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Quantum DevOps: Towards reliable and applicable NISQ Quantum Computing

: Gheorghe-Pop, Ilie-Daniel; Tcholtchev, Nikolay; Ritter, Tom; Hauswirth, Manfred

Preprint urn:nbn:de:0011-n-6333475 (1.1 MByte PDF)
MD5 Fingerprint: 577313015356b922923d37e78f5be86a
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Erstellt am: 19.3.2021

Institute of Electrical and Electronics Engineers -IEEE-:
IEEE Globecom Workshops, GC Wkshps 2020. Proceedings : Virtual conference, 7-11 December 2020
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-7281-7308-5
ISBN: 978-1-7281-7307-8
6 S.
Global Communications Conference (GLOBECOM) <2020, Online>
Workshop on Quantum Communications and Information Technology <2020, Online>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer FOKUS ()
Quantum DevOps; quantum computing; DevOps; testing; framework; IT

Quantum Computing is emerging as one of the great hopes for boosting current computational resources and enabling the application of ICT for optimizing processes and solving complex and challenging domain specific problems. However, the Quantum Computing technology has not matured to a level where it can provide a clear advantage over high performance computing yet. Towards achieving this "quantum advantage", a larger number of Qubits is required, leading inevitably to a more complex topology of the computing Qubits. This raises additional difficulties with decoherence times and implies higher Qubit error rates. Nevertheless, the current Noisy Intermediate-Scale Quantum (NISQ) computers can prove useful despite the intrinsic uncertainties on the quantum hardware layer. In order to utilize such error-prone computing resources, various concepts are required to address Qubit errors and to deliver successful computations. In this paper describe and motivate the need for the novel concept of Quantum DevOps. which entails regular checking of the reliability of NISQ Quantum Computing (QC) instances. By means of testing the computational reliability of basic quantum gates and computations (C-NOT, Hadamard, etc.)it consequently estimates the likelihood for a large scale critical computation (e.g. calculating hourly traffic flow models for a city) to provide results of sufficient quality. Following this approach to select the best matching (cloud) QC instance and having it integrated directly with the processes of development, testing and finally the operations of quantum based algorithms and systems enables the Quantum DevOps concept.