Related papers: Imputation of Missing Photometric Data and Photome…

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…

Large imaging surveys will rely on photometric redshifts (photo-z's), which are typically estimated through machine learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training…

Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a…

Datasets with missing values are very common in real world applications. GAIN, a recently proposed deep generative model for missing data imputation, has been proved to outperform many state-of-the-art methods. But GAIN only uses a…

Wide, deep photometric surveys require robust photometric redshift estimates (photo-z's) for studies of large-scale structure. These estimates depend critically on accurate photometry. We describe the improvements to the photometric…

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…

The forthcoming CSST wide-field multiband imaging survey will produce seven-band photometric spectral energy distributions (SEDs) for billions of galaxies. The effective extraction of astronomical information from these massive datasets of…

Machine learning photo-z methods, trained directly on spectroscopic redshifts, provide a viable alternative to traditional template fitting methods but may not generalise well on new data that deviates from that in the training set. In this…

We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({\theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by…

Forthcoming astronomical surveys are expected to detect new sources in such large numbers that measuring their spectroscopic redshift measurements will be not be practical. Thus, there is much interest in using machine learning to yield the…

We seek to improve the accuracy of joint galaxy photometric redshift estimation and spectral energy distribution (SED) fitting. By simulating different sources of uncorrected systematic errors, we demonstrate that if the uncertainties on…

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for…

We present the first systematic analysis of photometric redshifts (photo-z) estimated from the Rubin Observatory Data Preview 1 (DP1) data taken with the Legacy Survey of Space and Time (LSST) Commissioning Camera. Employing the Redshift…

Accurate and precise photometric redshifts (photo-z's) of Type Ia supernovae (SNe Ia) can enable the use of SNe Ia, measured only with photometry, to probe cosmology. This dramatically increases the science return of supernova surveys…

In this paper we advance the simple analytic photometric redshift estimator for Type Ia supernovae (SNe Ia) proposed by Wang (2007), and use it to study simulated SN Ia data. We find that better than 0.5% accuracy in z_phot (with…

Current and future imaging surveys require photometric redshifts (photo-zs) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge but is needed to advance our understanding of cosmology. In this paper…

We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of the redshift probability distributions (PDZs) obtained independently from each…

We study the impact of catastrophic errors occurring in the photometric redshifts of galaxies on cosmological parameter estimates with cosmic shear tomography. We consider a fiducial survey with 9-filter set and perform photo-z measurement…

Photometric redshifts are necessary for enabling large-scale multicolour galaxy surveys to interpret their data and constrain cosmological parameters. While the increased depth of future surveys such as the Large Synoptic Survey Telescope…

Chinese Space Station Telescope (CSST) has the capability to conduct slitless spectroscopic survey simultaneously with photometric survey. The spectroscopic survey will measure slitless spectra, potentially providing more accurate…