Qutrit state tomography via optimal unambiguous state discrimination and mutually unbiased measurements.
In: Results in Physics, Jg. 34 (2022-03-01), S. N.PAG
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Zugriff:
We propose an efficient scheme for qutrit state tomography based on optimal unambiguous discrimination of three nonorthogonal pure qutrit states. In our scheme, we first introduce an ancillary qubit initially prepared in a known state and apply a joint unitary transformation on the whole system composed of a qutrit state and an ancillary qubit state. Afterwards, we make a local von Neumann measurement (VNM) on the ancillary qubit. If it is projected onto the state | 0 〉 , we finally perform mutually unbiased measurements (MUMs) on the collapsed qutrit state arbitrarily chosen from a complete set of four mutually unbiased bases (MUBs). With only six properly-chosen projectors, the real and imaginary parts of non-diagonal elements can be entirely obtained. Together with the diagonal elements obtained directly from one VNM in the computational bases, the density matrix of an arbitrary unknown qutrit state can be fully determined. Compared with the previous work (R. Salazar and A. Delgado 2012), our scheme consumes much less resources. In comparison with MUBs-based tomography scheme (H. Yuan, et al., 2016), our scheme requires more measurements and less projectors, but pays the price of a loss of certain fraction identically prepared states. Our proposal can be extended to the case of other d -dimensional quantum states if their d MUBs are exactly known. • An efficient scheme for qutrit state tomography based on optimal unambiguous state discrimination is proposed. • Three mutually unbiased measurements with six projectors are performed. • Our scheme consumes much less resources, compared to the previous works. [ABSTRACT FROM AUTHOR]
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Titel: |
Qutrit state tomography via optimal unambiguous state discrimination and mutually unbiased measurements.
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Autor/in / Beteiligte Person: | Yuan, Hao ; Shi, Xuan ; Han, Lian-Fang |
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Zeitschrift: | Results in Physics, Jg. 34 (2022-03-01), S. N.PAG |
Veröffentlichung: | 2022 |
Medientyp: | academicJournal |
ISSN: | 2211-3797 (print) |
DOI: | 10.1016/j.rinp.2022.105228 |
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