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.
The luminosity and spectral energy distribution (SED) of high-$z$ galaxies are sensitive to the stellar population synthesis (SPS) models. In this paper, we study the effects of different SPS models on the measurements of high-$z$ galaxies and the budget of ionizing photons during the epoch of reionization, by employing each of them in the semi-analytical galaxy formation model {\sc L-Galaxies 2020}. We find that the different SPS models lead to $\lesssim 0.5$ dex differences on the amplitudes of UV luminosity functions, while the two modes of the same SPS model with and without the inclusion of binary stars leads to similar UV luminosity functions at $z \ge 6$. Instead, the binary stars produce $\sim 40\%$ more ionizing photons than the single stars, while such differences are smaller than those caused by different SPS models, e.g. the BPASS model produces $\sim 100\%$ more ionizing photons than other models.
China 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 redshift, compared to broadband photometry. However, due to low-resolution and signal-to-noise ratio of slitless spectra, measurement of these properties 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 slitless spectra are simulated based on real data from the early data release of the Dark Energy Spectroscopic Instrument (DESI-EDR) and the 16th data release of the Baryon Oscillaton Spectroscopic Survey (BOSS-DR16), combining the 9th data release of the DESI Legacy Survey (DESI LS DR9). The BNN provides redshifts estimates along with corresponding uncertainties, achieving an accuracy of $\sigma_{\rm NMAD} = 0.00063$, outlier percentage $\eta=0.92\%$ and weighted mean uncertainty $\bar{E} = 0.00228$. These results successfully meet the requirement for cosmological studies using slitless spectra from CSST.
Abstract The forthcoming Chinese Space Station Telescope (CSST) wide-field multiband imaging survey will produce seven-band photometric spectral energy distributions (SEDs) for billions of galaxies. The effective extraction of astronomical information from these massive data sets of SEDs relies on the techniques of SED synthesis (or modeling) and SED analysis (or fitting). We evaluate the performance of the latest version of the BayeSED code combined with SED models with increasing complexity for simultaneously determining the photometric redshifts and stellar population parameters of galaxies in this survey. By using an empirical statistics–based mock galaxy sample without SED modeling errors, we show that the random observational errors in photometries are more important sources of errors than the parameter degeneracies and Bayesian analysis method and tool. By using a Horizon-AGN hydrodynamical simulation–based mock galaxy sample with SED modeling errors about the star formation histories (SFHs) and dust attenuation laws (DALs), the simple typical assumptions lead to significantly worse parameter estimation with CSST photometries only. SED models with more flexible (or complicated) forms of SFH/DAL do not necessarily lead to better estimation of redshift and stellar population parameters. We discuss the selection of the best SED model by means of Bayesian model comparison in different surveys. Our results reveal that Bayesian model comparison with Bayesian evidence may favor SED models with different complexities when using photometries from different surveys. Meanwhile, the SED model with the largest Bayesian evidence tends to give the best performance of parameter estimation, which is clearer for photometries with higher discriminative power.
Abstract The massive galaxies and their central supermassive black holes (SMBHs) co-evolution scenario proposes that a gas-rich major merger can trigger the central starburst and feeding the SMBH accretion, and then star formation is eventually quenched by quasar feedback. In this evolutionary sequence, dust-obscured quasars may represent the critical transition phase between starburst and unobscured quasars. Modeling the panchromatic emission of these hidden monsters provides a unique way to explore their physical properties and therefore the co-evolution between SMBHs and their hosts. However, most of modelling methods are not suitable for the extremely luminous systems with obscured Active Galactic Nucleus (AGN) emission. Here we present two case studies of panchromatic modeling of the extremely luminous dust-obscured quasars at the cosmic noon.
Abstract 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.
Abstract 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 outshining light from active galactic nuclei (AGNs) poses significant challenges in studying the properties of AGN host galaxies. To address this issue, we propose a novel approach which combines image decomposition and spectral energy distribution (SED) decomposition to constrain properties of AGN host galaxies. Image decomposition allows us to disentangle optical flux into AGN and stellar components, thereby providing additional constraints on the SED models to derive more refined stellar mass. To test the viability of this approach, we obtained a sample of 24 X-ray selected type-I AGNs with redshifts ranging from 0.73 to 2.47. We estimated the stellar masses for our sample and found that our results are generally consistent with earlier estimates based on different methods. Through examining the posterior distribution of stellar masses, we find that our method could derive better constrained results compared to previous SED decomposition methods. With the derived stellar masses, we further studied the $M_{\rm BH}-M_\star$ relation of our sample, finding a higher intrinsic scatter in the correlation for our entire sample compared to the local quiescent correlation, which could be caused by a few black hole monsters in our sample. We propose that based on our method, future works could extend to larger samples of high-redshift AGN host galaxies, thereby enhancing our understanding of their properties.
ABSTRACT The Chinese Space Station Telescope (CSST) slitless spectroscopic survey will observe objects to a limiting magnitude of ∼23 mag (5σ, point sources) in U, V, and I over 17 500 deg2. The spectroscopic observations are expected to be highly efficient and complete for mapping galaxies over 0 < z < 1 with secure redshift measurements at spectral resolutions of R ∼ 200, providing unprecedented data sets for cosmological studies. To quantitatively examine the survey potential, we develop a software tool, namely the CSST Emulator for Slitless Spectroscopy (CESS), to quickly generate simulated 1D slitless spectra with limited computing resources. We introduce the architecture of CESS and the detailed process of creating simulated CSST slitless spectra. The extended light distribution of a galaxy induces the self-broadening effect on the 1D slitless spectrum. We quantify the effect using morphological parameters: Sérsic index, effective radius, position angle, and axis ratio. Moreover, we also develop a module for CESS to estimate the overlap contamination rate for CSST grating observations of galaxies in galaxy clusters. Applying CESS to the high-resolution model spectra of a sample of ∼140 million galaxies with mz < 21 mag selected from the Dark Energy Spectroscopic Instrument LS DR9 catalogue, we obtain the simulated CSST slitless spectra. We examine the dependence of measurement errors on different types of galaxies due to instrumental and observational effects and quantitatively investigate the redshift completeness for different environments out to z ∼ 1. Our results show that the CSST spectroscopy is able to provide secure redshifts for about one-quarter of the sample galaxies.
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