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20182025
most citedQuantum optimization with arbitrary connectivity using Rydberg atom arrays

128 citations · 615 across the 18 of their papers we have counts for

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16 papers · 1 filter

quant-ph2025

Continuous-time quantum walk-based ansätze on neutral atom hardware

Edric Matwiejew, Jonathan Wurtz, Jing Chen +3

Continuous-time quantum walks offer provable speedups for certain computational problems, yet translating these advantages to near-term hardware remains challenging. We realize var…

quant-ph2024★ 2 cited

Non-native Quantum Generative Optimization with Adversarial Autoencoders

Blake A. Wilson, Jonathan Wurtz, Vahagn Mkhitaryan +5

Large-scale optimization problems are prevalent in several fields, including engineering, finance, and logistics. However, most optimization problems cannot be efficiently encoded…

quant-ph2024★ 9 cited

Large-scale quantum reservoir learning with an analog quantum computer

Milan Kornjača, Hong-Ye Hu, Chen Zhao +50

Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite t…

quant-ph2024

Solving non-native combinatorial optimization problems using hybrid quantum-classical algorithms

Jonathan Wurtz, Stefan Sack, Sheng-Tao Wang

Combinatorial optimization is a challenging problem applicable in a wide range of fields from logistics to finance. Recently, quantum computing has been used to attempt to solve th…

quant-ph2023★ 4 cited

Quantum dynamics of a fully-blockaded Rydberg atom ensemble

Dominik S. Wild, Sabina Drăgoi, Corbin McElhanney +2

Classical simulation of quantum systems plays an important role in the study of many-body phenomena and in the benchmarking and verification of quantum technologies. Exact simulati…

quant-ph2023★ 14 cited

Constant-Overhead Fault-Tolerant Quantum Computation with Reconfigurable Atom Arrays

Qian Xu, J. Pablo Bonilla Ataides, Christopher A. Pattison +7

Quantum low-density parity-check (qLDPC) codes can achieve high encoding rates and good code distance scaling, providing a promising route to low-overhead fault-tolerant quantum co…

quant-ph2023★ 28 cited

Aquila: QuEra's 256-qubit neutral-atom quantum computer

Jonathan Wurtz, Alexei Bylinskii, Boris Braverman +10

The neutral-atom quantum computer "Aquila" is QuEra's latest device available through the Braket cloud service on Amazon Web Services (AWS). Aquila is a "field-programmable qubit a…

quant-ph2022★ 128 cited

Quantum optimization with arbitrary connectivity using Rydberg atom arrays

Minh-Thi Nguyen, Jin-Guo Liu, Jonathan Wurtz +3

Programmable quantum systems based on Rydberg atom arrays have recently been used for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376, 1209…

quant-ph2022★ 33 cited

Sampling Frequency Thresholds for Quantum Advantage of Quantum Approximate Optimization Algorithm

Danylo Lykov, Jonathan Wurtz, Cody Poole +3

In this work, we compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with state-of-the-art classical solvers such as Gurobi and MQLib to solve the comb…

quant-ph2022★ 12 cited

Industry applications of neutral-atom quantum computing solving independent set problems

Jonathan Wurtz, Pedro L. S. Lopes, Christoph Gorgulla +3

Architectures for quantum computing based on neutral atoms have risen to prominence as candidates for both near and long-term applications. These devices are particularly well suit…

quant-ph2021★ 34 cited

QAOAKit: A Toolkit for Reproducible Study, Application, and Verification of the QAOA

Ruslan Shaydulin, Kunal Marwaha, Jonathan Wurtz +1

Understanding the best known parameters, performance, and systematic behavior of the Quantum Approximate Optimization Algorithm (QAOA) remain open research questions, even as the a…

quant-ph2021★ 4 cited

The fixed angle conjecture for QAOA on regular MaxCut graphs

Jonathan Wurtz, Danylo Lykov

The quantum approximate optimization algorithm (QAOA) is a near-term combinatorial optimization algorithm suitable for noisy quantum devices. However, little is known about perform…

quant-ph2021★ 113 cited

Counterdiabaticity and the quantum approximate optimization algorithm

Jonathan Wurtz, Peter J. Love

The quantum approximate optimization algorithm (QAOA) is a near-term hybrid algorithm intended to solve combinatorial optimization problems, such as MaxCut. QAOA can be made to mim…

quant-ph2021

Classically optimal variational quantum algorithms

Jonathan Wurtz, Peter Love

Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQA), are suitable for implementation on NISQ computers. In this Letter we expand an implicit step of V…

quant-ph2020★ 107 cited

MAXCUT QAOA performance guarantees for p >1

Jonathan Wurtz, Peter J. Love

We obtain worst case performance guarantees for and QAOA for MAXCUT on uniform 3-regular graphs. Previous work by Farhi et al obtained a lower bound on the approximation…

quant-ph2018★ 64 cited

Cluster Truncated Wigner Approximation in Strongly Interacting Systems

Jonathan Wurtz, Anatoli Polkovnikov, Dries Sels

We present a general method by which linear quantum Hamiltonian dynamics with exponentially many degrees of freedom is replaced by approximate classical nonlinear dynamics with the…