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A Proposal for Physics-Informed Quantum Graph Neural Networks for Simulating Laser Cutting Processes

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dc.contributor.authorMehrin Ruhi, Zurana
dc.contributor.authorStein, Hannah
dc.contributor.authorMaaß, Wolfgang
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorWohlgemuth, Volker
dc.date.accessioned2023-11-29T14:50:24Z
dc.date.available2023-11-29T14:50:24Z
dc.date.issued2023
dc.description.abstractSimulations are crucial for production monitoring and planning in manufacturing. Still, the performance of simulations based on mathematical modeling and machine learning methods is limited and opaque to widespread application. Quantum computing offers the potential for exponential acceleration of these tools, while physically informed neural networks (PINN) improve learning and reduce ambiguity. Objective of this paper is to explore the concept of developing a tool for laser cutting simulation based on a quantum neural network that can be trained on thermal physics principles.en
dc.identifier.doi10.18420/inf2023_183
dc.identifier.isbn978-3-88579-731-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43111
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2023 - Designing Futures: Zukünfte gestalten
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-337
dc.subjectQuantum Computing
dc.subjectPINN
dc.subjectGraph Neural Network
dc.subjectPredictive Simulation
dc.titleA Proposal for Physics-Informed Quantum Graph Neural Networks for Simulating Laser Cutting Processesen
dc.typeText/Conference Paper
gi.citation.endPage1811
gi.citation.publisherPlaceBonn
gi.citation.startPage1809
gi.conference.date26.-29. September 2023
gi.conference.locationBerlin
gi.conference.sessiontitleWirtschaft, Management Industrie - Joint Workshop IntDig 2023 MOC 2023; Intelligente Digitalisierung, (KI-basiertes) Management und Optimierung komplexer Systeme

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P337 - INFORMATIK 2023 - Designing Futures: Zukünfte gestalten