212 citations · 443 across the 5 of their papers we have counts for
14 papers · 1 filter
An Invitation to Distributed Quantum Neural Networks
Lirandë Pira, Chris Ferrie
Deep neural networks have established themselves as one of the most promising machine learning techniques. Training such models at large scales is often parallelized, giving rise t…
Robust and Efficient High-dimensional Quantum State Tomography
Markus Rambach, Mahdi Qaryan, Michael Kewming +3
The exponential growth in Hilbert space with increasing size of a quantum system means that accurately characterising the system becomes significantly harder with system dimension…
Quantum Geometric Machine Learning for Quantum Circuits and Control
Elija Perrier, Christopher Ferrie, Dacheng Tao
The application of machine learning techniques to solve problems in quantum control together with established geometric methods for solving optimisation problems leads naturally to…
Beyond Quantum Noise Spectroscopy: modelling and mitigating noise with quantum feature engineering
Akram Youssry, Gerardo A. Paz-Silva, Christopher Ferrie
The ability to use quantum technology to achieve useful tasks, be they scientific or industry related, boils down to precise quantum control. In general it is difficult to assess a…
Experimental realization of self-guided quantum process tomography
Zhibo Hou, Jun-Feng Tang, Christopher Ferrie +3
Characterization of quantum processes is a preliminary step necessary in the development of quantum technology. The conventional method uses standard quantum process tomography, wh…
Modeling and Control of a Reconfigurable Photonic Circuit using Deep Learning
Akram Youssry, Robert J. Chapman, Alberto Peruzzo +2
The complexity of experimental quantum information processing devices is increasing rapidly, requiring new approaches to control them. In this paper, we address the problems of pra…