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000617836 005__ 20250115142352.0
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000617836 0247_ $$2arXiv$$aarXiv:2401.10293
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000617836 037__ $$aPUBDB-2024-07090
000617836 041__ $$aEnglish
000617836 088__ $$2arXiv$$aarXiv:2401.10293
000617836 082__ $$a530
000617836 1001_ $$aTüysüz, Cenk$$b0
000617836 245__ $$aSymmetry Breaking in Geometric Quantum Machine Learning in the Presence of Noise
000617836 260__ $$c2024
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000617836 520__ $$aGeometric quantum machine learning based on equivariant quantum neural networks (EQNNs) recently appeared as a promising direction in quantum machine learning. Despite encouraging progress, studies are still limited to theory, and the role of hardware noise in EQNN training has never been explored. This work studies the behavior of EQNN models in the presence of noise. We show that certain EQNN models can preserve equivariance under Pauli channels, while this is not possible under the amplitude damping channel. We claim that the symmetry breaks linearly in the number of layers and noise strength. We support our claims with numerical data from simulations as well as hardware up to 64 qubits. Furthermore, we provide strategies to enhance the symmetry protection of EQNN models in the presence of noise.
000617836 536__ $$0G:(DE-HGF)POF4-611$$a611 - Fundamental Particles and Forces (POF4-611)$$cPOF4-611$$fPOF IV$$x0
000617836 536__ $$0G:(EU-Grant)101087126$$aQUEST - QUantum computing for Excellence in Science and Technology (101087126)$$c101087126$$fHORIZON-WIDERA-2022-TALENTS-01$$x1
000617836 588__ $$aDataset connected to CrossRef, INSPIRE, Journals: bib-pubdb1.desy.de
000617836 650_7 $$2INSPIRE$$amachine learning: quantum
000617836 650_7 $$2INSPIRE$$aneural network: quantum
000617836 650_7 $$2INSPIRE$$anoise
000617836 650_7 $$2INSPIRE$$ahardware
000617836 650_7 $$2INSPIRE$$asymmetry breaking
000617836 650_7 $$2INSPIRE$$aqubit
000617836 650_7 $$2INSPIRE$$aPauli
000617836 693__ $$0EXP:(DE-MLZ)NOSPEC-20140101$$5EXP:(DE-MLZ)NOSPEC-20140101$$eNo specific instrument$$x0
000617836 7001_ $$00000-0001-5768-2434$$aChang, Su Yeon$$b1
000617836 7001_ $$aDemidik, Maria$$b2
000617836 7001_ $$0P:(DE-H253)PIP1003636$$aJansen, Karl$$b3$$eCorresponding author
000617836 7001_ $$aVallecorsa, Sofia$$b4
000617836 7001_ $$00000-0003-1718-1314$$aGrossi, Michele$$b5
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000617836 9101_ $$0I:(DE-588b)2008985-5$$6P:(DE-H253)PIP1003636$$aDeutsches Elektronen-Synchrotron$$b3$$kDESY
000617836 9131_ $$0G:(DE-HGF)POF4-611$$1G:(DE-HGF)POF4-610$$2G:(DE-HGF)POF4-600$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bForschungsbereich Materie$$lMatter and the Universe$$vFundamental Particles and Forces$$x0
000617836 9141_ $$y2024
000617836 915__ $$0StatID:(DE-HGF)0580$$2StatID$$aPublished
000617836 9201_ $$0I:(DE-H253)CQTA-20221102$$kCQTA$$lCentre f. Quantum Techno. a. Application$$x0
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