activity
20162020
most citedExperimental Comparison of Two Quantum Computing Architectures

522 citations · 671 across the 3 of their papers we have counts for

collaborators

12 papers

quant-ph2020

Probing many-body localization on a noisy quantum computer

D. Zhu, S. Johri, N. H. Nguyen +5

A disordered system of interacting particles exhibits localized behavior when the disorder is large compared to the interaction strength. Studying this phenomenon on a quantum comp…

physics.atom-ph2020

Efficient sideband cooling protocol for long trapped-ion chains

J. -S. Chen, K. Wright, N. C. Pisenti +5

Trapped ions are a promising candidate for large scale quantum computation. Several systems have been built in both academic and industrial settings to implement modestly-sized qua…

quant-ph20196 cited

Noise reduction using past causal cones in variational quantum algorithms

Omar Shehab, Isaac H. Kim, Nhung H. Nguyen +5

We introduce an approach to improve the accuracy and reduce the sample complexity of near term quantum-classical algorithms. We construct a simpler initial parameterized quantum st…

physics.atom-ph2019

Two-qubit entangling gates within arbitrarily long chains of trapped ions

Kevin A. Landsman, Yukai Wu, Pak Hong Leung +5

Ion trap systems are a leading platform for large scale quantum computers. Trapped ion qubit crystals are fully-connected and reconfigurable, owing to their long range Coulomb inte…

quant-ph2019

Toward convergence of effective field theory simulations on digital quantum computers

Omar Shehab, Kevin A. Landsman, Yunseong Nam +5

We report results for simulating an effective field theory to compute the binding energy of the deuteron nucleus using a hybrid algorithm on a trapped-ion quantum computer. Two inc…

quant-ph2018

Training of Quantum Circuits on a Hybrid Quantum Computer

D. Zhu, N. M. Linke, M. Benedetti +10

Generative modeling is a flavor of machine learning with applications ranging from computer vision to chemical design. It is expected to be one of the techniques most suited to tak…