activity
20172022
most citedSupplementary information for "Quantum supremacy using a programmable superconducting processor"

7.2k citations · 8.8k across the 9 of their papers we have counts for

collaborators

10 papers

quant-ph2022★ 10 cited

Simulating Majorana zero modes on a noisy quantum processor

Kevin J. Sung, Marko J. Rančić, Olivia T. Lanes +1

The simulation of systems of interacting fermions is one of the most anticipated applications of quantum computers. The most interesting simulations will require a fault-tolerant q…

quant-ph2020★ 95 cited

Observation of separated dynamics of charge and spin in the Fermi-Hubbard model

Frank Arute, Kunal Arya, Ryan Babbush +96

Strongly correlated quantum systems give rise to many exotic physical phenomena, including high-temperature superconductivity. Simulating these systems on quantum computers may avo…

quant-ph2020★ 66 cited

Using models to improve optimizers for variational quantum algorithms

Kevin J. Sung, Jiahao Yao, Matthew P. Harrigan +5

Variational quantum algorithms are a leading candidate for early applications on noisy intermediate-scale quantum computers. These algorithms depend on a classical optimization out…

cond-mat.str-el2020★ 22 cited

Creating and manipulating a Laughlin-type fractional quantum Hall state on a quantum computer with linear depth circuits

Armin Rahmani, Kevin J. Sung, Harald Putterman +3

Here we present an efficient quantum algorithm to generate an equivalent many-body state to Laughlin's fractional quantum Hall state on a digitized quantum computer. Our al…

quant-ph2020★ 469 cited

Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor

Matthew P. Harrigan, Kevin J. Sung, Matthew Neeley +83

We demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algor…

quant-ph2020★ 731 cited

Hartree-Fock on a superconducting qubit quantum computer

Frank Arute, Kunal Arya, Ryan Babbush +79

As the search continues for useful applications of noisy intermediate scale quantum devices, variational simulations of fermionic systems remain one of the most promising direction…

quant-ph2019★ 7.2k cited

Supplementary information for "Quantum supremacy using a programmable superconducting processor"

Frank Arute, Kunal Arya, Ryan Babbush +74

This is an updated version of supplementary information to accompany "Quantum supremacy using a programmable superconducting processor", an article published in the October 24, 201…

quant-ph2019★ 79 cited

Learning to learn with quantum neural networks via classical neural networks

Guillaume Verdon, Michael Broughton, Jarrod R. McClean +5

Quantum Neural Networks (QNNs) are a promising variational learning paradigm with applications to near-term quantum processors, however they still face some significant challenges.…

quant-ph2017★ 162 cited

Quantum algorithms to simulate many-body physics of correlated fermions

Zhang Jiang, Kevin J. Sung, Kostyantyn Kechedzhi +2

Simulating strongly correlated fermionic systems is notoriously hard on classical computers. An alternative approach, as proposed by Feynman, is to use a quantum computer. Here, we…

quant-ph2017

OpenFermion: The Electronic Structure Package for Quantum Computers

Jarrod R. McClean, Kevin J. Sung, Ian D. Kivlichan +32

Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and…