Quantum process identification: a method for characterizing non-markovian quantum dynamics
Established methods for characterizing quantum information processes do not capture non-Markovian (history-dependent) behaviors that occur in real systems. These methods model a quantum process as a fixed map on the state space of a predefined system of interest. Such a map averages over the system’...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2019-01-01
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| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/ab3598 |
| _version_ | 1797750087258996736 |
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| author | Ryan S Bennink Pavel Lougovski |
| author_facet | Ryan S Bennink Pavel Lougovski |
| author_sort | Ryan S Bennink |
| collection | DOAJ |
| description | Established methods for characterizing quantum information processes do not capture non-Markovian (history-dependent) behaviors that occur in real systems. These methods model a quantum process as a fixed map on the state space of a predefined system of interest. Such a map averages over the system’s environment, which may retain some effect of its past interactions with the system and thus have a history-dependent influence on the system. Although the theory of non-Markovian quantum dynamics is currently an active area of research, a systematic characterization method based on a general representation of non-Markovian dynamics has been lacking. In this article we present a systematic method for experimentally characterizing the dynamics of open quantum systems. Our method, which we call quantum process identification (QPI), is based on a general theoretical framework which relates the (non-Markovian) evolution of a system over an extended period of time to a time-local (Markovian) process involving the system and an effective environment. In practical terms, QPI uses time-resolved tomographic measurements of a quantum system to construct a dynamical model with as many dynamical variables as are necessary to reproduce the evolution of the system. Through numerical simulations, we demonstrate that QPI can be used to characterize qubit operations with non-Markovian errors arising from realistic dynamics including control drift, coherent leakage, and coherent interaction with material impurities. |
| first_indexed | 2024-03-12T16:27:38Z |
| format | Article |
| id | doaj.art-90fa883da31c4330ad03d3c3cebeec83 |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:27:38Z |
| publishDate | 2019-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-90fa883da31c4330ad03d3c3cebeec832023-08-08T15:38:37ZengIOP PublishingNew Journal of Physics1367-26302019-01-0121808301310.1088/1367-2630/ab3598Quantum process identification: a method for characterizing non-markovian quantum dynamicsRyan S Bennink0Pavel Lougovski1Quantum Information Science Group, Oak Ridge National Laboratory, United States of AmericaQuantum Information Science Group, Oak Ridge National Laboratory, United States of AmericaEstablished methods for characterizing quantum information processes do not capture non-Markovian (history-dependent) behaviors that occur in real systems. These methods model a quantum process as a fixed map on the state space of a predefined system of interest. Such a map averages over the system’s environment, which may retain some effect of its past interactions with the system and thus have a history-dependent influence on the system. Although the theory of non-Markovian quantum dynamics is currently an active area of research, a systematic characterization method based on a general representation of non-Markovian dynamics has been lacking. In this article we present a systematic method for experimentally characterizing the dynamics of open quantum systems. Our method, which we call quantum process identification (QPI), is based on a general theoretical framework which relates the (non-Markovian) evolution of a system over an extended period of time to a time-local (Markovian) process involving the system and an effective environment. In practical terms, QPI uses time-resolved tomographic measurements of a quantum system to construct a dynamical model with as many dynamical variables as are necessary to reproduce the evolution of the system. Through numerical simulations, we demonstrate that QPI can be used to characterize qubit operations with non-Markovian errors arising from realistic dynamics including control drift, coherent leakage, and coherent interaction with material impurities.https://doi.org/10.1088/1367-2630/ab3598system identificationquantum process tomographydevice characterizationnon-Markovian dynamicsopen quantum dynamicsHamiltonian learning |
| spellingShingle | Ryan S Bennink Pavel Lougovski Quantum process identification: a method for characterizing non-markovian quantum dynamics New Journal of Physics system identification quantum process tomography device characterization non-Markovian dynamics open quantum dynamics Hamiltonian learning |
| title | Quantum process identification: a method for characterizing non-markovian quantum dynamics |
| title_full | Quantum process identification: a method for characterizing non-markovian quantum dynamics |
| title_fullStr | Quantum process identification: a method for characterizing non-markovian quantum dynamics |
| title_full_unstemmed | Quantum process identification: a method for characterizing non-markovian quantum dynamics |
| title_short | Quantum process identification: a method for characterizing non-markovian quantum dynamics |
| title_sort | quantum process identification a method for characterizing non markovian quantum dynamics |
| topic | system identification quantum process tomography device characterization non-Markovian dynamics open quantum dynamics Hamiltonian learning |
| url | https://doi.org/10.1088/1367-2630/ab3598 |
| work_keys_str_mv | AT ryansbennink quantumprocessidentificationamethodforcharacterizingnonmarkovianquantumdynamics AT pavellougovski quantumprocessidentificationamethodforcharacterizingnonmarkovianquantumdynamics |