23–24 Apr 2019
University of Sydney, School of Physics
Australia/Sydney timezone

The Deeper, Wider, Faster program: Pioneering all-wavelength, multi-messenger fast transient exploration

24 Apr 2019, 10:00
30m
Slade Lecture Theatre (University of Sydney, School of Physics)

Slade Lecture Theatre

University of Sydney, School of Physics

Speaker

Prof. Cooke Jeff (Swimburne University)

Description

I will discuss the history, structure and strategy behind our
all-wavelength, multi-messenger Deeper, Wider, Faster program (DWF) to detect and study transients with millisecond-to-hours duration in real time. Fast transients include events such as fast radio bursts (FRBs), supernova shock breakouts, gamma-ray bursts, Type Ia supernova collisions with companion stars, X-ray bursts, flare stars, blitzars, and kilonovae. DWF coordinates over 50 telescopes on every continent and in space, from radio through gamma-ray, organised with neutrino, cosmic ray, and gravitational wave detectors. The world's most sensitive, wide-field
telescopes are coordinated in all wavelengths to acquire fast-cadenced data, at the same time on the same fields, to detect fast transients and gather all possible information before they fade. The radio and high-energy facilities process and identify fast transients in real time on board or via
GPU clusters. Simultaneous fast-cadenced CTIO DECam and NAOJ Subaru HSC optical imaging is acquired and processes in real time (seconds) on the Swinburne supercomputer throughout the night. Optical candidates are
identified within minutes after outburst with the help from advanced software and data visualisation technology. The multi-wavelength information is combined to trigger coordinated telescopes for rapid-response (minutes later) and later-time deep spectroscopy and imaging. DWF is on field before, during, and after fast transients burst, making it the best program to detect and understand the counterparts to FRBs, including coherent bursts, and resolve their nature for the first time. DWF has been a trailblazer for LSST and future large transient survey programs and is an excellent platform to develop machine and deep learning techniques, Big Data
transfer and processing solutions, and real-time data analyses.

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