We present new mock catalogues for two of the largest stage-IV next-generation surveys in the optical and infrared: LSST and Euclid, based on an N-body simulation+semi-analytical cone with a posterior modification with \texttt{PhotReal}. This technique modifies the original photometry by using an empirical library of spectral templates to make it more realistic. The reliability of the catalogues is confirmed by comparing the obtained color-magnitude relation, the luminosity and mass function and the angular correlation function with those of real data.
Consistent comparisons between the expected photometric redshifts for different surveys are also provided. Very deep near infrared surveys such as Euclid will provide very good performance ($Δz/(1+z) \sim 0.025-0.053$) down to $H\sim24$ AB mag and up to $z\sim3$ depending on the optical observations available from the ground whereas extremely deep optical surveys such as LSST will obtain an overall lower photometric redshift resolution ($Δz/(1+z) \sim 0.045$) down to $i\sim27.5$ AB mag, being considerably improved ($Δz/(1+z) \sim 0.035$) if we restrict the sample down to i$\sim$24 AB mag. Those numbers can be substantially upgraded by selecting a subsample of galaxies with the best quality photometric redshifts. We finally discuss the impact that these surveys will have for the community in terms of photometric redshift legacy.
This is the first of a series of papers where we set a framework for comparability between mock catalogues and observations with a particular focus on cluster surveys. The Euclid and LSST mocks are made publicly available in the following link: http://photmocks.obspm.fr/.
The uncertainty in the photometric redshift estimation is one of the major systematics in weak lensing cosmology. The self-calibration method is able to reduce this systematics without assuming strong priors. We improve the recently proposed self-calibration algorithm to enhance the stability and robustness with the noisy measurement. The improved algorithm is tested on the power spectra measured from the simulated catalogues constructed according to DECaLS DR8 photometric catalogue. For the fiducial analysis with 5 equal-width redshift bins over $0<z<1$ and 6 bands over scales $100 \leq \ell<…
We first present a catalogue of photometric redshifts for 14.68 million galaxies derived from the 7-band photometric data of Hyper Suprime-Cam Subaru Strategic Program and the Wide-field Infrared Survey Explorer using the nearest-neighbour algorithm. The redshift uncertainty is about 0.024 for galaxies of z<0.7, and steadily increases with redshift to about 0.11 at z~2. From such a large data set, we identify 21,661 clusters of galaxies, among which 5537 clusters have redshifts z>1 and 642 clusters have z>1.5, significantly enlarging the high redshift sample of galaxy clusters. Cluster richnes…
A Parametrized Galaxy Catalog Simulator For Testing Cluster Finding, Mass Estimation and Photometric Redshift Estimation in Optical and Near Infrared Surveys
We present a multi-band analysis of the six Hubble Frontier Field clusters and their parallel fields, producing catalogs with measurements of source photometry and photometric redshifts. We release these catalogs to the public along with maps of intracluster light and models for the brightest galaxies in each field. This rich data set covers a wavelength range from 0.2 to 8 $μm$, utilizing data from the Hubble Space Telescope, Keck Observatories, Very Large Telescope array, and Spitzer Space Telescope. We validate our products by injecting into our fields and recovering a population of synthet…
We develop a novel method to explore the galaxy-halo connection using the galaxy imaging surveys by modeling the projected two-point correlation function measured from the galaxies with reasonable photometric redshift measurements. By assuming a Gaussian form of the photometric redshift errors, we are able to simultaneously constrain the halo occupation distribution (HOD) models and the effective photometric redshift uncertainties. Tests with mock galaxy catalogs demonstrate that this method can successfully recover (within $\sim 1σ$) the intrinsic large-scale galaxy bias, as well as the HOD m…
Contamination from galaxy fragments, identified as sources, is a major issue in large photometric galaxy catalogs. In this paper, we prove that this problem can be easily addressed with computer vision techniques. We use image cutouts to train a convolutional neural network (CNN) to identify catalogued sources that are in reality just star formation regions and/or shreds of larger galaxies. The CNN reaches an accuracy ~98% on our testing datasets. We apply this CNN to galaxy catalogs from three amongst the largest surveys available today: the Sloan Digital Sky Survey (SDSS), the DESI Legacy Im…
A Public, K-Selected, Optical-to-Near-Infrared Catalog of the Extended Chandra Deep Field South (ECDFS) from the MUltiwavelength Survey by Yale-Chile (MUSYC)
An Enhanced Catalog of Gaia DR3 Galaxy Candidates with Spectroscopic and Machine-Learning Photometric Redshifts
Seoul National University(首尔大学);SNU Astronomy Research Center, Seoul National University(首尔大学天文研究中心);Institute for Data Innovation in Science, Seoul National University(首尔大学数据科学创新研究所)
Infrared-enhanced Photometric Redshifts for the Dark Energy Survey Y6 Gold catalogue
Universidad Complutense de Madrid(马德里康普顿斯大学);Instituto de Física de Partículas y del Cosmos, IPARCOS(粒子与宇宙物理研究所,IPARCOS);Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT)(能源、环境和技术研究中心 (CIEMAT));Port d’Informació Científica (PIC)(科学信息港 (PIC));University of Chicago(芝加哥大学);Fermi National Accelerator Laboratory(费米国家加速器实验室)
We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging dataset, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of $0.4 < z < 0.9$ over 5655 deg$^2$. We have developed new photometric redshift (photo-$z$) estimates using the Legacy Survey DECam and WISE photometry, with $σ_{\mathrm{NMAD}} = 0.02$ precision for LRGs. We compute the projected correlation function using new…
The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data has been collected in the COSMOS field. This paper describes the collection, processing, and analysis of this new imaging data to produce a new reference photometric redshift catalog. Source detection and multi-wavelength photometry is performed for 1.7 million sources across the $2\,\mathrm{deg}^{2}$ of the COSMOS field, $\sim$966,000 of which are measured with all available broad-band data using both traditional apertu…
The Pan-STARRS1 (PS1) $3π$ survey is a comprehensive optical imaging survey of three quarters of the sky in the $grizy$ broad-band photometric filters. We present the methodology used in assembling the source classification and photometric redshift (photo-z) catalogue for PS1 $3π$ Data Release 1, titled Pan-STARRS1 Source Types and Redshifts with Machine learning (PS1-STRM). For both main data products, we use neural network architectures, trained on a compilation of public spectroscopic measurements that has been cross-matched with PS1 sources. We quantify the parameter space coverage of our …
A Precision Multi-Band Two-Epoch Photometric Catalog of 44 Million Sources in the Northern Sky from Combination of the USNO-B and Sloan Digital Sky Survey Catalogs
下一代宽视场光学和无线电测量的一个关键科学驱动力是对时变天空的探索。这些调查将具有前所未有的敏感性和覆盖面,但在比调查寿命更长的时间尺度上发现变化的能力将受到限制。我们提出了一个新的精度,多历元的光度计目录,跨越60年,结合USNO-B和SDSS数据发布9目录。我们重新校准了原始USNO-B星表的测光,并创建了一个星表,其中包含位于北天DR 9足迹中的43,647,887个光学点源的两个测光时期,最多可达5个不同波段。重新校准的对象跨越的幅度范围14 < m < 20,是准确的$\approx$ 0.1马格。我们最大限度地减少虚假的对象和那些不准确的幅度通过识别和删除几个来源的系统误差在两个起源目录,重点虚假的对象,表现出大的视星等变化。在考虑了这些影响之后,我们发现$\approx$ 250,000颗恒星和类星体在USNO-B和SDSS DR 9时期之间显示出显著的(> 4 $σ$)亮度变化。讨论了该星表的历史价值及其在长时标、大振幅变星和类星体研究中的应用。
JWST Advanced Deep Extragalactic Survey (JADES) Data Release 5: Photometric Catalog
Department of Astronomy and Astrophysics, University of California, Santa Cruz(加州大学圣克鲁兹分校天体物理学与天文学系);Kavli Institute for Cosmology, University of Cambridge(剑桥大学卡弗里宇宙学研究所);Cavendish Laboratory, University of Cambridge(剑桥大学卡文迪许实验室);Steward Observatory, University of Arizona(亚利桑那大学斯图德天文台);AURA for the European Space Agency (ESA), Space Telescope Science Institute(欧洲航天局(ESA)所属美国大学研究协会(AURA)太空望远镜科学研究所);Centro de Astrobiología (CAB), CSIC–INTA(西班牙国家航空航天技术研究所(INTA)/西班牙国家科学研究委员会(CSIC)天体生物学中心)
We describe the SDSS-IV MaNGA PyMorph Photometric (MPP-VAC) and MaNGA Deep Learning Morphology (MDLM-VAC) Value Added Catalogs. The MPP-VAC provides photometric parameters from Sérsic and Sérsic+Exponential fits to the 2D surface brightness profiles of the MaNGA DR15 galaxy sample. Compared to previous PyMorph analyses of SDSS imaging, our analysis of the MaNGA DR15 incorporates three improvements: the most recent SDSS images; modified criteria for determining bulge-to-disk decompositions; and the fits in MPP-VAC have been eye-balled, and re-fit if necessary, for additional reliability. A comp…
Since its launch in 1999, the XMM-\textit{Newton} mission has compiled the largest catalogue of serendipitous X-ray sources, with the 3XMM being the third version of this catalogue. This is because of the combination of a large effective area (5000 $\rm cm^2$ at 1 keV) and a wide field of view (30 arcmin). The 3XMM-DR6 catalogue contains about 470,000 unique X-ray sources over an area of 982 $\rm deg^2$. A significant fraction of these (100,178 sources) have reliable optical, near/mid-IR counterparts in the SDSS, PANSTARRS, VIDEO, UKIDSS and WISE surveys. In a previous paper we have presented …