activity
20172023
most citedScaling advantage in quantum simulation of geometrically frustrated magnets

153 citations · 247 across the 7 of their papers we have counts for

collaborators

7 papers

quant-ph2023★ 1 cited

Quantum error mitigation in quantum annealing

Mohammad H. Amin, Andrew D. King, Jack Raymond +32

Quantum Error Mitigation (QEM) presents a promising near-term approach to reduce error when estimating expectation values in quantum computing. Here, we introduce QEM techniques ta…

quant-ph2022★ 5 cited

Probing flux and charge noise with macroscopic resonant tunneling

Alexander M. Whiticar, Anatoly Y. Smirnov, Trevor Lanting +8

We report on measurements of flux and charge noise in an rf-SQUID flux qubit using macroscopic resonant tunneling (MRT). We measure rates of incoherent tunneling from the lowest en…

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-ph2020★ 11 cited

Probing Environmental Spin Polarization with Superconducting Flux Qubits

T. Lanting, M. H. Amin, C. Baron +6

We present measurements of the dynamics of a polarized magnetic environment coupled to the flux degree of freedom of rf-SQUID flux qubits. The qubits are used as both sources of po…

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…

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-ph2017

Algorithms for Embedding Quantum-Dot Cellular Automata Networks onto a Quantum Annealing Processor

Jacob Retallick, Michael Babcock, Miguel Aroca-Ouellette +5

Advancements in computing based on qubit networks, and in particular the flux-qubit processor architecture developed by D-Wave System's Inc., have enabled the physical simulation o…