Research description:

The Simons Observatory (SO) is a new, multi-telescope experiment to study the origin and evolution of the cosmos by measuring the cosmic microwave background (CMB), the oldest light in the Universe. Raw data consist of TBs of timestreams of measured sky brightness recorded each day—adding up to several PB over several years—that need to be reconstructed into 2D maps. However, before this can happen, the timestreams need to be automatically processed to remove noise contaminants and foreground galaxies/stars that block the main signal. In this project, you will work with a small team of researchers in Toronto that is developing machine learning methods to identify and classify these objects. Some development may use existing data from the Atacama Cosmology Telescope (ACT), a precursor to SO. Possible avenues of research include developing ways of retraining our classification algorithms on-the-fly and figuring out how to propagate uncertainties in classification into errors in the final maps. An exciting aspect of this project is that our classification will help enable the search for astrophysical transients, such as flaring stars and gamma ray bursts. The successful candidate will:

Write and document code in coordination with the research team led by Profs. Hincks & Hložek. This may include researching suitable methods/algorithms for the code.
Participate in regular meetings (~weekly) with team members, with flexibility regarding in-person or remote attendance.
Possibly participate in ~weekly telecons with other SO researchers.
Optionally attend training sessions and seminars for undergraduate researchers offered in the department of Astronomy & Astrophysics.
This is a full time position, but apart from meetings (schedules TBD), work hours are flexible.

Year: 2024

Researcher:
Adam Hincks, David A. Dunlap Department of Astronomy and Astrophysics, Faculty of Arts & Science, University of Toronto

Student:
Maxwell Bridgewater, University of Toronto

Through SUDS, undergraduate students engage in hands-on research focused on data sciences and AI methodology applications.

Learn more

Research description:

The Simons Observatory (SO) is a new, multi-telescope experiment to study the origin and evolution of the cosmos by measuring the cosmic microwave background (CMB), the oldest light in the Universe. Raw data consist of TBs of timestreams of measured sky brightness recorded each day—adding up to several PB over several years—that need to be reconstructed into 2D maps. However, before this can happen, the timestreams need to be automatically processed to remove noise contaminants and foreground galaxies/stars that block the main signal. The successful candidate will join the research groups of Profs. Adam Hincks and Renée Hložek that are actively researching machine learning methods to identify and classify these objects, using existing data from the Atacama Cosmology Telescope (ACT), a precursor to SO. Possible projects include characterising and improving deep learning techniques (including combining multi-modal data and using attention mapping) for detecting and classifying events in the telescope’s raw timestreams and contributing to the data processing pipeline of SO. An exciting aspect of this project is that our classification will help enable the search for astrophysical transients, such as flaring stars and gamma ray bursts.

Year: 2025

Researcher:
Adam Hincks, David A. Dunlap Department of Astronomy and Astrophysics, Faculty of Arts and Science University of Toronto

Students:
Mehtab Cheema, University of Toronto
Abdulaziz Saad Alkharjy, King Abdullah University of Science & Technology
Anas Abdulrahman Alshehri, King Abdullah University of Science & Technology

Through SUDS, undergraduate students engage in hands-on research focused on data sciences and AI methodology applications.

Learn more