at the precision level of 4\% while it will be difficult to detect the feature in photometry-based weak lensing surveys. With a more optimistic assumption, a KWL-Stage IV could achieve a $\sim 2\%$ BAO scale measurement with $4.9$-$σ$ confidence. A built-in spectroscopic galaxy survey within such KWL survey will allow cross-correlation between galaxies and cosmic shear, which will tighten the constraint beyond the lower limit we present in this paper and therefore possibly allow a detection of the BAO scale bias between galaxies and dark matter.

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arXiv2019

Overview of the DESI Legacy Imaging Surveys

The DESI Legacy Imaging Surveys are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Survey) that will jointly image approximately 14,000 deg^2 of the extragalactic sky visible from the northern hemisphere in three optical bands (g, r, and z) using telescopes at the Kitt Peak National Observatory and the Cerro Tololo Inter-American Observatory. The combined survey footprint is split into two contiguous areas by the Galactic plane. The optical imaging is conducted using a unique strategy of dynamically adjusting the exposure times and pointing selection during observing that results in a survey of nearly uniform depth. In addition to calibrated images, the project is delivering a catalog, constructed by using a probabilistic inference-based approach to estimate source shapes and brightnesses. The catalog includes photometry from the grz optical bands and from four mid-infrared bands (at 3.4, 4.6, 12 and 22 micorons) observed by the Wide-field Infrared Survey Explorer (WISE) satellite during its full operational lifetime. The project plans two public data releases each year. All the software used to generate the catalogs is also released with the data. This paper provides an overview of the Legacy Surveys project.

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arXiv2018

Theoretical Systematics of Future Baryon Acoustic Oscillation Surveys

Future Baryon Acoustic Oscillation surveys aim at observing galaxy clustering over a wide range of redshift and galaxy populations at great precision, reaching tenths of a percent, in order to detect any deviation of dark energy from the $\LCDM$ model. We utilize a set of paired quasi-\Nb\, FastPM simulations that were designed to mitigate the sample variance effect on the BAO feature and evaluated the BAO systematics as precisely as $\sim 0.01\%$. We report anisotropic BAO scale shifts before and after density field reconstruction in the presence of redshift-space distortions over a wide range of redshift, galaxy/halo biases, and shot noise levels. We test different reconstruction schemes and different smoothing filter scales, and introduce physically-motivated BAO fitting models. For the first time, we derive a Galilean-invariant infrared resummed model for halos in real and redshift space. We test these models from the perspective of robust BAO measurements and non-BAO information such as growth rate and nonlinear bias. We find that pre-reconstruction BAO scale has moderate fitting-model dependence at the level of $0.1\%-0.2\%$ for matter while the dependence is substantially reduced to less than $0.07\%$ for halos. We find that post-reconstruction BAO shifts are generally reduced to below $0.1\%$ in the presence of galaxy/halo bias and show much smaller fitting model dependence. Different reconstruction conventions can potentially make a much larger difference on the line-of-sight BAO scale, upto $0.3\%$. Meanwhile, the precision (error) of the BAO measurements is quite consistent regardless of the choice of the fitting model or reconstruction convention.

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arXiv2016

The DESI Experiment Part I: Science,Targeting, and Survey Design

DESI (Dark Energy Spectroscopic Instrument) is a Stage IV ground-based dark energy experiment that will study baryon acoustic oscillations (BAO) and the growth of structure through redshift-space distortions with a wide-area galaxy and quasar redshift survey. To trace the underlying dark matter distribution, spectroscopic targets will be selected in four classes from imaging data. We will measure luminous red galaxies up to $z=1.0$. To probe the Universe out to even higher redshift, DESI will target bright [O II] emission line galaxies up to $z=1.7$. Quasars will be targeted both as direct tracers of the underlying dark matter distribution and, at higher redshifts ($ 2.1 < z < 3.5$), for the Ly-$α$ forest absorption features in their spectra, which will be used to trace the distribution of neutral hydrogen. When moonlight prevents efficient observations of the faint targets of the baseline survey, DESI will conduct a magnitude-limited Bright Galaxy Survey comprising approximately 10 million galaxies with a median $z\approx 0.2$. In total, more than 30 million galaxy and quasar redshifts will be obtained to measure the BAO feature and determine the matter power spectrum, including redshift space distortions.

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arXiv2016

The DESI Experiment Part II: Instrument Design

DESI (Dark Energy Spectropic Instrument) is a Stage IV ground-based dark energy experiment that will study baryon acoustic oscillations and the growth of structure through redshift-space distortions with a wide-area galaxy and quasar redshift survey. The DESI instrument is a robotically-actuated, fiber-fed spectrograph capable of taking up to 5,000 simultaneous spectra over a wavelength range from 360 nm to 980 nm. The fibers feed ten three-arm spectrographs with resolution $R= λ/Δλ$ between 2000 and 5500, depending on wavelength. The DESI instrument will be used to conduct a five-year survey designed to cover 14,000 deg$^2$. This powerful instrument will be installed at prime focus on the 4-m Mayall telescope in Kitt Peak, Arizona, along with a new optical corrector, which will provide a three-degree diameter field of view. The DESI collaboration will also deliver a spectroscopic pipeline and data management system to reduce and archive all data for eventual public use.

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