This project aims to provide a solution to a critical problem in existing superconducting quantum processors by developing methods to create long-range interactions. Superconducting qubits are one of the most promising platforms for building quantum computers. Currently, quantum processors based on this technology offer the largest quantum memories, but do not benchmark well in terms […]

Given a group of molecules and a specification of reaction conditions, do chemical reactions occur? If so, what products are produced, and what is their relative abundance? This problem pervades chemistry, with applications in environmental science (e.g., the degradation of pollutants), molecular sensing (e.g., interpreting the results of tandem mass spectrometry), chemical synthesis (e.g., finding […]

In order to understand how chemical bonds fracture and form, and to predict how electrons rearrange in photoactive materials, one must describe the electron structure of the substances. This requires evaluating a quantum-mechanical model for the system. Unfortunately, accurate quantum-mechanical models require enormous computational resources, and can only be applied for tiny systems. For systems […]

In this project, the intern will work with an expert team from the company Zapata, to compare the performances of machine learning models on classical computers and on quantum models in terms of generalization to unseen data

Transient electronics and their dissolution byproducts, are usually harmless and benign, and hence they are an attractive approach for the global e-waste problem especially for low-cost, one time use devices such as RFID tag antennas. For this research, a straightforward laser-induced method of environmentally friendly reduced Graphene Oxide films is proposed for fabricating transient RFID […]

Quantum computers have the potential to perform computational tasks which are impossible to solve on classical computers. One natural application of quantum computing is to use them for predicting how quantum mechanical systems (e.g., models of quantum magnetism or chemical molecules) evolve in time. However, existing quantum computers – so-called noisy intermediate-scale quantum (NISQ) devices […]

In this project, we will develop innovative AI tools to speed up the process of catalyst discovery, in particular in the domain of renewable energy. Specific catalysts are essential to applications such as the efficient synthesis of solar fuels and fertilizer. However, many known catalysts are suboptimal in their efficacy or require scarce elements. Currently, […]

An organism’s genome contains the information necessary for its development. Part of this information is used as “instructions” for cells to synthesize molecules called proteins, which perform most of the cell’s functions. However, over time, changes to the genomic information can occur. These changes (mutations) can have all kinds of effects: some might cause diseases, […]

Magnetometers have been used for decades for exploration in mining, navigation and defence and security. However, high accuracy sensors often provide only the amplitude of magnetic fields, severely limiting the extent of magnetic interpretations. A novel type of quantum magnetometers based on Nitrogen Vacancy centers in diamond promise enhanced sensitivity and accuracy, while providing the […]

Photons are particles of light. While countless numbers are emitted from a light source to illuminate a room, sensitive electronics can detect light down to the level of a single photon. These electronic devices, known as single photon avalanche diodes (SPADs), use a process that triggers an avalanche of electrical charges, which can be measured […]

Foqus Technologies Inc. provides solutions based on Quantum Information algorithms and Machine Learning techniques to enhance the sensitivity of Magnetic Resonance Technologies such as MRI and Nuclear Magnetic Resonance (NMR). We are developing a software solution that implements our proprietary quantum algorithms and enhances the MRI/NMR. Although there are various potential market applications and opportunities, […]

The Mitacs Globalink Award will empower an interdisciplinary research effort which is geared towards the realization of a prototype Compact Accelerator-based Neutron Source in Canada (CANS) at the University of Windsor. Three beamlines are being planned for the CANS facility and they are intended to serve applications in materials sciences, medical sciences and fluorine-18 radioisotope […]