Related papers: Photometric Supernova Cosmology with BEAMS and SDS…
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 investigate the performance of some common machine learning techniques in identifying BHB stars from photometric data. To train the machine learning algorithms, we use previously published spectroscopic identifications of BHB stars from…
The Sloan Digital Sky Survey-II Supernova Survey has identified a large number of new transient sources in a 300 sq. deg. region along the celestial equator during its first two seasons of a three-season campaign. Multi-band (ugriz) light…
We present results exploring the role that probabilistic deep learning models can play in cosmology from large scale astronomical surveys through estimating the distances to galaxies (redshifts) from photometry. Due to the massive scale of…
A quantitative data-driven comparison among supernovae (SNe) based on their spectral time series combined with multi-band photometry is presented. We use an unsupervised Random Forest algorithm as a metric on a set of 82 well-documented SNe…
Star-galaxy classification is one of the most fundamental data-processing tasks in survey astronomy, and a critical starting point for the scientific exploitation of survey data. For bright sources this classification can be done with…
In the era of large astronomical surveys, photometric classification of supernovae (SNe) has become an important research field due to limited spectroscopic resources for candidate follow-up and classification. In this work, we present a…
The discovery of accelerated expansion using supernova surveys has been one of the most surprising discoveries in cosmology in the past ten years. Present and future surveys, among which SNLS, JDEM or LSST, are based on samples of a few…
We present photometric properties and distance measurements of 252 high redshift Type Ia supernovae (0.15 < z < 1.1) discovered during the first three years of the Supernova Legacy Survey (SNLS). These events were detected and their…
Current cosmological analyses which use Type Ia supernova (SN Ia) observations combine SN samples to expand the redshift range beyond that of a single sample and increase the overall sample size. The inhomogeneous photometric calibration…
Cosmological parameter estimation techniques that robustly account for systematic measurement uncertainties will be crucial for the next generation of cosmological surveys. We present a new analysis method, superABC, for obtaining…
With the upcoming Vera C.~Rubin Observatory Legacy Survey of Space and Time (LSST), it is expected that only $\sim 0.1\%$ of all transients will be classified spectroscopically. To conduct studies of rare transients, such as Type I…
We present a new technique to create a bin-averaged Hubble Diagram (HD) from photometrically identified SN~Ia data. The resulting HD is corrected for selection biases and contamination from core collapse (CC) SNe, and can be used to infer…
Using a sample of 608 Type Ia supernovae from the SDSS-II and BOSS surveys, combined with a sample of foreground galaxies from SDSS-II, we estimate the weak lensing convergence for each supernova line-of-sight. We find that the correlation…
Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from…
Large numbers of supernovae (SNe) have been discovered in recent years, and many more will be found in the near future. Once discovered, further study of a SN and its possible use as an astronomical tool (e.g., as a distance estimator)…
State-Space Models (SSMs) have emerged as an efficient alternative to transformers, yet existing visual SSMs retain deeply ingrained biases from their origins in natural language processing. In this paper, we address these limitations by…
Type Ia supernova (SN Ia) as a standard candle is an ideal tool to measure cosmic distance and expansion history of the Universe. Here we investigate the SN Ia photometric measurement in the China Space Station Telescope Ultra Deep Field…
{We study biasing as a physical phenomenon by analysing geometrical and clustering properties of density fields of matter and galaxies.} {Our goal is to determine the bias function using a combination of geometrical and power spectrum…
We present the full Hubble diagram of photometrically-classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of…