Our group at Deakin University undertakes research in a broad area of Quantum IT, which includes Quantum Information Processing, Quantum Computing, Quantum Machine Learning and Quantum Optimisation. Our members also collaborate with other research groups at Deakin, such as Cyber Security, AI and Software Engineering, forming joint projects and partnering with quantum scholars and practitioners outside Deakin. The following is a list of the Quantum IT @ Deakin research areas and our researchers.
Any general inquiry about Quantum IT research, please contact Ria Rushin Joseph
Quantum information processing is an interdisciplinary area of investigation intersecting quantum mechanics and information theory. It provides fundamental theories and foundation for quantum computing, including the study of quantum information theory, quantum communication, error correction and cryptography, cyber security, etc.
Its study is also relevant to disciplines such as cognitive science, psychology and neuroscience.
Quantum computing is a new technology that employs quantum machines, which are based on the principles of quantum mechanics, to deal with computation thought impossible to perform on classical computers. Quantum computing finds its applications in areas where quantum computing is able to simulate the natural processes, e.g. in chemistry or physics. However, it has also been successful in solving some of the most complex problems in finance, economics, logistics and machine learning.
Quantum machine learning is the study of quantum algorithms capable of performing machine learning functions, such as neural networks or kernel models. It explores novel ways of representing and processing quantum information to derive intelligent outcomes. Some of quantum machine learning algorithms rely on purely quantum processing, however, more often hybrid methods are used to combine classical and quantum processing, where the most complex aspects of computation take place on quantum devices.
Researchers:
External Collaborators:
Research students:
Tim Nguyen (SIT Hons)
Quantum optimization explores the use of quantum algorithms and their execution on quantum computers to deal with very complex optimization problems. Quantum optimization pursues novel approaches to optimization, which combine massively parallel computation of quantum devices and their natural ability for effective stochastic processing, to deliver solutions that are effective in solving a wide variety of complex problems and at the same time are highly efficient.