activity
20092021
most citedExperimental Investigation of an Eight Qubit Unit Cell in a Superconducting Optimization Processor

281 citations · 1.1k across the 9 of their papers we have counts for

collaborators

10 papers

quant-ph2021★ 11 cited

Architectural considerations in the design of a third-generation superconducting quantum annealing processor

Kelly Boothby, Colin Enderud, Trevor Lanting +46

Early generations of superconducting quantum annealing processors have provided a valuable platform for studying the performance of a scalable quantum computing technology. These s…

quant-ph2019★ 153 cited

Scaling advantage in quantum simulation of geometrically frustrated magnets

Andrew D. King, Jack Raymond, Trevor Lanting +51

The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter s…

cs.LG2019

MIOpen: An Open Source Library For Deep Learning Primitives

Jehandad Khan, Paul Fultz, Artem Tamazov +12

Deep Learning has established itself to be a common occurrence in the business lexicon. The unprecedented success of deep learning in recent years can be attributed to: abundance o…

quant-ph2019★ 66 cited

Demonstration of nonstoquastic Hamiltonian in coupled superconducting flux qubits

I. Ozfidan, C. Deng, A. Y. Smirnov +45

Quantum annealing (QA) is a heuristic algorithm for finding low-energy configurations of a system, with applications in optimization, machine learning, and quantum simulation. Up t…

quant-ph2015★ 13 cited

A frequency and sensitivity tunable microresonator array for high-speed quantum processor readout

J. D. Whittaker, L. J. Swenson, M. H. Volkmann +18

Superconducting microresonators have been successfully utilized as detection elements for a wide variety of applications. With multiplexing factors exceeding 1,000 detectors per tr…

quant-ph2014★ 195 cited

Entanglement in a quantum annealing processor

T. Lanting, A. J. Przybysz, A. Yu. Smirnov +23

Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable by classical approaches. One such algorithm, quantum annealing (QA), provides a…

cond-mat.supr-con2010★ 16 cited

Observation of Co-tunneling in Pairs of Coupled Flux Qubits

T. Lanting, R. Harris, J. Johansson +17

We report measurements of macroscopic resonant tunneling between the two lowest energy states of a pair of magnetically coupled rf-SQUID flux qubits. This technique provides a dire…

cond-mat.supr-con2010★ 281 cited

Experimental Investigation of an Eight Qubit Unit Cell in a Superconducting Optimization Processor

R. Harris, M. W. Johnson, T. Lanting +23

A superconducting chip containing a regular array of flux qubits, tunable interqubit inductive couplers, an XY-addressable readout system, on-chip programmable magnetic memory, and…

cond-mat.supr-con2009★ 184 cited

Experimental Demonstration of a Robust and Scalable Flux Qubit

R. Harris, J. Johansson, A. J. Berkley +16

A novel rf-SQUID flux qubit that is robust against fabrication variations in Josephson junction critical currents and device inductance has been implemented. Measurements of the pe…

quant-ph2009★ 169 cited

A scalable control system for a superconducting adiabatic quantum optimization processor

M. W. Johnson, P. Bunyk, F. Maibaum +10

We have designed, fabricated and operated a scalable system for applying independently programmable time-independent, and limited time-dependent flux biases to control superconduct…