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Exact quantum Bayesian rule for qubit measurements in circuit QED

Overview of attention for article published in Scientific Reports, February 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Title
Exact quantum Bayesian rule for qubit measurements in circuit QED
Published in
Scientific Reports, February 2016
DOI 10.1038/srep20492
Pubmed ID
Authors

Wei Feng, Pengfei Liang, Lupei Qin, Xin-Qi Li

Abstract

Developing efficient framework for quantum measurements is of essential importance to quantum science and technology. In this work, for the important superconducting circuit-QED setup, we present a rigorous and analytic solution for the effective quantum trajectory equation (QTE) after polaron transformation and converted to the form of Stratonovich calculus. We find that the solution is a generalization of the elegant quantum Bayesian approach developed in arXiv:1111.4016 by Korotokov and currently applied to circuit-QED measurements. The new result improves both the diagonal and off-diagonal elements of the qubit density matrix, via amending the distribution probabilities of the output currents and several important phase factors. Compared to numerical integration of the QTE, the resultant quantum Bayesian rule promises higher efficiency to update the measured state, and allows more efficient and analytical studies for some interesting problems such as quantum weak values, past quantum state, and quantum state smoothing. The method of this work opens also a new way to obtain quantum Bayesian formulas for other systems and in more complicated cases.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Researcher 3 20%
Student > Master 3 20%
Professor 2 13%
Other 1 7%
Other 0 0%
Unknown 1 7%
Readers by discipline Count As %
Physics and Astronomy 14 93%
Unknown 1 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 January 2017.
All research outputs
#4,292,826
of 25,374,647 outputs
Outputs from Scientific Reports
#34,486
of 140,664 outputs
Outputs of similar age
#69,817
of 405,737 outputs
Outputs of similar age from Scientific Reports
#847
of 3,263 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 140,664 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.7. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 405,737 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 3,263 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.