Pengjie Zhang’s research while affiliated with Shanghai Jiao Tong University and other places

The measurement of cosmological distances using baryon acoustic oscillations (BAO) is crucial for studying the universe’s expansion. The China 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 σ0 = 0.003 and σ0 = 0.006, representative of expected CSST errors, and examine their effects on the BAO peak and distance scaling factors, α⊥ and α∥, across redshift bins within 0.0 < z ⩽ 1.0. The wedge 2PCF method proves more effective in detecting the BAO peak compared with the monopole 2PCF, particularly for σ0 = 0.006. Constraints on the BAO peaks show that α⊥ is well constrained around 1.0, regardless of σ0, with precision between 1% and 3% across redshift bins. In contrast, α∥ measurements are more sensitive to increases in σ0. For σ0 = 0.003, the results remain close to the fiducial value, with uncertainties ranging between 4% and 9%; for σ0 = 0.006, significant deviations from the fiducial value are observed. We also study the ability to measure parameters (Ωm, H0rd) using distance measurements, proving robust constraints as a cosmological probe under CSST-like redshift uncertainties. These findings demonstrate that the CSST survey enables few-percent precision measurements of DA using the wedge 2PCF method, highlighting its potential to place tight constraints on the universe’s expansion history and contribute to high-precision cosmological studies.

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 ∼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.

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 $\sigma_0 = 0.003$ and $\sigma_0 = 0.006$, representative of expected CSST errors, and examine their effects on the BAO peak and distance scaling factors, $\alpha_\perp$ and $\alpha_\parallel$, 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 $\sigma_0 = 0.006$. Constraints on the BAO peaks show that $\alpha_\perp$ is well constrained around 1.0, regardless of $\sigma_0$, with precision between 1% and 3% across redshift bins. In contrast, $\alpha_\parallel$ measurements are more sensitive to increases in $\sigma_0$. For $\sigma_0 = 0.003$, the results remain close to the fiducial value, with uncertainties ranging between 4% and 9%; for $\sigma_0 = 0.006$, significant deviations from the fiducial value are observed. We also study the ability to measure parameters $(\Omega_m, H_0r_\mathrm{d})$ using distance measurements, proving robust constraints as a cosmological probe under CSST-like redshift uncertainties.

This study employs a novel approach for reconstructing the thermal Sunyaev-Zeldovich (tSZ) effect power spectrum from Planck data using the Analytical Blind Separation (ABS) method. The ABS method improves the recovery of weak signals, by applying eigenmode exclusion for low signal-to-noise ratio regimes and introducing a shift parameter to stabilize calculations. Validation through simulated Planck data demonstrates the robustness of ABS in reconstructing the tSZ power spectrum, even under challenging conditions. In the analysis of the Planck PR3 full-mission data, ABS shows lower amplitudes at $\ell \gtrsim 300$ compared to the Planck 2015 band powers using the MILCA and NILC foreground cleaning methods. After marginalizing over residual foreground components, the ABS analysis finds the overall tSZ power spectrum amplitude to be 20\% lower than the Planck best-fit one, suggesting a smaller $S_8$. At $\ell \simeq 200$, the tSZ band power is $10^{12} \ell(\ell+1)C^{yy}_\ell/(2\pi) = 0.126\pm 0.018$, largely independent of the tSZ model choice. These findings highlight the potential of the ABS method as a promising alternative for tSZ power spectrum analysis, offering a robust and independent means of extracting cosmological parameters.

Chinese Space Station Telescope (CSST) has the capability to conduct a slitless spectroscopic survey simultaneously with a 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 use baryon acoustic oscillations (BAOs) and other probes to constrain the cosmological parameters. However, due to the 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 a transfer learning technique, by appending two Bayesian layers after a convolutional neural network, 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 NMAD = 0.00063, outlier percentage η = 0.92%, and weighted mean uncertainty E ¯ = 0.00228 . These results successfully fulfill the requirement of σ NMAD < 0.005 for BAO and other studies employing CSST slitless spectroscopic surveys.

In \citep{Qin+}, we attempted to reconstruct the weak lensing convergence map $\hat{\kappa}$ from cosmic magnification by linearly weighting the DECaLS galaxy overdensities in different magnitude bins of grz photometry bands. The $\hat{\kappa}$ map is correlated with cosmic shear at 20-$\sigma$ significance. However, the low galaxy number density in the DECaLS survey prohibits the measurement of $\hat{\kappa}$ 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 $0.4<z_\kappa<0.6,0.6<z_\kappa<0.8$ and $0.8<z_\kappa<1.0$ respectively. More remarkably, the $\hat{\kappa}-\hat{\kappa}$ correlations of the $0.4<z_\kappa<0.6$ and $0.6<z_\kappa<0.8$ bins show reasonably good agreement with predictions based on theoretical interpretation of $\hat{\kappa}-\gamma$ measurement. This result takes a step further towards the cosmological application of our lensing reconstruction method.

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 ($\kappa$) 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 $\kappa$ 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 $\kappa$ map. We tested AKRA 2.0 using simulated shear catalogs with various masks, demonstrating that the reconstructed $\kappa$ map by AKRA 2.0 maintains high accuracy. For the reconstructed $\kappa$ map in unmasked regions, the reconstructed convergence power spectrum $C_\kappa^{\rm{rec}}$ and the correlation coefficient with the true $\kappa$ 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.

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$\sigma$, 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 wCDM 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 wCDM 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 $\Lambda$.