Related papers: Simulation tool of a Supernova search with VST
We investigate measuring the peculiar motions of galaxies up to $z=0.5$ using Type Ia supernovae (SNe Ia) from LSST, and predict the subsequent constraints on the growth rate of structure. We consider two cases. Our first is based on…
The luminosity functions of galaxies and quasars provide invaluable information about galaxy and quasar formation. Estimating the luminosity function from magnitude limited samples is relatively straightforward, provided that the distances…
Over the last decade, quasar sample sizes have increased from several thousand to several hundred thousand, thanks mostly to SDSS imaging and spectroscopic surveys. LSST, the next-generation optical imaging survey, will provide hundreds of…
Wide Field Survey Telescope (WFST), with a powerful sky survey capability in the northern hemisphere, will play an important role in asteroid searching and monitoring. However, WFST is not a telescope dedicated to near-Earth asteroids…
We predict cosmological constraints for forthcoming surveys using Superluminous Supernovae (SLSNe) as standardisable candles. Due to their high peak luminosity, these events can be observed to high redshift (z~3), opening up new…
We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from large-scale astronomical surveys. The main goal of this work is to explore the potential of adaptive learning…
We investigate the flux and event rate of supernova relic neutrinos (SRNs) and discuss their implications for the cosmic star formation rate. As reference models, we adopt the supernova rate model based on recent observations and the…
The James Webb Space Telescop (JWST) promises to revolutionise our understanding of the early Universe, and contrasting its upcoming observations with predictions of the $\Lambda$CDM model requires detailed theoretical forecasts. Here, we…
We apply one of lazy learning methods named k-nearest neighbor algorithm (kNN) to estimate the photometric redshifts of quasars, based on various datasets from the Sloan Digital Sky Survey (SDSS), UKIRT Infrared Deep Sky Survey (UKIDSS) and…
We present a new approach to obtaining photometric redshifts using a kernel learning technique called Support Vector Machines (SVMs). Unlike traditional spectral energy distribution fitting, this technique requires a large and…
We present the discovery of a Type Ia supernova (SN) at redshift $z = 1.914$ from the CANDELS multi-cycle treasury program on the \textit{Hubble Space Telescope (HST)}. This SN was discovered in the infrared using the Wide-Field Camera 3,…
Accurate estimation of photometric redshifts (photo-$z$s) is crucial for cosmological surveys. Various methods have been developed for this purpose, such as template fitting methods and machine learning techniques, each with its own…
The Foundation Supernova Survey aims to provide a large, high-fidelity, homogeneous, and precisely-calibrated low-redshift Type Ia supernova (SN Ia) sample for cosmology. The calibration of the current low-redshift SN sample is the largest…
Our search for high-redshift Type Ia supernovae discovered, in its first years, a sample of seven supernovae. Using a "batch" search strategy, almost all were discovered before maximum light and were observed over the peak of their light…
Identification and characterisation of Kilonovae (KNe) can be instrumental in improving our understanding of cosmology and astrophysics. However, their detection poses unique challenges due to rarity and faintness. Upcoming telescopes, with…
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will provide a windfall of new transients and variable sources. Here we have performed mock observation simulations to understand LSST's expected detection rates for…
Recent high-cadence transient surveys have discovered rapid transients whose light curve timescales are shorter than those of typical supernovae. In this paper, we present a systematic search for rapid transients at medium-high redshifts…
In the next decade, the LSST will become a major facility for the astronomical community. However accurately determining the redshifts of the observed galaxies without using spectroscopy is a major challenge. Reconstruction of the redshifts…
We present a novel method of classifying Type Ia supernovae using convolutional neural networks, a neural network framework typically used for image recognition. Our model is trained on photometric information only, eliminating the need for…
Supernova (SN) light echoes could be a powerful tool for determining distances to galaxies geometrically, Sparks 1994. In this paper we present CCD photometry of the environments of 64 historical supernovae, the first results of a program…