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A new Pattern for Quantum Evolutionary Algorithms

dc.contributor.authorReers,Volker
dc.contributor.authorLässig,Jörg
dc.contributor.editorDemmler, Daniel
dc.contributor.editorKrupka, Daniel
dc.contributor.editorFederrath, Hannes
dc.date.accessioned2022-09-28T17:11:04Z
dc.date.available2022-09-28T17:11:04Z
dc.date.issued2022
dc.description.abstractQuantum Evolutionary Algorithms have been discussed in the literature in different forms. One branch in these efforts studies approaches for the representation of genetic information, i.e., problem information, in terms of qubits. A typical downside of this representation has been the loss of quantum information in the evaluation and selection steps of the algorithm. I.e., algorithms are implemented in a hybrid-classical setup and require measurements in each iteration. This inevitably destroys superpositions and entanglement structures in the genome representation. In this work, we propose a new implementation approach for genetic information and the evaluation and selection phase, which realizes those steps within the quantum circuit. To achieve this, we utilize qudits for representing the evolving entities. Additionally, we make use of patterns for the design of quantum sub-circuits to compose control structures known from the classical realm. As a result, we show a quantum circuit design for anytime algorithms that does not have to be measured in every iteration and that does not depend on classical control. The overall progress of the evolutionary process only needs to be checked occasionally on a flag-qubit. The approach currently comes with some limitations e.g., in the objective function. It is presented here for the toy problem Leading Ones.en
dc.identifier.doi10.18420/inf2022_98
dc.identifier.isbn978-3-88579-720-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39603
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 Information Processing
dc.subjectQuantum Evolutionary Algorithm
dc.subjectQuantum Genetic Algorithm
dc.titleA new Pattern for Quantum Evolutionary Algorithmsen
gi.citation.endPage1162
gi.citation.startPage1153
gi.conference.date26.-30. September 2022
gi.conference.locationHamburg
gi.conference.sessiontitleGI Quantum Computing Workshop

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