Related papers: Quasar candidates selection in the Virtual Observa…
Astronomical databases currently provide high-volume spectroscopic and photometric data. While spectroscopic data is better suited to the analysis of many astronomical objects, photometric data is relatively easier to obtain due to shorter…
We have used the VLA FIRST survey and the APM catalog of the POSS-I plates as the basis for constructing a new radio-selected sample of optically bright quasars. This is the first radio-selected sample that is competitive in size with…
We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive…
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…
Achieving practical applications of quantum machine learning for real-world scenarios remains challenging despite significant theoretical progress. This paper proposes a novel approach for classifying satellite images, a task of particular…
I describe two novel techniques originally devised to select strongly lensed quasar candidates in wide-field surveys. The first relies on outlier selection in optical and mid-infrared magnitude space; the second combines mid-infrared colour…
We present an algorithm for selecting gravitational lens candidates from amongst Sloan Digital Sky Survey (SDSS) quasars. In median Early Data Release (EDR) conditions, the algorithm allows for the recovery of pairs of equal flux point…
We have used the KPNO 4-meter Mayall telescope to image 0.83 square degrees of sky in six fields at high galactic latitude in six filters spanning 3000-10000\AA\ to magnitude limits ranging from 22.1 to 23.8. As a first use of this…
We explored the AllWISE catalogue of the Wide-field Infrared Survey Explorer mission and identified Young Stellar Object candidates. Reliable 2MASS and WISE photometric data combined with Planck dust opacity values were used to build our…
We introduce a general range of science drivers for using the Virtual Observatory (VO) and identify some common aspects to these as well as the advantages of VO data access. We then illustrate the use of existing VO tools to tackle multi…
Time-delay cosmography can be used to infer the Hubble parameter $H_0$ by measuring the relative time delays between multiple images of gravitationally-lensed quasars. A few of such systems have already been used to measure $H_0$: their…
This is the first paper in a series aimed at defining a statistically significant sample of QSOs in the range $ 15 < B < 18.75$ and $ 0.3 < z < 2.2$. The selection is carried out using direct plates obtained at the ESO and UK Schmidt…
The Hubble tension, revealed by a $\sim 5\sigma$ discrepancy between measurements of the Hubble-Lemaitre constant from early- and local-Universe observations, is one of the most significant problems in modern cosmology. In order to better…
Measuring time delays between the multiple images of gravitationally lensed quasars is now recognized as a competitive way to constrain the cosmological parameters, and it is complementary with other cosmological probes. This requires long…
The Virtual Observatory has reached sufficient maturity for its routine scientific exploitation by astronomers. To prove this statement, here I present a brief description of the complete VO-powered PhD thesis entitled "Galactic and…
We develop a galaxy cluster finding algorithm based on spectral clustering technique to identify optical counterparts and estimate optical redshifts for X-ray selected cluster candidates. As an application, we run our algorithm on a sample…
Machine learning can provide powerful tools to detect patterns in multi-dimensional parameter space. We use K-means -a simple yet powerful unsupervised clustering algorithm which picks out structure in unlabeled data- to study a sample of…
We present a classification-based approach to identify quasi-stellar radio sources (quasars) in the Sloan Digital Sky Survey and evaluate its performance on a manually labeled training set. While reasonable results can already be obtained…
Observatories and satellites around the globe produce tremendous amounts of imaging data to study many different astrophysical phenomena. The serendipitous observations of Solar System objects are a fortunate by-product which have often…
Digital co-addition of astronomical images is a common technique for increasing signal-to-noise and image depth. A modification of this simple technique has been applied to the detection of minor bodies in the Solar System: first stationary…