分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The question of radio dichotomy in the active galactic nuclei (AGNs) is still in debate even it has been proposed for more than forty years. In order to solve the old riddle, we collect a sample of AGNs with optical $B$ band and radio 6cm wavelength data to analyze the radio loudness ${\rm log}R$. Our results indicate a separation of ${\rm log}R = \langle 1.37 \pm 0.02 \rangle$ between radio-loud (RL) AGNs and radio-quiet (RQ) AGNs, suggest the existence of an RL/RQ dichotomy. For the first time, we suggest combining radio luminosity and radio loudness as a double-criterion to divide AGNs into RLs and RQs to avoid misclassification problems that may happen in the single-criterion scenario, we propose the double-criterion dividing line ${\rm log}L_{\rm 6cm} = -2.7{\rm log}R +44.3$ by using a machine learning method. In addition, the key point of the RL/RQ dichotomy is the origin of radio emission for the two classes, we suggest the radio emission from RLs and RQs share the same origin, e.g. jets and mini-jets (aborted-jet or outflow), through a correlation study between radio 6cm luminosity and optical $B$ band luminosity.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： With mock strong gravitational lensing images, we investigate the performance of broken power-law (BPL) model on the mass reconstruction of galaxy-scale lenses. An end-to-end test is carried out, including the creation of mock strong lensing images, the subtraction of lens light, and the reconstruction of lensed images. Based on these analyses, we can reliably evaluate how accurate the lens mass and source light distributions can be measured. We notice that, based on lensed images alone, only the Einstein radii ($R_{\rm E}$) or the mean convergence within them can be well determined, with negligible bias (typically $<1\%$) and controllable uncertainty. Away from the Einstein radii, the radial and mean convergence profiles can hardly be constrained unless well-designed priors are applied to the BPL model. We find that, with rigid priors, the BPL model can clearly outperform the singular power-law models by recovering the lens mass distributions with small biases out to several Einstein radii (e.g., no more than $5\%$ biases for the mean convergence profiles within $3~R_{\rm E}$). We find that the source light reconstructions are sensitive to both lens light contamination and lens mass models, where the BPL model with rigid priors still performs best when there is no lens light contamination. It is shown that, by correcting for the projection effect, the BPL model is capable of estimating the aperture and luminosity weighted line-of-sight velocity dispersions to an accuracy of $\sim6\%$. These results further highlight the great potential of the BPL model in strong lensing related studies.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： With mock strong gravitational lensing images, we investigate the performance of broken power-law (BPL) model on the mass reconstruction of galaxy-scale lenses. An end-to-end test is carried out, including the creation of mock strong lensing images, the subtraction of lens light, and the reconstruction of lensed images. Based on these analyses, we can reliably evaluate how accurate the lens mass and source light distributions can be measured. We notice that, based on lensed images alone, only the Einstein radii ($R_{\rm E}$) or the mean convergence within them can be well determined, with negligible bias (typically $<1\%$) and controllable uncertainty. Away from the Einstein radii, the radial and mean convergence profiles can hardly be constrained unless well-designed priors are applied to the BPL model. We find that, with rigid priors, the BPL model can clearly outperform the singular power-law models by recovering the lens mass distributions with small biases out to several Einstein radii (e.g., no more than $5\%$ biases for the mean convergence profiles within $3~R_{\rm E}$). We find that the source light reconstructions are sensitive to both lens light contamination and lens mass models, where the BPL model with rigid priors still performs best when there is no lens light contamination. It is shown that, by correcting for the projection effect, the BPL model is capable of estimating the aperture and luminosity weighted line-of-sight velocity dispersions to an accuracy of $\sim6\%$. These results further highlight the great potential of the BPL model in strong lensing related studies.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： We propose a novel method to detect cosmic magnification signals by cross-correlating foreground convergence fields constructed from galaxy shear measurements with background galaxy positional distributions, namely shear-number density correlation. We apply it to the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey data. With 27 non-independent data points and their full covariance, $\chi_0^2\approx 34.1$ and $\chi_T^2\approx 24.0$ with respect to the null and the cosmological model with the parameters from HSC shear correlation analyses in Hamana et al. 2020 (arXiv:1906.06041), respectively. The Bayes factor of the two is $\log_{10}B_{T0}\approx 2.2$ assuming equal model probabilities of null and HSC cosmology, showing a clear detection of the magnification signals. Theoretically, the ratio of the shear-number density and shear-shear correlations can provide a constraint on the effective multiplicative shear bias $\bar m$ using internal data themselves. We demonstrate the idea with the signals from our HSC-SSP mock simulations and rescaling the statistical uncertainties to a survey of $15000\deg^2$. For two-bin analyses with background galaxies brighter than $m_{lim}=23$, the combined analyses lead to a forecasted constraint of $\sigma(\bar m) \sim 0.032$, $2.3$ times tighter than that of using the shear-shear correlation alone. Correspondingly, $\sigma(S_8)$ with $S_8=\sigma_8(\Omega_\mathrm{m}/0.3)^{0.5}$ is tightened by $\sim 2.1$ times. Importantly, the joint constraint on $\bar m$ is nearly independent of cosmological parameters. Our studies therefore point to the importance of including the shear-number density correlation in weak lensing analyses, which can provide valuable consistency tests of observational data, and thus to solidify the derived cosmological constraints.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Galaxy photometric redshift (photo-$z$) is crucial in cosmological studies, such as weak gravitational lensing and galaxy angular clustering measurements. In this work, we try to extract photo-$z$ information and construct its probability distribution function (PDF) using the Bayesian neural networks (BNN) from both galaxy flux and image data expected to be obtained by the China Space Station Telescope (CSST). The mock galaxy images are generated from the Advanced Camera for Surveys of Hubble Space Telescope ($HST$-ACS) and COSMOS catalog, in which the CSST instrumental effects are carefully considered. And the galaxy flux data are measured from galaxy images using aperture photometry. We construct Bayesian multilayer perceptron (B-MLP) and Bayesian convolutional neural network (B-CNN) to predict photo-$z$ along with the PDFs from fluxes and images, respectively. We combine the B-MLP and B-CNN together, and construct a hybrid network and employ the transfer learning techniques to investigate the improvement of including both flux and image data. For galaxy samples with SNR$>$10 in $g$ or $i$ band, we find the accuracy and outlier fraction of photo-$z$ can achieve $\sigma_{\rm NMAD}=0.022$ and $\eta=2.35\%$ for the B-MLP using flux data only, and $\sigma_{\rm NMAD}=0.022$ and $\eta=1.32\%$ for the B-CNN using image data only. The Bayesian hybrid network can achieve $\sigma_{\rm NMAD}=0.021$ and $\eta=1.23\%$, and utilizing transfer learning technique can improve results to $\sigma_{\rm NMAD}=0.019$ and $\eta=1.17\%$, which can provide the most confident predictions with the lowest average uncertainty.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： The accuracy of galaxy photometric redshift (photo-$z$) can significantly affect the analysis of weak gravitational lensing measurements, especially for future high-precision surveys. In this work, we try to extract photo-$z$ information from both galaxy flux and image data expected to be obtained by China Space Station Telescope (CSST) using neural networks. We generate mock galaxy images based on the observational images from the Advanced Camera for Surveys of Hubble Space Telescope (HST-ACS) and COSMOS catalogs, considering the CSST instrumental effects. Galaxy flux data are then measured directly from these images by aperture photometry. The Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) are constructed to predict photo-$z$ from fluxes and images, respectively. We also propose to use an efficient hybrid network, which combines MLP and CNN, by employing transfer learning techniques to investigate the improvement of the result with both flux and image data included. We find that the photo-$z$ accuracy and outlier fraction can achieve $\sigma_{\rm NMAD} = 0.023$ and $\eta = 1.43\%$ for the MLP using flux data only, and $\sigma_{\rm NMAD} = 0.025$ and $\eta = 1.21\%$ for the CNN using image data only. The result can be further improved in high efficiency as $\sigma_{\rm NMAD} = 0.020$ and $\eta = 0.90\%$ for the hybrid transfer network. These approaches result in similar galaxy median and mean redshifts ~0.8 and 0.9, respectively, for the redshift range from 0 to 4. This indicates that our networks can effectively and properly extract photo-$z$ information from the CSST galaxy flux and image data.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Ruibiao Luo
Liping Fu
Wentao Luo
Nicola R. Napolitano
Linghua Xie
Mario Radovich
Jing Liu
Rui Li
Valeria Amaro
Zhu Chen
Dezi Liu
Zuhui Fan
Giovanni Covone
Mattia Vaccari
摘要： The multi-band photometry of the VOICE imaging data, overlapping with 4.9 deg$^2$ of the Chandra Deep Field South (CDFS) area, enables both shape measurement and photometric redshift estimation to be the two essential quantities for weak lensing analysis. The depth of $mag_{AB}$ is up to 26.1 (5$\sigma$ limiting) in $r$-band. We estimate the Excess Surface Density (ESD; $\Delta\Sigma$) based on galaxy-galaxy measurements around galaxies at lower redshift (0.10<$z_l$<0.35) while we select the background sources to be at higher redshift ranging from 0.3 to 1.5. The foreground galaxies are divided into two major categories according to their colour (blue/red), each of which has been further divided into high/low stellar mass bins. Then the halo masses of the samples are estimated by modelling the signals, and the posterior of the parameters are samples via Mote Carlo Markov Chain (MCMC) process. We compare our results with the existing Stellar-to-Halo Mass Relation (SHMR) and find that the blue low stellar mass bin (median $M_*=10^{8.31}M_\odot$) deviates from the SHMR relation whereas all other three samples agrees well with empirical curves. We interpret this discrepancy as the effect of a low star formation efficiency of the low-mass blue dwarf galaxy population dominated in the VOICE-CDFS area.
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