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20182022
most citedError mitigation increases the effective quantum volume of quantum computers

8 citations · 8 across the 2 of their papers we have counts for

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quant-ph20228 cited

Error mitigation increases the effective quantum volume of quantum computers

Ryan LaRose, Andrea Mari, Vincent Russo +2

Quantum volume is a single-number metric which, loosely speaking, reports the number of usable qubits on a quantum computer. While improvements to the underlying hardware are a dir…

quant-ph2022

Logical shadow tomography: Efficient estimation of error-mitigated observables

Hong-Ye Hu, Ryan LaRose, Yi-Zhuang You +2

We introduce a technique to estimate error-mitigated expectation values on noisy quantum computers. Our technique performs shadow tomography on a logical state to produce a memory-…

quant-ph2020

Digital zero noise extrapolation for quantum error mitigation

Tudor Giurgica-Tiron, Yousef Hindy, Ryan LaRose +2

Zero-noise extrapolation (ZNE) is an increasingly popular technique for mitigating errors in noisy quantum computations without using additional quantum resources. We review the fu…

quant-ph2020

Robust data encodings for quantum classifiers

Ryan LaRose, Brian Coyle

Data representation is crucial for the success of machine learning models. In the context of quantum machine learning with near-term quantum computers, equally important considerat…

quant-ph2018

Variational Quantum State Diagonalization

Ryan LaRose, Arkin Tikku, Étude O'Neel-Judy +2

Variational hybrid quantum-classical algorithms are promising candidates for near-term implementation on quantum computers. In these algorithms, a quantum computer evaluates the co…

quant-ph2018

Overview and Comparison of Gate Level Quantum Software Platforms

Ryan LaRose

Quantum computers are available to use over the cloud, but the recent explosion of quantum software platforms can be overwhelming for those deciding on which to use. In this paper,…