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000916699 037__ $$aFZJ-2023-00039
000916699 1001_ $$0P:(DE-Juel1)188287$$aPazem, Josephine$$b0$$eCorresponding author$$ufzj
000916699 1112_ $$aAPS March Meeting 2022$$cChicago$$d2022-03-14 - 2022-03-18$$wUSA
000916699 245__ $$aBeware of entropy phase transition! How to make quantum denoising successful?
000916699 260__ $$c2022
000916699 3367_ $$033$$2EndNote$$aConference Paper
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000916699 520__ $$aQuantum autoencoders can help to generate denoised entanglement on a noisy neural network. However noise outweighs the process if it gets too strong. [1]We show that the flow of Rényi entropy in a subnet can perform as a measure whose phase transition determines denoising success or failure. Moreover, we rely on the study to implement a deformation of the network that results in improved tolerance against heavier noises.References:[1] D. Bondarenko and P. Feldmann, “Quantum autoencoders to denoise quantum data,” Phys. Rev. Lett., vol. 124, no. 13, p. 130502, 2020.
000916699 536__ $$0G:(DE-HGF)POF4-5224$$a5224 - Quantum Networking (POF4-522)$$cPOF4-522$$fPOF IV$$x0
000916699 7001_ $$0P:(DE-Juel1)171686$$aAnsari, Mohammad$$b1$$ufzj
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000916699 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)188287$$aForschungszentrum Jülich$$b0$$kFZJ
000916699 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)171686$$aForschungszentrum Jülich$$b1$$kFZJ
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000916699 9141_ $$y2022
000916699 920__ $$lyes
000916699 9201_ $$0I:(DE-Juel1)PGI-2-20110106$$kPGI-2$$lTheoretische Nanoelektronik$$x0
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