The proposed project investigates an approach to solve difficult physics problems, which are too computationally intensive for standard computers, using Xanadu’s near-term quantum computers. The goal of the project is to create a simulation tool that harnesses the exponential increase in efficiency offered by quantum computers to simulate the movement of particles and the subsequent emitted radiation at the nanometer scale. These simulations could have practical implications for experiments involving optical and laser physics and could lead to further insights concerning atomic behaviour.
Biosensors are can detect a variety of molecules in a rapid and highly sensitive manner. A new biosensing technology was developed to allow scientists to customize the biomolecular target they wanted to detect, called an open-gated silicon junction field effect transistor (JFET). However, this technology lacks user friendly packaging needed accommodate its use in diverse research settings. This can discourage people from using and building new sensing platforms.
In Canada, as of April 21, only 569,878 people (~1.5% of the population) have been tested, with more than 38,413 positive COVID-19 cases identified; yet most people, including the asymptomatic COVID-19 cases, are not eligible for testing. Given that as many as 45% of all COVID-19 cases lack the known symptoms, or so-called asymptomatic cases, up to an estimated 17,000 cases could be asymptomatic and thus endangering public health. Moreover, these symptoms are not observed in the early stages of the disease, even in symptomatic cases.
The goal of this research project is to create a novel type of biosensor by combining two complimentary microfabrication techniques. First, a silicon chip containing JFET transistors with an open gate will be fabricated using traditional microfabrication techniques that are highly reliable and give good performance. Second, a graphene layer will be inkjet printed onto the open gate of the transistor. The graphene will act as a sensor transducer to sense pH or biological species such as insulin.
In 2014 a handheld DNA measurement device, the "MinION", was commercialized. It is 100X smaller by volume and 6X faster and 20X less expensive than the next smallest DNA measurement device on the market. But its measurements are of a lower quality, about 90% of measured DNA is accurately 'detected' compared to 99.9% for leading machines. Further, a tremendous amount of computing power is needed to carry out the detection function of the MinION. In fact, this is done by a standalone computer or GPU.