in physics, with specialisation in quantum computation. My research was supervised by Prof. Lloyd Hollenberg and Dr. Charles Hill, where I developed a distributed memory tensor network library for simulating noisy and noiseless quantum circuits. In particular, we used this library as an alternative approach to the classical simulations described in Google's quantum supremacy paper. Additionally, we were able to claim a record for the largest quantum circuit ever simulated at the time, a feat which received a nomination for the 2018 HPCwire Readers' Choice for Top Supercomputing Achievement.
diploma awarded for piano
In this role, I was a core developer and designer for the QUI, a quantum user interface for constructing, simulating and visualising circuits for quantum computing algorithms. Specifically, I was responsible for the React-based frontend, C++ backend simulation engine, authentication system, and a considerable portion of the Node.js-based web backend and production deployment. This tool has been successfully integrated as part of a new graduate course at The University of Melbourne, its first subject in quantum information science.
Supervised by A/Prof. Martin Sevior during this summer position, I was tasked with evaluating the then-new TensorFlow library for machine learning in particle physics, including integrating it with the current particle physics toolchain. This work was presented at the CHEP 2016 Conference in San Francisco.
A. Dang, C. D. Hill, and L. C. L. Hollenberg
Note: Chapter 3 of this thesis has been superseded by the above paper