Related papers: The supernova cosmology cookbook: Bayesian numeric…
Observations of high redshift type Ia supernovae (SNe) will enable us to probe the structure of galaxy halos and the composition of dark matter. The future prospects for this field are briefly discussed here. First the ability of SN…
Observations of Type Ia supernovae (\sne), which probe the late Universe, together with baryon acoustic oscillations (BAO) and the cosmic microwave background (CMB), which probe the intermediate and early epochs, provide complementary…
The use of advanced statistical analysis tools is crucial in order to improve cosmological parameter estimates via removal of systematic errors and identification of previously unaccounted for cosmological signals. Here we demonstrate the…
These lecture notes intend to form a short pedagogical introduction to the use of typical type Ia-Supernovae (hereafter SNIa) as standard candles to determine the energy density of the universe. Problems of principle for taking SNIa as…
A hierarchical Bayesian method is applied to the analysis of Type-Ia supernovae (SNIa) observations to constrain the properties of the dark matter haloes of galaxies along the SNIa lines-of-sight via their gravitational lensing effect. The…
Correctly interpreting observations of sources such as type Ia supernovae (SNe Ia) require knowledge of the power spectrum of matter on AU scales - which is very hard to model accurately. Because under-dense regions account for much of the…
Type Ia Supernovae are in many aspects still enigmatic objects. Recent years have witnessed a bonanza of supernova observations. The increased samples from dedicated searches have allowed the statistical investigation of Type Ia Supernovae…
Over the past decade, supernovae have emerged as some of the most powerful tools for measuring extragalactic distances. A well developed physical understanding of type II supernovae allow them to be used to measure distances independent of…
Cosmological distances inferred from supernova Ia observations constitute the most direct and solid evidence for the recently detected accelerated expansion of the universe. In this contribution, we show some inconsistencies between two of…
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…
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…
The ultimate fate of the universe, infinite expansion or a big crunch, can be determined by measuring the redshifts, apparent brightnesses, and intrinsic luminosities of very distant supernovae. Recent developments have provided tools that…
Empirically, Type Ia supernovae are the most useful, precise, and mature tools for determining astronomical distances. Acting as calibrated candles they revealed the presence of dark energy and are being used to measure its properties.…
This paper presents a systematic literature review focusing on the application of machine learning techniques for deriving observational constraints in cosmology. The goal is to evaluate and synthesize existing research to identify…
The Supernova Acceleration Probe (SNAP) will use Type Ia supernovae (SNe Ia) as distance indicators to measure the effect of dark energy on the expansion history of the Universe. (SNAP's weak-lensing program is described in a companion…
The accelerating expansion of the Universe is one of the most surprising and potentially profound discoveries of modern cosmology. Measuring the acceleration well enough to meaningfully constrain interesting physical models requires…
We study supernova (SN) classification using the machine learning method of the Recurrent Neural Network (RNN) in the Chinese Space Station Survey Telescope Ultra-Deep Field (CSST-UDF) photometric survey, and explore the improvement of the…
The 2-m aperture Chinese Space Station Telescope (CSST), which observes at wavelengths ranging from 255 to 1000 nm, is expected to start science operations in 2024. An ultra-deep field observation program covering approximately 10 square…
We study how future Type-Ia supernovae (SNIa) standard candles detected by the Vera C. Rubin Observatory (LSST) can constrain some cosmological models. We use a realistic three-year SNIa simulated dataset generated by the LSST Dark Energy…
We probe the cosmic acceleration by using the recently released SNLS3 sample of 472 type Ia supernovae. Combining this type Ia supernovae dataset with the cosmic microwave background anisotropy data from the Wilkinson Microwave Anisotropy…