Discovery

Discovery identifies transients at all wavelengths and messengers and collect all observational data. There are three key programs:

1. Rapid Real-Time Discovery and Early Warning: Transients present challenges for signal processing. They can appear unpredictably across billions of galaxies and fade quickly, requiring rapid detection in very large and fragmented data sets. In the last two decades, the discovery of transients has been increasing exponentially and, with the first light of the Rubin Observatory later this year, will make a step change from thousands per night to an estimated 10 million per night. The limitations for fully exploiting the upcoming datasets are that follow-up observations must be done within seconds to minutes of detection and only a handful of detections are available and embedded within millions of data points. For this, we require unique methods that are fast and accurate with sparse data and scalable to big data volumes.  We have been developing tools including AI applications to overcome these challenges and will operate three existing and future Australian flagship real-time detection and identification programs, all of which are either active or have been adopted into their respective international collaborations with proprietary data access.

2. Dynamic Follow-Up: Astrophysical transients span a vast range of brightness and durations, from milliseconds to months and emit light at a single wavelength or across multiple wavelengths, or at unknown wavelengths, with some events also producing high-energy particles and gravitational waves. These properties make their detection and follow up challenging. Rubin, CTAO, SKA, Roman, LVK, and Australian-led programs will actively search for transients. Once identified by the Rapid Real-time Discovery program or other facilities, the Dynamic Follow-up Program will leverage Australia’s geographical advantage to coordinate global follow-up using over 70 specialised telescopes. These observations—spectroscopy, colour imaging, polarimetry, and light curves—are essential to understand each event before it fades. We will develop software and real-time tools to coordinate rapid-response observations and link facilities across Australia into a unified, high-efficiency network. A central database will track all our observations and associated information (e.g., host galaxies), guiding current and future follow-up. We will use existing modelling tools, including the Redback code, and the family of models provided by the theorists to interpret these observations and fully characterise transient events. The observation database will support data mining across wavelengths and timescales for new discoveries, Indigenous research, and long-term legacy.

3. Data Mining for Transient Discovery: Data mining will uncover faint and serendipitous transients, multi-wavelength and multi-messenger correlations (e.g., optical–gamma-ray, and satellites and debris signatures. Oral histories and Indigenous knowledge will also inform past transient interpretations. AI and signal processing will cross-match and identify sub-threshold signals in Rubin, CTAO, Roman, and Australian surveys. Rubin and Roman image stacking will reveal early Universe supernovae, shortly after the Big Bang.

Core researchers

• Prof Jeff Cooke (Swinburne University) - All wavelength/messenger fast/early transients, high-redshift transients, host galaxies 

• Prof Gavin Rowell (University of Adelaide) - 

• Dr Karelle Siellez (University of Tasmania) - 

• Dr Rebecca Allen (Swinburne University of Technology) - 

• Prof Michael Ashley (University of New South Wales, Sydney) - 

• Prof Andrew Cole (University of Tasmania) - 

• Prof David Coward (University of Western Australia) - 

• Prof Simon Ellingsen (ICRAR, University of Western Australia) - 

• Prof Duncan Galloway (Monash University) - 

• Prof Duane Hamacher (Melbourne University) - 

• Dr Anais Möller (Swinburne University) -  Time-domain discovery, Rubin broker Fink co-PI, Observational supernova 

• Prof Anna Moore (Australian National University) - 

• A/Prof Tony Travouillon (Australian National University) - 

• A/Prof Brad Tucker (Australian National University) - 

• Prof Linqing Wen (University of Western Australia) - 

Partner researchers

• A/Prof Igor Andreoni (University of North Carolina, Chapel Hill) - 

• Prof David Buckley (South African Astronomical Observatory) -

• Prof Yanbei Chen (California Institute of Technology) - Gravitational wave detection

• A/Prof Michael Coughlin (University of Minnesota) - 

• Dr Phil Edwards (CSIRO) - 

• Dr Emille Ishida (Laboratoire de Physique de Clermont Auvergne) - 

• Prof Mansi Kasliwal (California Institute of Technology) - 

• A/Prof Takashi Moriya (National Astronomical Observatory of Japan) - Observational and theoretical supernova light curves and spectra

• A/Prof Antonella Palmese (Carnegie Mellon University) - 

• A/Prof Vikram Ravi (California Institute of Technology) - 

• Prof Lifan Wang (Texas A&M University) - 

Associate researchers

• A/Prof Richard Dodson (University of Western Australia) - 

• Dr Sabrina Einecke (University of Adelaide) - 

• Prof Natasha Hurley-Walker (ICRAR, Curtin University) - 

• Prof Brian Schmidt (Australian National University) - Hubble tension, Type Ia and other supernova light curves and spectra

• A/Prof Sara Webb (Swinburne University) -