activity
20172021
most citedStroboscopic qubit measurement with squeezed illumination

56 citations · 79 across the 5 of their papers we have counts for

collaborators

14 papers

quant-ph20211 cited

Characterizing mid-circuit measurements on a superconducting qubit using gate set tomography

Kenneth Rudinger, Guilhem J. Ribeill, Luke C. G. Govia +6

Measurements that occur within the internal layers of a quantum circuit -- mid-circuit measurements -- are an important quantum computing primitive, most notably for quantum error…

cond-mat.supr-con202111 cited

Reservoir Computing with Superconducting Electronics

Graham E. Rowlands, Minh-Hai Nguyen, Guilhem J. Ribeill +5

The rapidity and low power consumption of superconducting electronics makes them an ideal substrate for physical reservoir computing, which commandeers the computational power inhe…

quant-ph2021

Deep Neural Network Discrimination of Multiplexed Superconducting Qubit States

Benjamin Lienhard, Antti Vepsäläinen, Luke C. G. Govia +15

Demonstrating a quantum computational advantage will require high-fidelity control and readout of multi-qubit systems. As system size increases, multiplexed qubit readout becomes a…

cs.NE2021

Symmetry-Aware Reservoir Computing

Wendson A. S. Barbosa, Aaron Griffith, Graham E. Rowlands +5

We demonstrate that matching the symmetry properties of a reservoir computer (RC) to the data being processed dramatically increases its processing power. We apply our method to th…

quant-ph20219 cited

Neuromorphic computing with a single qudit

W. D. Kalfus, G. J. Ribeill, G. E. Rowlands +3

Accelerating computational tasks with quantum resources is a widely-pursued goal that is presently limited by the challenges associated with high-fidelity control of many-body quan…

quant-ph2020

Quantum reservoir computing with a single nonlinear oscillator

L. C. G. Govia, G. J. Ribeill, G. E. Rowlands +2

Realizing the promise of quantum information processing remains a daunting task, given the omnipresence of noise and error. Adapting noise-resilient classical computing modalities…