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Digital co-addition of astronomical images is a common technique for increasing signal-to-noise and image depth. A modification of this simple technique has been applied to the detection of minor bodies in the Solar System: first stationary…
Photometric redshift estimation algorithms are often based on representative data from observational campaigns. Data-driven methods of this type are subject to a number of potential deficiencies, such as sample bias and incompleteness.…
The aim of this paper is to investigate ways to optimize the accuracy of photometric redshifts for a SNAP like mission. We focus on how the accuracy of the photometric redshifts depends on the magnitude limit and signal-to-noise ratio,…
The estimation and utilization of photometric redshift probability density functions (photo-$z$ PDFs) has become increasingly important over the last few years and currently there exist a wide variety of algorithms to compute photo-$z$'s,…
This study aims to improve the photometric redshifts (photo-$z$s) of galaxies by integrating two contemporary methods: template-fitting and machine learning. Finding the synergy between these two methods was not a high priority in the past,…
As one of Stage IV space-based telescopes, China Space Station Telescope (CSST) can perform photometric and spectroscopic surveys simultaneously to efficiently explore the Universe in extreme precision. In this work, we investigate several…
Improvement in the precision of measurements of cosmological parameters with Type Ia Supernovae (SNIa) is expected to come from large photometrically identified (photometric) SN samples. Here we re-analyse the SDSS photometric SN sample,…
The effective redshift distribution $n(z)$ of galaxies is a critical component in the study of weak gravitational lensing. Here, we introduce a new method for determining $n(z)$ for weak lensing surveys based on high-quality redshifts and…
Upcoming measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect, which results from Cosmic Microwave Background (CMB) photons scattering off moving electrons, offer a powerful probe of the Epoch of Reionization (EoR). The kSZ signal…
Obtaining well-calibrated photometric redshift probability densities for galaxies without a spectroscopic measurement remains a challenge. Deep learning discriminative models, typically fed with multi-band galaxy images, can produce outputs…
A new approach to estimating photometric redshifts - using Artificial Neural Networks (ANNs) - is investigated. Unlike the standard template-fitting photometric redshift technique, a large spectroscopically-identified training set is…
We investigate the impact of photometric signal-to-noise (S/N) on the precision of photometric redshifts in multi-band imaging surveys, using both simulations and real data. We simulate the optical 4-band (BVRz) Deep Lens Survey (DLS,…
We examine the impact of non-Gaussian photometry errors on photometric redshift performance. We find that they greatly increase the scatter, but this can be mitigated to some extent by incorporating the correct noise model into the…
In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-$z$) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. \textsc{Deepz} reduces the $\sigma_{68}$ scatter…
Data analysis usually suffers from the Missing Not At Random (MNAR) problem, where the cause of the value missing is not fully observed. Compared to the naive Missing Completely At Random (MCAR) problem, it is more in line with the…
In the era of huge astronomical surveys, machine learning offers promising solutions for the efficient estimation of galaxy properties. The traditional, `supervised' paradigm for the application of machine learning involves training a model…
Photometric redshift uncertainties are a major source of systematic error for ongoing and future photometric surveys. We study different sources of redshift error caused by choosing a suboptimal redshift histogram bin width and propose…
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…
Wide-field slitless spectroscopic galaxy surveys, such as the one performed by the upcoming Chinese Space Station Survey Telescope (CSST), are crucial for precision cosmology but present formidable data analysis challenges. Because spectra…
We present an empirical method for estimating the underlying redshift distribution N(z) of galaxy photometric samples from photometric observables. The method does not rely on photometric redshift (photo-z) estimates for individual…