Selective and efficient quantum process tomography in arbitrary finite dimension
The characterization of quantum processes is a key tool in quantum information processing tasks for several reasons: on one hand, it allows one to acknowledge errors in the implementations of quantum algorithms; on the other, it allows one to characterize unknown processes occurring in nature. Bende...
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2018
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_24699926_v98_n6_p_Perito http://hdl.handle.net/20.500.12110/paper_24699926_v98_n6_p_Perito |
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paper:paper_24699926_v98_n6_p_Perito2023-06-08T16:36:10Z Selective and efficient quantum process tomography in arbitrary finite dimension Quantum optics Set theory Finite dimensions Mutually unbiased basis Quantum algorithms Quantum channel Quantum process Quantum process tomography Quantum-information processing Tensor products Quantum efficiency The characterization of quantum processes is a key tool in quantum information processing tasks for several reasons: on one hand, it allows one to acknowledge errors in the implementations of quantum algorithms; on the other, it allows one to characterize unknown processes occurring in nature. Bendersky, Pastawski, and Paz [A. Bendersky, F. Pastawski, and J. P. Paz, Phys. Rev. Lett. 100, 190403 (2008)PRLTAO0031-900710.1103/PhysRevLett.100.190403; Phys. Rev. A 80, 032116 (2009)PLRAAN1050-294710.1103/PhysRevA.80.032116] introduced a method to selectively and efficiently measure any given coefficient from the matrix description of a quantum channel. However, this method heavily relies on the construction of maximal sets of mutually unbiased bases (MUBs), which are known to exist only when the dimension of the Hilbert space is the power of a prime number. In this article, we lift the requirement on the dimension by presenting two variations of the method that work on arbitrary finite dimensions: one uses tensor products of maximal sets of MUBs, and the other uses a dimensional cutoff of a higher prime power dimension. © 2018 American Physical Society. 2018 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_24699926_v98_n6_p_Perito http://hdl.handle.net/20.500.12110/paper_24699926_v98_n6_p_Perito |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Quantum optics Set theory Finite dimensions Mutually unbiased basis Quantum algorithms Quantum channel Quantum process Quantum process tomography Quantum-information processing Tensor products Quantum efficiency |
| spellingShingle |
Quantum optics Set theory Finite dimensions Mutually unbiased basis Quantum algorithms Quantum channel Quantum process Quantum process tomography Quantum-information processing Tensor products Quantum efficiency Selective and efficient quantum process tomography in arbitrary finite dimension |
| topic_facet |
Quantum optics Set theory Finite dimensions Mutually unbiased basis Quantum algorithms Quantum channel Quantum process Quantum process tomography Quantum-information processing Tensor products Quantum efficiency |
| description |
The characterization of quantum processes is a key tool in quantum information processing tasks for several reasons: on one hand, it allows one to acknowledge errors in the implementations of quantum algorithms; on the other, it allows one to characterize unknown processes occurring in nature. Bendersky, Pastawski, and Paz [A. Bendersky, F. Pastawski, and J. P. Paz, Phys. Rev. Lett. 100, 190403 (2008)PRLTAO0031-900710.1103/PhysRevLett.100.190403; Phys. Rev. A 80, 032116 (2009)PLRAAN1050-294710.1103/PhysRevA.80.032116] introduced a method to selectively and efficiently measure any given coefficient from the matrix description of a quantum channel. However, this method heavily relies on the construction of maximal sets of mutually unbiased bases (MUBs), which are known to exist only when the dimension of the Hilbert space is the power of a prime number. In this article, we lift the requirement on the dimension by presenting two variations of the method that work on arbitrary finite dimensions: one uses tensor products of maximal sets of MUBs, and the other uses a dimensional cutoff of a higher prime power dimension. © 2018 American Physical Society. |
| title |
Selective and efficient quantum process tomography in arbitrary finite dimension |
| title_short |
Selective and efficient quantum process tomography in arbitrary finite dimension |
| title_full |
Selective and efficient quantum process tomography in arbitrary finite dimension |
| title_fullStr |
Selective and efficient quantum process tomography in arbitrary finite dimension |
| title_full_unstemmed |
Selective and efficient quantum process tomography in arbitrary finite dimension |
| title_sort |
selective and efficient quantum process tomography in arbitrary finite dimension |
| publishDate |
2018 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_24699926_v98_n6_p_Perito http://hdl.handle.net/20.500.12110/paper_24699926_v98_n6_p_Perito |
| _version_ |
1768542620268625920 |