Olivia Di MatteoQuantum Information Science Associate, TRIUMF | ||
Research TopicsThe focus of my research is quantum computing, and in particular minimizing the different resources required to do it. My major areas of work are: quantum tomography and designing more efficient ways to characterize quantum systems, and quantum circuit synthesis and optimization, the compilation of arbitrary quantum operations to those of a fixed, universal instruction set to be executed on hardware. More recently, I have been exploring with TRIUMF colleagues some applications of quantum annealers for particle physics problems, and improving the calculation of molecular energies using hybrid quantum-classical computing techniques. Much of my work makes use of high-performance computing and machine learning. I also like combinatorial designs, discrete math, and teaching people about quantum computing. Code | ||