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Register a new userCosmology from the Chinese Space Station Optical Survey (CSS-OS)
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The Chinese Space Station Optical Survey (CSS-OS) is a planned full sky survey operated by the Chinese Space Station Telescope (CSST). It can simultaneously perform the photometric imaging and spectroscopic slitless surveys, and will probe weak and strong gravitational lensing, galaxy clustering, individual galaxies and galaxy clusters, active galactic nucleus (AGNs), and so on. It aims to explore the properties of dark matter and dark energy and other important cosmological problems. In this work, we focus on two main CSS-OS scientific goals, i.e. the weak gravitational lensing (WL) and galaxy clustering surveys. We generate the mock CSS-OS data based on the observational COSMOS and zCOSMOS catalogs. We investigate the constraints on the cosmological parameters from the CSS-OS using the Markov Chain Monte Carlo (MCMC) method. The intrinsic alignments, galaxy bias, velocity dispersion, and systematics from instrumental effects in the CSST WL and galaxy clustering surveys are also included, and their impacts on the constraint results are discussed. We find that the CSS-OS can improve the constraints on the cosmological parameters by a factor of a few (even one order of magnitude in the optimistic case), compared to the current WL and galaxy clustering surveys. The constraints can be further enhanced when performing joint analysis with the WL, galaxy clustering, and galaxy-galaxy lensing data. Therefore, the CSS-OS is expected to be a powerful survey for exploring the Universe. Since some assumptions may be still optimistic and simple, it is possible that the results from the real survey could be worse. We will study these issues in details with the help of simulations in the future.
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The Chinese Space Station Optical Survey (CSS-OS) is a major science project of the Space Application System of the China Manned Space Program. This survey is planned to perform both photometric imaging and slitless spectroscopic observations, and it will focus on different cosmological and astronomical goals. Most of these goals are tightly dependent on the accuracy of photometric redshift (photo-z) measurement, especially for the weak gravitational lensing survey as a main science driver. In this work, we assess if the current filter definition can provide accurate photo-z measurement to meet the science requirement. We use the COSMOS galaxy catalog to create a mock catalog for the CSS-OS. We compare different photo-z codes and fitting methods that using the spectral energy distribution (SED) template-fitting technique, and choose to use a modified LePhare code in photo-z fitting process. Then we investigate the CSS-OS photo-z accuracy in certain ranges of filter parameters, such as band position, width, and slope. We find that the current CSS-OS filter definition can achieve reasonably good photo-z results with sigma_z~0.02 and outlier fraction ~3%.
The estimation of spectroscopic and photometric redshifts (spec-z and photo-z) is crucial for future cosmological surveys. It can directly affect several powerful measurements of the Universe, e.g. weak lensing and galaxy clustering. In this work, we explore the accuracies of spec-z and photo-z that can be obtained in the China Space Station Optical Surveys (CSS-OS), which is a next-generation space survey, using neural networks. The 1-dimensional Convolutional Neural Networks (1-d CNN) and Multi-Layer Perceptron (MLP, one of the simplest forms of Artificial Neural Network) are employed to derive the spec-z and photo-z, respectively. The mock spectral and photometric data used for training and testing the networks are generated based on the COSMOS catalog. The networks have been trained with noisy data by creating Gaussian random realizations to reduce the statistical effects, resulting in similar redshift accuracy for both high-SNR (signal to noise ratio) and low-SNR data. The probability distribution functions (PDFs) of the predicted redshifts are also derived via Gaussian random realizations of the testing data, and then the best-fit redshifts and 1-sigma errors also can be obtained. We find that our networks can provide excellent redshift estimates with accuracies ~0.001 and 0.01 on spec-z and photo-z, respectively. Compared to existing photo-z codes, our MLP has similar accuracy but is more efficient in the training process. The fractions of catastrophic redshifts or outliers can be dramatically suppressed comparing to the ordinary template-fitting method. This indicates that the neural network method is feasible and powerful for spec-z and photo-z estimations in future cosmological surveys.
The Chinese Space Station Telescope (CSST) spectroscopic survey plans to deliver high-quality low-resolution ($R > 200$) slitless spectra for hundreds of millions of targets down to a limiting magnitude of about 21 mag, covering a large survey area (17500 deg$^2$) and a wide wavelength range (255-1000 nm by 3 bands GU, GV, and GI). In this work, we use empirical spectra of the Next Generation Spectral Library to simulate the CSST stellar spectra at $R = 250$, and investigate their capabilities in measuring radial velocities. We find that velocity uncertainties depend strongly on effective temperature, weakly on metallicity for only FGK stars, and hardly on surface gravity. It is possible to deliver stellar radial velocities to a precision of about $3 ,mathrm{km},mathrm{s}^{-1}$ for AFGKM stars, and about $10 ,mathrm{km},mathrm{s}^{-1}$ for OB stars, at signal-to-noise ratio (SNR) of 100. Velocity uncertainties using single GU/GV/GI band spectra are also explored. Given the same SNR, the GU band performs best, the GV band the second best, and then the GI band. The effects of spectral normalization and imperfect template on velocity measurements are investigated and found to be very weak. The uncertainties caused by wavelength calibration are considered and found to be moderate. Given the possible precision of radial velocities, the CSST spectroscopic survey can enable interesting science such as searching for hyper-velocity stars. Limitations of our results are also discussed.
Anisotropies of the cosmic optical background (COB) and cosmic near-IR background (CNIRB) are capable of addressing some of the key questions in cosmology and astrophysics. In this work, we measure and analyze the angular power spectra of the simulated COB and CNIRB in the ultra-deep field of the China Space Station Telescope (CSST-UDF). The CSST-UDF covers about 9 square degrees, with magnitude limits ~28.3, 28.2, 27.6, 26.7 for point sources with 5-sigma detection in the r (0.620 um), i (0.760 um), z (0.915 um), and y (0.965 um) bands, respectively. According to the design parameters and scanning pattern of the CSST, we generate mock data, merge images and mask the bright sources in the four bands. We obtain four angular power spectra from l=200 to 2,000,000 (from arcsecond to degree), and fit them with a multi-component model including intrahalo light (IHL) using the Markov chain Monte Carlo (MCMC) method. We find that the signal-to-noise ratio (SNR) of the IHL is larger than 8 over the range of angular scales that are useful for astrophysical studies (l~10,000-400,000). Comparing to previous works, the constraints on the model parameters are improved by factors of 3~4 in this study, which indicates that the CSST-UDF survey can be a powerful probe on the cosmic optical and near-IR backgrounds.
The Chinese Space Station Telescope (CSST) spectroscopic survey aims to deliver high-quality low-resolution ($R > 200$) slitless spectra for hundreds of millions of targets down to a limiting magnitude of about 21 mag, distributed within a large survey area (17500 deg$^2$) and covering a wide wavelength range (255-1000 nm by 3 bands GU, GV, and GI). As slitless spectroscopy precludes the usage of wavelength calibration lamps, wavelength calibration is one of the most challenging issues in the reduction of slitless spectra, yet it plays a key role in measuring precise radial velocities of stars and redshifts of galaxies. In this work, we propose a star-based method that can monitor and correct for possible errors in the CSST wavelength calibration using normal scientific observations, taking advantage of the facts that i) there are about ten million stars with reliable radial velocities now available thanks to spectroscopic surveys like LAMOST, ii) the large field of view of CSST enables efficient observations of such stars in a short period of time, and iii) radial velocities of such stars can be reliably measured using only a narrow segment of CSST spectra. We demonstrate that it is possible to achieve a wavelength calibration precision of a few $mathrm{km},mathrm{s}^{-1}$ for the GU band, and about 10 to 20 $mathrm{km},mathrm{s}^{-1}$ for the GV and GI bands, with only a few hundred velocity standard stars. Implementations of the method to other surveys are also discussed.
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