Related papers: Quantifying systematic uncertainties in supernova …
Anomalies drive scientific discovery -- they are associated with the cutting edge of the research frontier, and thus typically exploit data in the low signal-to-noise regime. In astronomy, the prevalence of systematics --- both "known…
Vastly different time and length scales are a common problem in numerical simulations of astrophysical phenomena. Here, we present an approach to numerical modeling of such objects on the example of Type Ia supernova simulations. The…
Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on…
We present a method for measuring the cosmic expansion history H(z) in uncorrelated redshift bins, and apply it to current and simulated type Ia supernova data assuming spatial flatness. If the matter density parameter Omega_m can be…
New supernova surveys such as the Dark Energy Survey, Pan-STARRS and the LSST will produce an unprecedented number of photometric supernova candidates, most with no spectroscopic data. Avoiding biases in cosmological parameters due to the…
We present a systematic analysis of the cosmological constraints from the "Pantheon Sample" of 1048 Type Ia Supernovae (SNe Ia) in the redshift range $0.01<z<2.3$ compiled by Scolnic et al. (2018). Applying the flux-averaging method for…
The latest improvements in the scale and calibration of Type Ia supernovae catalogues allow us to constrain the specific nature and evolution of dark energy through its effect on the expansion history of the universe. We present the results…
We investigate the potential of a future supernova dataset, as might be obtained by the proposed SNAP satellite, to discriminate among different ``dark energy'' theories that describe an accelerating Universe. We find that many such models…
To probe the late evolution history of the Universe, we adopt two kinds of optimal basis systems. One of them is constructed by performing the principle component analysis (PCA) and the other is build by taking the multidimensional scaling…
Dramatically increasing data volumes are forcing astronomers to adopt automated methods for the identification and classification of astronomical objects. Although deep-learning models are often well-suited to this task, obtaining a measure…
Weak-lensing peak counts provide a straightforward way to constrain cosmology by linking local maxima of the lensing signal to the mass function. Recent applications to data have already been numerous and fruitful. However, the importance…
Late-time cosmic acceleration is one of the most interesting unsolved puzzles in modern cosmology. The explanation most accepted nowadays, dark energy, raises questions about its own nature, e.g. what exactly is dark energy, and…
This paper presents a novel approach to estimate the Standard Model backgrounds based on modifying Monte Carlo predictions within their systematic uncertainties. The improved background model is obtained by altering the original predictions…
Shocks are ubiquitous in the interstellar medium of galaxies, where they contribute to the energetic balance and to the cycle of matter, and where they are thought to be the primary sites for cosmic rays acceleration. Most of the time: in…
The actual knowledge of the structure and future evolution of our universe is based on the use of cosmological models, which can be tested through the so-called 'probes', namely astrophysical phenomena, objects or structures with peculiar…
The muon intensity attenuation method to detect heterogeneities in large matter volumes is analyzed. Approximate analytical expressions to estimate the collection time and the signal to noise ratio, are proposed and validated by Monte Carlo…
The next generation of galaxy surveys has the potential to substantially deepen our understanding of the Universe. This potential hinges on our ability to rigorously address systematic uncertainties. Until now, diagnosing systematic effects…
Future measurements of the nature of dark energy using Type Ia supernovae will require a precise characterization of systematic sources of error. Evolutionary effects remain the most uncertain contributor to the overall systematic error…
The standard technique for measurement of random uncertainties of star formation histories (SFHs) is the bootstrap Monte Carlo, in which the color-magnitude diagram (CMD) is repeatedly resampled. The variation in SFHs measured from the…
The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (CMB, SNe Ia, BAO) have been studied in depth to better understand the nature of the…