Grants and Contributions

The periods before and during the formation of the first stars in the Universe, known respectively as the Dark Ages and Cosmic Dawn, remain almost completely unexplored. In the current paradigm of cosmology, the first stars formed within the first 100 million years of the Universe, and studying them through direct optical or infrared observations is not expected to be possible. Fortunately, the early Universe was filled with neutral hydrogen gas, out of which the first stars formed. Ultraviolet and X-ray radiation from the first stars and galaxies left an imprint on the 21 cm neutral hydrogen radiation, which is a promising observational tool for characterizing the first stars and galaxies.

This project consists of deploying custom-built radio telescopes at the extremely remote McGill Arctic Research Station (MARS), in the Canadian High Arctic, to attempt to observe the faint signal emitted by the first stars. The main purpose of this project is to use these telescopes as prototypes for a future space mission and test them at MARS, which will be used as a space analogue site. In addition to conducting the sky measurements, other objectives of this project include the characterization of the soil and topography at MARS, and the accurate calibration of the radio instruments in the laboratory before and after the MARS deployments. Broader objectives include the hands-on training of students in all aspects of the project and the dissemination of results in conferences and scientific journals.

This project will enable, for the first time, testing of radio telescopes’ performance at a space analogue site. The expected outcomes include the verification of the performance of the telescopes, the experience gained by the team after operating these instruments at an extremely remote site, and the use of the sky measurements to test physical hypotheses about the first stars. The hands-on training received by the students will help them to strongly contribute to industry and academia. The measurement techniques to be demonstrated at MARS will go beyond the state-of-the-art in radio engineering and geophysics, and this project will promote Canadian participation in international partnerships.

A key question for astrobiology is the distribution of life in the universe. Presently, we have only one example of life which is found on Earth. However, there is evidence that habitable
environments once existed on Mars and might currently exist within the subsurface ocean of Enceladus, an icy moon of Saturn. Therefore, space agencies have great interest in searching for evidence of life on these planetary worlds, or to at least search for environments with conditions that are compatible with life as we know it.

A goal of this project is to inform and enable future methods for the search for life at Enceladus. In 2005, the Cassini mission revealed this icy ocean world to have plumes of gas containing CO2, organic compounds and H2 venting into space over the south polar region. At Lake Untersee, a perennially ice-covered lake in Antarctica, the deep anoxic basin with its unusual biogeochemical processes serves as an analog environment, providing a model for the study of the composition of the Enceladus plume and the potential habitability of its sub-ice ocean. This project seeks to determine the source of H2-CO2 in Untersee’s anoxic waters which drives many of the biochemical processes taking place, search for the presence of biosignatures, and determine the isotopic composition and concentration of other geochemical constituents. Our results will be used to investigate the possibility of a habitable subsurface ocean world at Enceladus. Using a remotely operated vehicle capable of exploring the anaerobic and aerobic waters within the sub-ice environment of Untersee, our project will map the distribution of the benthic microbial mats, characterize their various morphologies and collect sediment samples for additional laboratory analyses.

The objectives pursued in this project are highly relevant to the analyses of the gaseous constituents in the plumes of Enceladus, the analyses of carbon compounds from plume samples returned to Earth, or for the deployment of a penetrator into the subsurface ocean that would conduct in-situ experiments and image a possible ecosystem. Highly qualified personnel will be trained in space-related activities and will work with international co-applicants as well as Canadian industry partners where they will gain practical experience in the fields of astrobiology and technology. Our findings at Untersee will help inform and prepare future missions that will search for evidence of life on Enceladus.

Contribution agreement with the International Atomic Energy Agency to support the development of Safeguards e-Learning Modules

Contribution agreement to assist Algonquins of Pikwakanagan First Nation (AOPFN) in finalizing and implementing the AOPFN-CNSC Terms of Reference for Long-Term Engagement.

The objective of this Project is to support the participation of Indigenous groups on the Indigenous Advisory and Monitoring Committee for the Trans Mountain Expansion Project.

The objective of this project is capacity building activities that build knowledge and skills related to renewable energy and grid modernization projects in Canada.

This project advances the Government of Canada commitment to plant an additional two billion new trees over the next 10 years as part of a broader approach to nature-based climate solutions.

This project is to improve energy efficiency in Canada's residential sector.

This project is to improve energy efficiency in Canada's residential sector.

This Project will focus on adapting a general learning framework to improvements related to nanophotonic component design. Novel optimization techniques such as inverse design are promising tools to significantly reduce the size of nanophotonic components while maintaining their functionality and performance. Although published results demonstrate various proof of concept miniaturized devices with pre-determined size and aspect ratio, their performances as of now are inferior to the state of the art classical devices which are however much larger, with designs that are highly non-interpretable. In this respect, recent developments in learning generative models through the use of generative-adversarial architecture is a promising technological breakthrough. Specifically, this type of training provides a framework to build neural-network based models capable of generating a diverse set of useful data instances in high-dimensional spaces, which are well-performing designs in this context