Lately, much attention has been given to quantum algorithms that solve pattern recognition tasks in machine learning. Many of these quantum machine learning algorithms try to implement classical models on large-scale universal quantum
computers that have access to non-trivial subroutines such as Hamiltonian simulation, amplitude amplification and phase estimation.
Recently, the problem has been approached from the opposite direction and it was shown that a distance-based classifier can be realised by a simple quantum interference circuit [M. Schuld, M. Fingerhuth, F. Petruccione, EPL 119 (2017) 60002]. After state preparation, the circuit only consists of a Hadamard gate as well as two single-qubit measurements and can be implemented with small-scale setups available today, such as the IBM Quantum Experience.
Potential extensions of the above quantum interference circuit approach can help to analyse quantum machine learning on real quantum processors, and create models for pattern recognition that are inspired by the strengths of quantum computing.
Future work could aim at amending the circuit to realise different kernel functions that allow for more localised measures in order to increase the power and flexibility of the classifier, as well as considering circuits that make more use of quantum resources such as entanglement. Furthermore, one can extend the perspective presented here fruitfully to more general quantum devices and ask if their evolution can solve a learning problem. We expect this question to become a much more prominent future research topic of quantum machine learning.
Francesco Petruccione was born in 1961 in Genova (Italy). He studied Physics at the University of Freiburg Br. and received his PhD in 1988. He was conferred the Habilitation degree (Dr. rer. nat. habil.) from the same University in 1994. In 2004 he was appointed Professor of Theoretical Physics at the University of KwaZulu-Natal, in Durban (South Africa). In 2005 he was awarded an Innovation Fund grant to set up a Centre for Quantum Technology. In 2007 he was granted a South African Research Chair for Quantum Information Processing and Communication. At present, he is also one of the Deputy Directors of the National Institute for Theoretical Physics.
He has published more than 170 papers in refereed scientific journals. He is the co-author of a monograph on “The Theory of Open Quantum Systems” (about 6000 citations according to Google Scholar), that was published in 2002, reprinted as paperback in 2007, and recently translated in Russian. He is a member the Editorial Board of “Open Systems and Information Dynamics” and “Scientific Reports”. He is the editor of several proceedings volumes and of special editions of scientific journals. He is currently writing a book on Quantum Machine Learning.