Related papers: Advanced Data Analysis for Observational Cosmology…
The Lyman-$\alpha$ forest refers to the series of absorption features observed in the spectra of distant quasars that are produced by neutral hydrogen in the intergalactic medium. Observed over a wide range of redshifts with both ground-…
Recent developments in spatial omics technologies have enabled the generation of high dimensional molecular data, such as transcriptomes, proteomes, and epigenomes, within their spatial tissue context, either through coprofiling on the same…
We review observations of molecular absorption line systems at high redshift toward red quasars and gravitational lenses.
Modern astronomy relies on massive databases collected by robotic telescopes and digital sky surveys, acquiring data in a much faster pace than what manual analysis can support. Among other data, these sky surveys collect information about…
Cosmography, the study and making of maps of the universe or cosmos, is a field where visual representation benefits from modern three-dimensional visualization techniques and media. At the extragalactic distance scales, visualization is…
The Q \& U Bolometric Interferometer for Cosmology (QUBIC) is a new kind of cosmological instrument that uses interferometry to observe the sky. The unique synthesized beam of QUBIC has an important frequency d\'ependance that we use to…
The physical nature of the material responsible for the high--velocity, broad-absorption line features seen in a small fraction of quasar spectra has been the subject of debate since their discovery. This has been especially compounded by…
In recent years the possibility of measuring the temporal change of radial and transverse position of sources in the sky in real time have become conceivable thanks to the thoroughly improved technique applied to new astrometric and…
The physical state of the intergalactic medium can be probed in great detail with the intervening absorption systems seen in quasar spectra. The properties of the Hydrogen absorbers depend on many cosmological parameters, such as the…
Methods based on machine learning have recently made substantial inroads in many corners of cosmology. Through this process, new computational tools, new perspectives on data collection, model development, analysis, and discovery, as well…
We study the circumgalactic medium (CGM) of a z=0.54 simulated dwarf galaxy using hydroART simulations. We present our analysis methods, which emulate observations, including objective absorption line detection, apparent optical depth (AOD)…
In cosmology, the analysis of observational evidence is very important to test theoretical models of the Universe. Artificial neural networks are powerful and versatile computational tools for data modelling and are recently being…
In recent years, deep learning has been successfully applied in various scientific domains. Following these promising results and performances, it has recently also started being evaluated in the domain of radio astronomy. In particular,…
Long range observations in the field of astronomy have opened up our understanding of the Solar System, the Galaxy and the wider Universe. In this paper we discuss the idea of direct in-situ reconnaissance of nearby stellar systems, using…
End-to-end deep learning models fed with multi-band galaxy images are powerful data-driven tools used to estimate galaxy physical properties in the absence of spectroscopy. However, due to a lack of interpretability and the associational…
We present a random forest framework for predicting circumgalactic medium (CGM) physical conditions from quasar absorption line observables, trained on a sample of Voigt profile-fit synthetic absorbers from the Simba cosmological…
Cosmological data in the next decade will be characterized by high-precision, multi-wavelength measurements of thousands of square degrees of the same patches of sky. By performing multi-survey analyses that harness the correlated nature of…
We develop a new model for automatic extraction of reported measurement values from the astrophysical literature, utilising modern Natural Language Processing techniques. We use this model to extract measurements present in the abstracts of…
This article reviews recent advances in the application of machine learning to weak-lensing cosmology. Weak gravitational lensing provides a unique and powerful probe of the total matter distribution in the Universe, independent of its…
We present an improved model for the absorption of X-rays in the ISM intended for use with data from future X-ray missions with larger effective areas and increased energy resolution such as Chandra and XMM, in the energy range above 100eV.…