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dc.contributor.authorMüssig,Daniel
dc.contributor.authorLässig,Jörg
dc.contributor.editorDemmler, Daniel
dc.contributor.editorKrupka, Daniel
dc.contributor.editorFederrath, Hannes
dc.date.accessioned2022-09-28T17:09:57Z
dc.date.available2022-09-28T17:09:57Z
dc.date.issued2022
dc.identifier.isbn978-3-88579-720-3
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/39461
dc.description.abstractQuantum computing is an exciting field, which brought out many competitors, both on the hardware and algorithmic side. Although users are not expecting to outperform classical machines yet, they are still interested in quantum computers, which can demonstrate advantages of their algorithms best. However, for users, especially in the industry, it is not easy to find a quantum device, which fits their needs. This problem arises from an unmanageable amount of meta information about qubits and connections between them such as fidelity, error rates and timings. In this paper we propose a web tool, which helps the user to find quantum computers best suited for their problem or quantum algorithm. Further, it will generate necessary graphs and reports for benchmark studies, which can be directly included in papers of scientists.en
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-326
dc.subjectQuantum Computing
dc.subjectQuantum Device
dc.subjectQuantum Algorithm
dc.subjectBenchmark Study
dc.titleQuantum Computer and Quantum Algorithm Benchmarkingen
mci.reference.pages1175-1178
mci.conference.sessiontitleGI Quantum Computing Workshop
mci.conference.locationHamburg
mci.conference.date26.-30. September 2022
dc.identifier.doi10.18420/inf2022_100


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