G
Georg Sulyok
Researcher at Vienna University of Technology
Publications - 22
Citations - 538
Georg Sulyok is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: Uncertainty principle & Ion. The author has an hindex of 8, co-authored 21 publications receiving 482 citations.
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Experimental demonstration of a universally valid error-disturbance uncertainty relation in spin measurements
TL;DR: The uncertainty principle in its original form ignores, however, the unavoidable effect of recoil in the measuring device as discussed by the authors, and the original formulation is broken by an experimental test now validates an alternative relation.
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Violation of Heisenberg's error-disturbance uncertainty relation in neutron-spin measurements
TL;DR: In this paper, the authors show that the relationship between the error of a quantum measurement and the induced disturbance on the measured object is not a reciprocal relation between error and disturbance in general.
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Experimental Test of Entropic Noise-Disturbance Uncertainty Relations for Spin-1/2 Measurements.
Georg Sulyok,Stephan Sponar,Bülent Demirel,Francesco Buscemi,Michael J. W. Hall,Masanao Ozawa,Yuji Hasegawa +6 more
TL;DR: This work derives a tight noise-disturbance uncertainty relation for complementary qubit observables and carries out an experimental test, which saturates the tight Noise-Disturbance Uncertainty relation for qubits when an optimal correction procedure is applied.
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Experimental Test of Residual Error-Disturbance Uncertainty Relations for Mixed Spin- ½ States
TL;DR: A neutron-optical experiment is carried out to investigate whether error and disturbance of quantum measurements disappear or persist in mixing up the measured ensemble, and falsifying the tightness of Branciard's bound for mixed spin states.
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Extraction of a photovoltaic cell's double-diode model parameters from data sheet values
Georg Sulyok,Johann Summhammer +1 more
TL;DR: In this article, the authors derived the parameters of the single cell's circuit model by fitting measured data points to the theoretical IV-curve, which can serve as starting point for further research and cell optimization.