International Conference on Machine Learning for Astrophysics - ML4Astro

Session

Unsupervised Learning and Pattern Discovery

31 May 2022, 09:50

Catania

Conveners

Unsupervised Learning and Pattern Discovery

• Santiago Gonzalez-Gaitan (CENTRA, IST, University of Lisbon)

26. Unsupervised classification reveals new evolutionary pathways

Malgorzata Siudek (IFAE, Barcelona)

31/05/2022, 09:50

Oral Presentation

While we already seem to have a general scenario of the evolution of different types of galaxies, a complete and satisfactory understanding of the processes that led to the formation of all the variety of today's galaxy types is still beyond our reach. To solve this problem, we need both large datasets reaching high redshifts and novel methodologies of dealing with them.

The statistical...

173. An unsupervised approach to galaxy spectra classification

Julien Dubois (IPAG, UGA, CNRS)

31/05/2022, 10:10

In a data-intensive era, turning to automated statistical methods has become necessary in most scientific fields, including astronomy and astrophysics. Such methods make possible the analysis of large quantities of data of various forms, ranging from images to spectra, time series, and much more. They are capable of tackling lots of challenging tasks: inference problems, clustering, pattern...

13. Patterns in the chaos? An unsupervised view of Galactic SNRs

Cristobal Bordiu (Istituto Nazionale di Astrofisica (INAF))

31/05/2022, 10:30

Oral Presentation

Supernova Remnants (SNRs) are the remains of supernova explosions, the cataclysmic deaths of certain types of stars. These rapidly expanding structures have a notorious impact into the surroundings, releasing vast amounts of energy and processed matter to the interstellar medium. The study of SNRs is then crucial to understand the structural, dynamical and chemical evolution of the Galaxy as a...

12. Modelling Galactic Microwave emission with ML techniques

Giuseppe Puglisi (Universita' di Roma Tor Vergata)

31/05/2022, 10:50

Oral Presentation

One of the major challenges in the context of the Cosmic Microwave Background (CMB) radiation is to detect a polarization pattern, the so called B-modes of CMB polarization, that are thought to be directly linked to the space-time metric fluctuations present in the Universe at the very first instants of life. To date, several challenges have prevented to detect the B-modes partly because of...

160. An Unsupervised Dive Into Gamma-ray Burst Afterglow Classification

Dr Eliot Ayache (The Oskar Klein Centre, Department of Astronomy, Stockholm University, AlbaNova, SE-10691 Stockholm, Sweden)

Oral Presentation

The Neil Gehrels "Swift" Observatory has been detecting and measuring emission from gamma-ray bursts (GRBs) and their associated afterglow for the last 17 years. Today, over 1500 bursts have been observed, with light curves displaying different morphologies in the succession of decay regimes with time. We explore prospects for acquiring physical inference from machine-learning models by ...

60. Modelling Galactic Microwave emission with ML techniques

Giuseppe Puglisi (Universita' di Roma Tor Vergata)

Oral Presentation

One of the major challenges in the context of the Cosmic Microwave Background (CMB) radiation is to detect a polarization pattern, the so called B-modes of CMB polarization, that are thought to be directly linked to the space-time metric fluctuations present in the Universe at the very first instants of life. To date, several challenges have prevented to detect the B-modes partly because...

108. Patterns in the chaos? An unsupervised view of Galactic SNRs

Cristobal Bordiu (Istituto Nazionale di Astrofisica (INAF))

Oral Presentation

Supernova Remnants (SNRs) are the remains of supernova explosions, the cataclysmic deaths of certain types of stars. These rapidly expanding structures have a notorious impact into the surroundings, releasing vast amounts of energy and processed matter to the interstellar medium. The study of SNRs is then crucial to understand the structural, dynamical and chemical evolution of the Galaxy as a...

105. Unsupervised classification reveals new evolutionary pathways

Malgorzata Siudek (IFAE, Barcelona)

Oral Presentation

While we already seem to have a general scenario of the evolution of different types of galaxies, a complete and satisfactory understanding of the processes that led to the formation of all the variety of today's galaxy types is still beyond our reach. To solve this problem, we need both large datasets reaching high redshifts and novel methodologies of dealing with them.

The...