اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدAnisotropies of Cosmic Optical and Near-IR Background from China Space Station Telescope (CSST)
440
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
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.
قيم البحث
اقرأ أيضاً
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.
We study how the presence of world-sheet currents affects the evolution of cosmic string networks, and their impact on predictions for the cosmic microwave background (CMB) anisotropies generated by these networks. We provide a general description of
string networks with currents and explicitly investigate in detail two physically motivated examples: wiggly and superconducting cosmic string networks. By using a modified version of the CMBact code, we show quantitatively how the relevant network parameters in both of these cases influence the predicted CMB signal. Our analysis suggests that previous studies have overestimated the amplitude of the anisotropies for wiggly strings. For superconducting strings the amplitude of the anisotropies depends on parameters which presently are not well known - but which can be measured in future high-resolution numerical simulations.
We report measurements of the cosmic microwave background (CMB) power spectrum from the complete 2008 South Pole Telescope (SPT) data set. We analyze twice as much data as the first SPT power spectrum analysis, using an improved cosmological paramete
r estimator which fits multi-frequency models to the SPT 150 and $220,$GHz bandpowers. We find an excellent fit to the measured bandpowers with a model that includes lensed primary CMB anisotropy, secondary thermal (tSZ) and kinetic (kSZ) Sunyaev-Zeldovich anisotropies, unclustered synchrotron point sources, and clustered dusty point sources. In addition to measuring the power spectrum of dusty galaxies at high signal-to-noise, the data primarily constrain a linear combination of the kSZ and tSZ anisotropy contributions at $150,$GHz and $ell=3000$: $D^{tSZ}_{3000} + 0.5,D^{kSZ}_{3000} = 4.5pm 1.0 ,mu{rm K}^2$. The 95% confidence upper limits on secondary anisotropy power are $D^{tSZ}_{3000} < 5.3,mu{rm K}^2$ and $D^{kSZ}_{3000} < 6.5,mu{rm K}^2$. We also consider the potential correlation of dusty and tSZ sources, and find it incapable of relaxing the tSZ upper limit. These results increase the significance of the lower than expected tSZ amplitude previously determined from SPT power spectrum measurements. We find that models including non-thermal pressure support in groups and clusters predict tSZ power in better agreement with the SPT data. Combining the tSZ power measurement with primary CMB data halves the statistical uncertainty on $sigma_8$. However, the preferred value of $sigma_8$ varies significantly between tSZ models. Improved constraints on cosmological parameters from tSZ power spectrum measurements require continued progress in the modeling of the tSZ power.
We use a range of cosmological data to constrain phenomenological modifications to general relativity on cosmological scales, through modifications to the Poisson and lensing equations. We include cosmic microwave background anisotropy measurements f
rom the Planck satellite, cosmic shear from CFHTLenS and DES-SV, and redshift-space distortions from BOSS data release 12 and the 6dF galaxy survey. We find no evidence of departures from general relativity, with the modified gravity parameters constrained to $Sigma_0 = 0.05^{+0.05}_{-0.07}$ and $mu_0 = -0.10^{+0.20}_{-0.16}$, where $Sigma_0$ and $mu_0$ refer to deviations from general relativity today and are defined to be zero in general relativity. We also forecast the sensitivity to those parameters of the full five-year Dark Energy Survey and of an experiment like the Large Synoptic Survey Telescope, showing a substantial expected improvement in the constraint on $Sigma_0$.
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.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
