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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
IEEE DataPort™
Dataset . 2022
License: CC BY
Data sources: Datacite
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Quantum Volume in Practice: What Users Can Expect from NISQ Devices Dataset

Authors: Pelofske, Elijah; Bärtschi, Andreas; Eidenbenz, Stephan;

Quantum Volume in Practice: What Users Can Expect from NISQ Devices Dataset

Abstract

Quantum volume (QV) has become the de-facto standard benchmark to quantify the capability of Noisy Intermediate-Scale Quantum (NISQ) devices. While QV values are often reported by NISQ providers for their systems, we perform our own series of QV calculations on more than 20 NISQ devices currently (2021/2022) offered by IBM Q, IonQ, Rigetti, Oxford Quantum Circuits, and Quantinuum (formerly Honeywell). Our approach characterizes the performances that an advanced user of these NISQ devices can expect to achieve with a reasonable amount of optimization, but without white-box access to the device. In particular, we compile QV circuits to standard gate sets of the vendor using compiler optimization routines where available, and we perform experiments across different initial qubit mappings. We find that running QV tests requires very significant compilation cycles, QV values achieved in our tests typically lag behind officially reported results and also depend significantly on the classical compilation effort invested. This dataset is comprised of the compiled (and un-compiled) circuits generated for this analysis.

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Keywords

NISQ devices, Quantum Volume, Quantum Computing

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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