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Volumn 80, Issue 2, 2009, Pages

Two-qubit Hamiltonian tomography by Bayesian analysis of noisy data

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN ANALYSIS; BAYESIAN METHODS; CONTROLLABLE SYSTEMS; FULL CONTROL; HAMILTONIAN DYNAMICS; MEASUREMENT DATA; MULTI-STEP; NOISY DATA; PHASE FACTOR; SIGNAL PARAMETERS; SIMULATED EXPERIMENTS; TWO-QUBIT; TWO-QUBIT SYSTEM; UNOBSERVABLE;

EID: 69449088691     PISSN: 10502947     EISSN: 10941622     Source Type: Journal    
DOI: 10.1103/PhysRevA.80.022333     Document Type: Article
Times cited : (56)

References (32)
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    • Image courtesy of Hitachi Cambridge Laboratories, Hitachi Europe Ltd.
    • Image courtesy of Hitachi Cambridge Laboratories, Hitachi Europe Ltd.
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    • Formally, the method presented will work for any four-dimensional Hamiltonian system.
    • Formally, the method presented will work for any four-dimensional Hamiltonian system.
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    • We consider only noise due to finite sampling for each time tn, which is Poissonian. In the large Ne limit, and for pkl 0,1, this tends to Gaussian noise.
    • We consider only noise due to finite sampling for each time tn, which is Poissonian. In the large Ne limit, and for pkl 0,1, this tends to Gaussian noise.
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    • note
    • In this case, the small number of parameters to be estimated means that a simple least-squares fit performs adequately. A Bayesian analysis is made more difficult by the complicated dependence of the basis functions on the undetermined parameters, although this approach may lead to better estimates than the ones presented here, but at a cost of greater computational complexity. This is a topic for further research.
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    • note
    • Composite pulses or robust optimal control can be used to relax the need for extremely accurate Hamiltonian characterization.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.