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.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yicheng Guo
Timothy Carleton
Eric F. Bell
Zhu Chen
Avishai Dekel
S. M. Faber
Mauro Giavalisco
Dale D. Kocevski
Anton M. Koekemoer
David C. Koo
Peter Kurczynski
Seong-Kook Lee
F. S. Liu
Casey Papovich
Pablo G. Pérez-González
摘要： We use the Cosmic Assembly Deep Near-infrared Extragalactic Legacy Survey (CANDELS) data to study the relationship between quenching and the stellar mass surface density within the central radius of 1 kpc ($\Sigma_1$) of low-mass galaxies (stellar mass $M_* \lesssim 10^{9.5} M_\odot$) at $0.5 \leq z < 1.5$. Our sample is mass complete down to $\sim 10^9 M_\odot$ at $0.5 \leq z < 1.0$. We compare the mean $\Sigma_1$ of star-forming galaxies (SFGs) and quenched galaxies (QGs) at the same redshift and $M_*$. We find that low-mass QGs have higher $\Sigma_1$ than low-mass SFGs, similar to galaxies above $10^{10} M_\odot$. The difference of $\Sigma_1$ between QGs and SFGs increases slightly with $M_*$ at $M_* \lesssim 10^{10} M_\odot$ and decreases with $M_*$ at $M_* \gtrsim 10^{10} M_\odot$. The turnover mass is consistent with the mass where quenching mechanisms transition from internal to environmental quenching. At $0.5 \leq z < 1.0$, we find that the $\Sigma_1$ of galaxies increases by about 0.25 dex in the green valley (i.e., the transitioning region from star forming to fully quenched), regardless of their $M_*$. Using the observed specific star formation rate (sSFR) gradient in the literature as a constraint, we estimate that the quenching timescale (i.e., time spent in the transition) of low-mass galaxies is a few ($\sim4$) Gyrs at $0.5 \leq z < 1.0$. The mechanisms responsible for quenching need to gradually quench star formation in an outside-in way, i.e., preferentially ceasing star formation in outskirts of galaxies while maintaining their central star formation to increase $\Sigma_1$. An interesting and intriguing result is the similarity of the growth of $\Sigma_1$ in the green valley between low-mass and massive galaxies, which suggests that the role of internal processes in quenching low-mass galaxies is a question worthy of further investigation.
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