arXiv subjects

Pengjie Zhang

Publications and source records attributed to Pengjie Zhang.

At least 37 records · Page 2Linked to original sources

arXiv2025

AKRA 2.0: Accurate Kappa Reconstruction Algorithm for masked shear catalog

Cosmic shear surveys serve as a powerful tool for mapping the underlying matter density field, including non-visible dark matter. A key challenge in cosmic shear surveys is the accurate reconstruction of lensing convergence ($κ$) maps from shear catalogs impacted by survey boundaries and masks, which seminal Kaiser-Squires (KS) method are not designed to handle. To overcome these limitations, we previously proposed the Accurate Kappa Reconstruction Algorithm (AKRA), a prior-free maximum likelihood map-making method. Initially designed for flat sky scenarios with periodic boundary conditions, AKRA has proven successful in recovering high-precision $κ$ maps from masked shear catalogs. In this work, we upgrade AKRA to AKRA 2.0 by integrating the tools designed for spherical geometry. This upgrade employs spin-weighted spherical harmonic transforms to reconstruct the convergence field over the full sky. To optimize computational efficiency, we implement a scale-splitting strategy that segregates the analysis into two parts: large-scale analysis on the sphere (referred to as AKRA-sphere) and small-scale analysis on the flat sky (referred to as AKRA-flat); the results from both analyses are then combined to produce final reconstructed $κ$ map. We tested AKRA 2.0 using simulated shear catalogs with various masks, demonstrating that the reconstructed $κ$ map by AKRA 2.0 maintains high accuracy. For the reconstructed $κ$ map in unmasked regions, the reconstructed convergence power spectrum $C_κ^{\rm{rec}}$ and the correlation coefficient with the true $κ$ map $r_\ell$ achieve accuracies of $(1-C_\ell^{\rm{rec}}/C_\ell^{\rm{true}}) \lesssim 1\%$ and $(1-r_\ell) \lesssim 1\%$, respectively. Our algorithm is capable of straightforwardly handling further issues such as inhomogeneous shape measurement noise, which we will address in subsequent analysis.

astro-ph.IM↗

arXiv2025

Meta-Calibration of the Cosmic Magnification Coefficient: Toward Unbiased Weak Lensing Reconstruction by Counting Galaxies

Weak lensing alters galaxy sizes and fluxes, influencing the clustering patterns of galaxies through cosmic magnification. This effect enables the reconstruction of weak lensing convergence $\hatκ$ maps for DES and DECaLS by linearly combining galaxy overdensities across magnitude bins in the $g$, $r$, and $z$ photometry bands \citep{Qin+,Qin2+}. In this study, we enhance the lensing reconstruction method by addressing biases in the magnification coefficient estimation, which arise from incomplete consideration of selection effects, especially those induced by photometric redshift (photo-$z$) selection. Using a Random Forest-based photo-$z$ estimation for DECaLS and DES galaxies, we quantify the impact of photo-$z$ induced selection on magnification coefficient estimation. Our results show that neglecting photo-$z$ selection introduces significant biases in the magnification coefficient, leading to deviations in the reconstructed convergence map amplitude $A$, with values ranging from 0.4 to 3.5 depending on the survey, redshift, and magnitude cuts. By incorporating an improved magnification coefficient estimation that accounts for photo-$z$ selection, these biases are significantly reduced, with $A$ converging to $\sim 1$ as the magnitude cuts approach optimal values. This improvement is consistently observed across DES and DECaLS datasets and redshift bins, despite differences in survey strategies and depths. Our findings highlight the importance of addressing photo-$z$ induced selection to achieve unbiased weak lensing reconstructions and accurate cosmic magnification measurements.

astro-ph.CO↗

arXiv2025

CSST Large Scale Structure Analysis Pipeline: III. Emission-line Redshift Measurement for Slitless Spectra

The China Space Station Telescope (CSST) is a forthcoming space-based optical telescope designed to co-orbit with the Chinese Space Station. With a planned slitless spectroscopic survey spanning a broad wavelength range of $255-1000$nm and an average spectral resolution exceeding 200, the CSST holds significant potential for cosmic large-scale structure analysis. In this study, we focus on redshift determinations from slitless spectra through emission line analysis within the CSST framework. Our tailored redshift measurement process involves identifying emission lines in one-dimensional slitless spectra, aligning observed wavelengths with their rest-frame counterparts from prominent galaxy emissions, and calculating wavelength shifts to determine redshifts accurately. To validate our redshift measurement algorithm, we leverage simulated spectra generated by the CSST emulator for slitless spectroscopy. The outcomes demonstrate a remarkable redshift completeness exceeding 95 per cent for emission line galaxies (ELGs), alongside a purity surpassing 85 per cent. The redshift uncertainty remains impressively below than $\sim 0.001$. Notably, when concentrating on galaxies with more than three matched emission lines, the completeness of ELGs and the purity of measurable galaxies can reach 98 per cent and 97 per cent, respectively. Furthermore, we explore the influence of parameters like magnitude, spectral signal-to-noise ratio, and redshift on redshift completeness and purity. The discussion also delves into redshift degeneracies stemming from emission-line matching confusion. Our developed redshift measurement process will be applied to extensive simulated datasets and forthcoming CSST slitless spectroscopic observations for further cosmological and extragalactic analyses.

astro-ph.CO↗

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.

astro-ph.CO↗

arXiv2024

A dark energy parameterization independent constraint of the spatial curvature $Ω_K$

Determining the spatial curvature $Ω_K$ of the Universe has long been crucial in cosmology. In practice, this effort is often entangled with assumptions of dark energy. A combination of distance ($D_{\rm M}$, $D_{\rm L}$) and expansion rate ($H(z)$) measurements can break this degeneracy. However, fitting against discrete data points requires parameterizations of distance and expansion rate as functions of redshifts, which often induces cosmological model dependence. In this work, we propose a new dark energy model-independent parameterization of the cosmological comoving radial distance $χ$. Fitting data combining distance ($D_{\rm M}$, $D_{\rm L}$) and Hubble parameter (or equivalently $D_H$) measurements, we are then able to obtain $Ω_K$ in a dark energy model-independent manner. We test this parameterization and the associated fitting scheme with mock data generated with a wide range of fiducial dark energy equations of state ($-1.3<w<1.3$), finding that the best-fit $Ω_K$ is always unbiased. Then we combine SDSS Baryon Acoustic Oscillation (BAO), Pantheon+ sample of Type Ia Supernovae (SNe Ia), and Observational Hubble Data (OHD) to constrain $Ω_K$. We find a flat universe with $Ω_K=-0.01\pm 0.09$. Most constraining power is contributed by SDSS BAO, with the BAO-alone constraint $Ω_K=-0.03 \pm 0.10$. When replacing SDSS BAO with DESI year-one BAO measurement, we obtain $Ω_K=0.06 \pm 0.08$. With the full DESI BAO data alone, we forecast $σ(Ω_K)\sim 0.03$. Our result verifies the flatness of the universe free of dark energy modeling, and the proposed parameterization would be useful for future investigation of $Ω_K$ and other parameters of interest, such as the horizon radius.

astro-ph.CO↗

arXiv2024

Weak Lensing Reconstruction by Counting DECaLS Galaxies

Alternative to weak lensing measurements through cosmic shear, we present a weak lensing convergence $\hatκ$ map reconstructed through cosmic magnification effect in DECaLS galaxies of the DESI imaging surveys DR9. This is achieved by linearly weighing $12$ maps of galaxy number overdensity in different magnitude bins of $grz$ photometry bands. The weight is designed to eliminate the mean galaxy deterministic bias, minimize galaxy shot noise while maintaining the lensing convergence signal. We also perform corrections of imaging systematics in the galaxy number overdensity. The $\hatκ$ map has $8365$ deg$^2$ sky coverage. Given the low number density of DECaLS galaxies, the $\hatκ$ map is overwhelmed by shot noise and the map quality is difficult to evaluate using the lensing auto-correlation. Alternatively, we measure its cross-correlation with the cosmic shear catalogs of DECaLS galaxies of DESI imaging surveys DR8, which has $8365$ deg$^2$ overlap in sky coverage with the $\hatκ$ map. We detect a convergence-shear cross-correlation signal with $S/N\simeq 10$. The analysis also shows that the galaxy intrinsic clustering is suppressed by a factor $\mathcal{O}(10^2)$ and the residual galaxy clustering contamination in the $\hatκ$ map is consistent with zero. Various tests with different galaxy and shear samples, and the Akaike information criterion analysis all support the lensing detection. So is the imaging systematics corrections, which enhance the lensing signal detection by $\sim 30\%$. We discuss various issues for further improvement of the measurements.

astro-ph.CO↗

arXiv2024

Weak Lensing Reconstruction by Counting Galaxies: Improvement with DES Y3 Galaxies

In \citep{Qin+}, we attempted to reconstruct the weak lensing convergence map $\hatκ$ from cosmic magnification by linearly weighting the DECaLS galaxy overdensities in different magnitude bins of $grz$ photometry bands. The $\hatκ$ map is correlated with cosmic shear at 20-$σ$ significance. However, the low galaxy number density in the DECaLS survey prohibits the measurement of $\hatκ$ auto-correlation. In this paper, we apply the reconstruction method to the Dark Energy Survey Year 3 (DES Y3) galaxies from the DES Data Release 2 (DR2). With greater survey depth and higher galaxy number density, convergence-shear cross-correlation signals are detected with $S/N\approx 9,16,20$ at $0.4<z_κ<0.6,0.6<z_κ<0.8$ and $0.8<z_κ<1.0$ respectively. More remarkably, the $\hatκ-\hatκ$ correlations of the $0.4<z_κ<0.6$ and $0.6<z_κ<0.8$ bins show reasonably good agreement with predictions based on theoretical interpretation of $\hatκ-γ$ measurement. This result takes a step further towards the cosmological application of our lensing reconstruction method.

astro-ph.CO↗

arXiv2024

Parameterization of Stochasticity in Galaxy Clustering and Reconstruction of Tomographic Matter Clustering

The stochasticity in galaxy clustering, the mismatch between galaxy and underlying matter distribution, suppresses the matter clustering amplitude reconstructed by the combination of galaxy auto-correlation and galaxy-galaxy lensing cross-correlation. In this work, we solve the stochasticity systematics by parameterizing the cross correlation coefficient $r(k)$ between galaxy and matter. We investigate the performance of 12 kinds of parameterization schemes, against the cosmoDC2 $\&$ TNG300-1 galaxy samples over a wide range of redshift and flux cut. The 2-parameter fits are found to describe the stochasticity up to $k_{\rm max}=0.9\,{\rm Mpc^{-1}}h$, while the best performing quadratic scheme $r^2_s(k) = 1+c_1 k+c_2 k^2$ reaches better than $1\%$ accuracy for both the direct ${r}^2_s(k)$ fit and reconstructing matter clustering. Then, we apply the accurate quadratic scheme to forecast the tomographic matter clustering reconstruction by the combination DESI-like LRG $\times$ CSST-like cosmic shear. Depending on assumption of stochasticity, we find that the neglect of a serious stochasticity would result in significant systematic bias in both the reconstruction and the inferred cosmological parameters, even if we adopt scale cut $k_{\rm max}=0.1\,{\rm Mpc^{-1}}h$. We demonstrate the necessity of including stochasticity in reconstruction, and forecast that the reconstruction alone enables a $S_8$ constraint at about $1.5\%$ precision, free from galaxy bias and stochasticity. We will validate our method for DESI spectroscopic survey, and the analysis is expected to be complementary to DESI cosmological constraint by BAO and RSD.

astro-ph.CO↗

arXiv2024

EMatch: A Unified Framework for Event-based Optical Flow and Stereo Matching

Event cameras have shown promise in vision applications like optical flow estimation and stereo matching, with many specialized architectures leveraging the asynchronous and sparse nature of event data. However, existing works only focus event data within the confines of task-specific domains, overlooking how tasks across the temporal and spatial domains can reinforce each other. In this paper, we reformulate event-based flow estimation and stereo matching as a unified dense correspondence matching problem, enabling us to solve both tasks within a single model by directly matching features in a shared representation space. Specifically, our method utilizes a Temporal Recurrent Network to aggregate event features across temporal or spatial domains, and a Spatial Contextual Attention to enhance knowledge transfer across event flows via temporal or spatial interactions. By utilizing a shared feature similarities module that integrates knowledge from event streams via temporal or spatial interactions, our network performs optical flow estimation from temporal event segment inputs and stereo matching from spatial event segment inputs simultaneously. We demonstrate that our unified model inherently supports multi-task fusion and cross-task transfer. Without the need for retraining for specific task, our model can effectively handle both optical flow and stereo estimation, achieving state-of-the-art performance on both tasks.

cs.CV↗

arXiv2024

The direct measurement of gravitational potential decay rate at cosmological scales II -- Improved dark energy constraint from $z\le1.4$

The gravitational potential decay rate (DR) is caused by the cosmic acceleration of the universe, providing a direct probe into the existence of dark energy (DE). We present measurements of DR and explore its implications for DE models using the Data Release 9 galaxy catalog of DESI imaging surveys and the Planck cosmic microwave background maps. Our analysis includes six redshift bins within the range of $0.2\le z<1.4$ and achieves a total significance of 3.1$σ$, extending the DR measurements to a much higher redshift comparing to Dong et al. (2022), which focused on $0.2\le z<0.8$. Other improvements involve addressing potential systematics in the DR-related measurements of correlation functions, including imaging systematics and magnification bias. We explore the constraining power of DR both the $w$CDM model and the $w_0w_a$CDM model. We find that, the addition of DR can significantly improves DE constraints, over Sloan Digital Sky Survey baryon acoustic oscillation (BAO) data alone or PantheonPlus supernovae (SNe) compilation alone, although it shows only a modest improvement for DESI BAO. In the $w$CDM model, all three probes-DR, DESI BAO and SNe-favor $w=-1$. For the $w_0w_a$CDM, while DESI BAO prefers $w_0>-1$ and $w_a<0$, SNe Ia and DR data constrain $w_0=-0.94^{+0.11}_{-0.13}$ and $w_a=-0.22^{+0.57}_{-0.97}$. Namely SNe Ia and DR data has no preference on dynamical dark energy over $Λ$.

astro-ph.CO↗

arXiv2024

Accurately Estimating Redshifts from CSST Slitless Spectroscopic Survey using Deep Learning

Chinese Space Station Telescope (CSST) has the capability to conduct slitless spectroscopic survey simultaneously with photometric survey. The spectroscopic survey will measure slitless spectra, potentially providing more accurate estimations of galaxy properties, particularly redshifts, compared to using broadband photometry. CSST relies on these accurate redshifts to perform baryon acoustic oscilliation (BAO) and other probes to constrain the cosmological parameters. However, due to low resolution and signal-to-noise ratio of slitless spectra, measurement of redshifts is significantly challenging.} In this study, we employ a Bayesian neural network (BNN) to assess the accuracy of redshift estimations from slitless spectra anticipated to be observed by CSST. The simulation of slitless spectra is based on real observational data from the early data release of the Dark Energy Spectroscopic Instrument (DESI-EDR) and the 16th data release of the Baryon Oscillation Spectroscopic Survey (BOSS-DR16), combined with the 9th data release of the DESI Legacy Survey (DESI LS DR9). The BNN is constructed employing transfer learning technique, by appending two Bayesian layers after a convolutional neural network (CNN), leveraging the features learned from the slitless spectra and corresponding redshifts. Our network can provide redshift estimates along with corresponding uncertainties, achieving an accuracy of $σ_{\rm NMAD} = 0.00063$, outlier percentage $η=0.92\%$ and weighted mean uncertainty $\bar{E} = 0.00228$. These results successfully fulfill the requirement of $σ_{\rm NMAD} < 0.005$ for BAO and other studies employing CSST slitless spectroscopic surveys.

astro-ph.CO↗

arXiv2024

On the capability of high redshift kSZ measurement with galaxy surveys

The kSZ effect has been detected at z<1 using various techniques and data sets. The ongoing and upcoming spectroscopic galaxy surveys such as DESI and PFS will push the detection beyond z = 1, and therefore map the baryon distribution at high redshifts. Such detection can be achieved by both the kSZ stacking and tomography methods. While the two methods are theoretically equivalent, they differ significantly in the probed physics and scales, and required data sets. Taking the combination of PFS and ACT as an example, we build mocks of kSZ and galaxies, quantify the kSZ detection S/N, and compare between the two methods. We segment the PFS galaxies into three redshift bins: 0.6 < z < 1.0, 1.0 < z < 1.6, and 1.6 < z < 2.4. For tomography method, our analysis reveals that the two higher redshift bins exhibit higher S/N, with values of 32 and 28, respectively, compared to the first redshift bin (S/N = 8). This is attributed to not only the increasing of electron density with redshifts, but also the larger survey volume and the reduced non-linearity, facilitating velocity reconstruction at higher redshifts. Therefore, the capability of the PFS survey to measure high redshift kSZ effect stands as a substantial advantage over other spectroscopic surveys at lower redshift. The S/N of kSZ stacking largely depends on the number of clusters/groups available from another photometric survey. But in general, its S/N is lower than that of kSZ tomography. Incorporating next-generation CMB surveys like CMB-S4, characterized by significantly reduced instrument noise and improved angular resolution, is expected to enhance tomographic detection by a factor of ten and stacking detection by five. This future high S/N detection holds the promise of not only providing precise constraints on the overall baryon abundance but also initiating a new insight into baryon distribution.

astro-ph.CO↗

arXiv2024

Challenges in Cosmic Magnification Reconstruction by Magnification Response

Cosmic magnification on the observed galaxy overdensity is a promising weak gravitational lensing tracer. Current cosmic magnification reconstruction algorithms, ABS (Analytical method of Blind Separation) and cILC (constrained Internal Linear Combination), intend to disentangle the weak lensing signal using the magnification response in various flux bins. In this work, we reveal an unrecognized systematic bias arising from the difference between galaxy bias and the galaxy-lensing cross-correlation bias, due to the mismatch between the weak lensing kernel and the redshift distribution of photometric objects. It results into a galaxy-lensing degeneracy, which invalidates ABS as an exact solution. Based on the simulated cosmoDC2 galaxies, we verify that the recovered weak lensing amplitude by ABS is biased low by $\sim10\%$. cILC, including a modified version proposed here, also suffers from systematic bias of comparable amplitude. Combining flux and color information leads to significant reduction in statistical errors, but fails to eliminate the aforementioned bias. With the presence of this newly found systematic, it remains a severe challenge in blindly and robustly separating the cosmic magnification from the galaxy intrinsic clustering.

astro-ph.CO↗

arXiv2024

Enhancing Morphological Measurements of Cosmic Web with Delaunay Tessellation Field Estimation

The density fields constructed by traditional mass assignment methods are susceptible to irritating discreteness, which hinders morphological measurements of cosmic large-scale structure (LSS) through Minkowski functionals (MFs). For alleviating this issue, fixed-kernel smoothing methods are commonly used in literatures, at the expense of losing substantial structural information. In this work, we propose to measure MFs with Delaunay tessellation field estimation (DTFE) technique, with the goal to maximize extractions of morphological information from sparse tracers. We perform our analyses starting from matter fields and progressively extending to halo fields. At matter field level, we elucidate how discreteness affects the morphological measurements of LSS. Then, by comparing with traditional Gaussian smoothing scheme, we preliminarily showcase the advantages of DTFE for enhancing measurements of MFs from sparse tracers. At halo field level, we first numerically investigate various systematic effects on MFs of DTFE fields, which are induced by finite voxel sizes, halo number densities, halo weightings, and redshift space distortions (RSDs), respectively. Then, we explore the statistical power of MFs measured with DTFE for extracting cosmological information encoded in RSDs. We find that MFs measured with DTFE exhibit improvements by $\sim$ $2$ orders of magnitude in discriminative power for RSD effects and by a factor of $\sim$ $3$-$5$ in constraining power on structure growth rate over the MFs measured with Gaussian smoothing. These findings demonstrate the remarkable enhancements in statistical power of MFs achieved by DTFE, showing enormous application potentials of our method in extracting various key cosmological information from galaxy surveys.

astro-ph.CO↗

arXiv2024

Forecast of foreground cleaning strategies for AliCPT-1

We report the test results of several independent foreground-cleaning pipelines used in the Ali CMB Polarization Telescope experiment (AliCPT-1), a high-altitude CMB imager in the Northern hemisphere with thousands of detectors dedicated to the search for a primordial CMB polarization $B$-mode signature. Based on simulated data from 4 detector modules and a single season of observation, which we refer to as Data Challenge 1 (DC1), we employ different and independent pipelines to examine the robustness and effectiveness of the estimates on foreground parameters and the primordial $B$-mode detection. The foreground-cleaning strategies used in the pipelines include the parametric method of template fitting (TF) and the non-parametric methods of the constrained internal linear combination (cILC), the analytical blind separation (ABS), and the generalized least squares (GLS). We examine the impact of possible foreground residuals on the estimate of the CMB tensor-to-scalar ratio ($r$) for each pipeline by changing the contamination components in the simulated maps and varying the foreground models and sky patches for various tests. According to the DC1 data with the simulation input value $r_{\rm true}=0.023$, the foreground residual contamination levels in the TF/ABS/cILC/GLS pipelines are well within the corresponding statistical errors at the $2σ$ level. Furthermore, by utilizing the tension estimator, which helps identify significant residual foreground contamination in the detection of the primordial $B$-mode signal by quantifying the discrepancy between various $r$ measurements, we conclude that the presence of small foreground residuals does not lead to any significant inconsistency in the estimation of $r$.

astro-ph.CO↗

arXiv2024

Accurate Kappa Reconstruction Algorithm for masked shear catalog (AKRA)

Weak gravitational lensing is an invaluable tool for understanding fundamental cosmological physics. An unresolved issue in weak lensing cosmology is to accurately reconstruct the lensing convergence $κ$ maps from discrete shear catalog with survey masks, which the seminal Kaiser-Squire (KS) method is not designed to address. We present the Accurate Kappa Reconstruction Algorithm for masked shear catalog (AKRA) to address the issue of mask. AKRA is built upon the prior-free maximum likelihood mapmaking method (or the unbiased minimum variance linear estimator). It is mathematically robust in dealing with mask, numerically stable to implement, and practically effective in improving the reconstruction accuracy. Using simulated maps with mask fractions ranging from 10\% to 50\% and various mask shapes, we demonstrate that AKRA outperforms KS at both the map level and summary statistics such as the auto power spectrum $C_κ$ of the reconstructed map, its cross-correlation coefficient $r_\ell$ with the true $κ$ map, the scatter plot and the localization measure. Unlike the Wiener filter method, it adopts no priors on the signal power spectrum, and therefore avoids the Wiener filter related biases at both the map level and cross-correlation statistics. If we only use the reconstructed map in the unmasked regions, the reconstructed $C_κ$ is accurate to $1\%$ or better and $1-r_\ell \lesssim 1\%$ (excluding $\ell$ at the smallest scales investigated), even for extreme cases of mask fraction and shape. As the first step, the current version of AKRA only addresses the mask issue and therefore ignores complexities such as curved sky and inhomogeneous shape measurement noise. AKRA is capable of dealing with these issues straightfowrardly, and will be addressed in the next version.

astro-ph.CO↗

arXiv2024

Forecast constraints on the baryonic feedback effect from the future kinetic Sunyaev-Zel'dovich effect detection

The baryonic feedback effect is an important systematic error in the weak lensing (WL) analysis. It contributes partly to the $S_8$ tension in the literature. With the next generations of large scale structure (LSS) and CMB experiments, the high signal-to-noise kinetic Sunyaev-Zel'dovich (kSZ) effect detection can tightly constrain the baryon distribution in and around dark matter halos, and quantify the baryonic effect in the weak lensing statistics. In this work, we apply the Fisher matrix technique to predict the future kSZ constraints on 3 kSZ-sensitive Baryon Correction Model (BCM) parameters. Our calculations show that, in combination with next generation LSS surveys, the 3rd generation CMB experiments such as AdvACT and Simon Observatory can constrain the matter power spectrum damping $S(k)$ to the precision of $σ_S(k)<0.8\%\sqrt{37.8{\rm Gpc}^3h^{-3}/V}$ at $k\lesssim 10h/$Mpc, where $V$ is the overlapped survey volume between the future LSS and CMB surveys. For the 4th generation CMB surveys such as CMB-S4 and CMB-HD, the constraint will be enhanced to $σ_S(k)<0.4\%\sqrt{37.8{\rm Gpc}^3h^{-3}/V}$. If extra-observations, e.g. X-ray detection and thermal SZ observation, can effectively fix the gas density profile slope parameter $δ$, the constraint on $S(k)$ will be further boosted to $σ_S(k)<0.3\%\sqrt{37.8{\rm Gpc}^3h^{-3}/V}$ and $σ_S(k)<0.1\%\sqrt{37.8{\rm Gpc}^3h^{-3}/V}$ for the 3rd and 4th generation CMB surveys.

astro-ph.CO↗

arXiv2024

CSST large-scale structure analysis pipeline: I. constructing reference mock galaxy redshift surveys

In this paper, we set out to construct a set of reference mock galaxy redshift surveys (MGRSs) for the future Chinese Space-station Survey Telescope (CSST) observation, where subsequent survey selection effects can be added and evaluated. This set of MGRSs is generated using the dark matter subhalos extracted from a high-resolution Jiutian $N$-body simulation of the standard $Λ$CDM cosmogony with $Ω_m=0.3111$, $Ω_Λ=0.6889$, and $σ_8=0.8102$. The simulation has a boxsize of $1~h^{-1} {\rm Gpc}$, and consists of $6144^3$ particles with mass resolution $3.723 \times 10^{8} h^{-1} M_\odot $. In order to take into account the effect of redshift evolution, we first use all 128 snapshots in the Jiutian simulation to generate a light-cone halo/subhalo catalog. Next, galaxy luminosities are assigned to the main and subhalo populations using the subhalo abundance matching (SHAM) method with the DESI $z$-band luminosity functions at different redshifts. Multi-band photometries, as well as images, are then assigned to each mock galaxy using a 3-dimensional parameter space nearest neighbor sampling of the DESI LS observational galaxies and groups. Finally, the CSST and DESI LS survey geometry and magnitude limit cuts are applied to generate the required MGRSs. As we have checked, this set of MGRSs can generally reproduce the observed galaxy luminosity/mass functions within 0.1 dex for galaxies with $L > 10^8 L_\odot$ (or $M_* > 10^{8.5} M_\odot$) and within 1-$σ$ level for galaxies with $L < 10^8L_\odot$ (or $M_* < 10^{8.5} M_\odot$). Together with the CSST slitless spectra and redshifts for our DESI LS seed galaxies that are under construction, we will set out to test various slitless observational selection effects in subsequent probes.

astro-ph.GA↗