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most citedQuantum Algorithm Exploration using Application-Oriented Performance Benchmarks

3 citations · 3 across the 2 of their papers we have counts for

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quant-ph2026

Benchmarking the computational power of quantum computers

Timothy Proctor, Oliver Hart, Oliver Widzowski Maupin +27

Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare r…

quant-ph2025

Easier randomizing gates provide more accurate fidelity estimation

Debankan Sannamoth, Kristine Boone, Arnaud Carignan-Dugas +4

Accurate benchmarking of quantum gates is crucial for understanding and enhancing the performance of quantum hardware. A standard method for this is interleaved benchmarking, a tec…

quant-ph2025

Digital quantum magnetism on a trapped-ion quantum computer

Reza Haghshenas, Eli Chertkov, Michael Mills +56

Digital quantum matter -- realized when discrete quantum gates approximate continuous time evolution -- is susceptible to heating into chaotic, structureless states. If digitizatio…

quant-ph2024

The computational power of random quantum circuits in arbitrary geometries

Matthew DeCross, Reza Haghshenas, Minzhao Liu +49

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimens…

quant-ph20243 cited

Quantum Algorithm Exploration using Application-Oriented Performance Benchmarks

Thomas Lubinski, Joshua J. Goings, Karl Mayer +11

The QED-C suite of Application-Oriented Benchmarks provides the ability to gauge performance characteristics of quantum computers as applied to real-world applications. Its benchma…