Recent Talks

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Data challenges and solutions in forthcoming surveys
Lecture 2

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: General overview on the use of machine learning techniques in astronomy
Lecture 2

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Deep learning
Lecture 1

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Machine learning methods for non-supervised classification and dimension reduction techniques
Lecture 1

No sound available

BRITE-Constellation (BRight Target Explorer) consists of six nano-satellites aiming to study of variability of the brightest stars in the sky. Austria, Poland, and Canada contribute two spacecraft each all launched into low earth orbits. The satellites have the same structure: they are 20 cm cubes, 7kg mass, with a CCD photometer fed by 3 cm aperture telescopes. The main difference between pairs of satellites is the instrument passband which set to blue (400-450nm) or red (550-700nm). The core scientific objective is to obtain high precision two color photometry, with a time base of up to 180 days, of stars brighter than 4.5 mag in order to study stellar pulsations, spots, and granulation, eclipsing binaries, search for planets and more.
Since the launch of the first two BRITE satellites in February 2013 more than 5 and a half years of experiences in space have been gathered to run the mission and a summary of lessons learned will be presented.  By now more than 20 peer-reviewed scientific articles have been published based on data collected by BRITE-Constellation satellites in space and most results presented therein benefitted greatly from supplementary spectroscopy by meter size telescopes obtained on ground.

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 2

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 1

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Data challenges and solutions in forthcoming surveys
Lecture 1

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy

Topic: General overview on the use of machine learning techniques in astronomy

Lecture 1

Two exotic elements have been introduced into the standard
cosmological model: non-baryonic dark matter and dark energy. The success
in converting a hypothesis into a solid theory depends strongly on whether
we are able to solve the problems in explaining observations with these
dark elements and whether the solutions of these problems are unique within
the standard paradigm without recourse to alternative scenarios. We have
not achieved that success yet because of numerous inconsistencies, mainly
on galactic scales, the non-detection so far of candidate particles for
dark matter, and the existence of many alternative hypotheses that might
substitute the standard picture to explain the cosmological observations. A
review of some ideas and facts is given here.
(arXiv:1808.09823)