Description
Afternoon sessin of the 2nd day.
There is a shortage of multiwavelength and spectroscopic followup capabilities given the number of transient and variable astrophysics events discovered through wide-field, optical surveys. From the haystack of potential science targets, astronomers must pick the valuable needles to study. Given millions of events discovered annually, how does one find a...
In astronomy as well as other sciences, neural networks are often trained on simulation data with the prospect of being used on real instrument data. Astronomical large-scale surveys are already producing very large datasets, and machine learning will play a crucial role in enabling us to fully utilize all of the available data. Unfortunately, training a model on simulated data and then...
Bayesian parameter estimation and model comparison are widely used in cosmology. This has led to the development of very efficient and user-friendly codes that perform these complex calculations. In this presentation, we will demonstrate the wider applicability of these algorithms, by applying them to study the COVID pandemic. We will perform Bayesian parameter estimation and model comparison...
Literature surveys in astronomy are greatly facilitated by both open-access preprint servers (ArXiv) and online tools like the Astrophysics Data System (ADS). However, the astrophysics literature often uses specialised jargon, sometimes using multiple identifiers for the same phenomena. For example, the terms SFR-M$_*$ correlation, Star Forming Sequence and Star Formation Main Sequence, all...
