Quantum phase estimation using path-symmetric entangled states

Su Yong Lee, Chang Woo Lee, Jaehak Lee, Hyunchul Nha

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

We study the sensitivity of phase estimation using a generic class of path-symmetric entangled states |φ>|0>> + |0>|φ>, where an arbitrary state |φ> occupies one of two modes in quantum superposition. With this generalization, we identify the fundamental limit of phase estimation under energy constraint that is characterized by the photon statistics of the component state |φ>. We show that quantum Cramer-Rao bound (QCRB) can be indefinitely lowered with super-Poissonianity of the state |φ>. For possible measurement schemes, we demonstrate that a full photon-counting employing the path-symmetric entangled states achieves the QCRB over the entire range [0, 2π] of unknown phase shift Φ whereas a parity measurement does so in a certain confined range of Φ. By introducing a component state of the form |φ> = √q|1> + √1-q|N>, we particularly show that an arbitrarily small QCRB can be achieved even with a finite energy in an ideal situation. This component state also provides the most robust resource against photon loss among considered entangled states over the range of the average input energy Nav > 1. Finally we propose experimental schemes to generate these path-symmetric entangled states for phase estimation.

Original languageEnglish
Article number30306
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 26 Jul 2016

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Cramer-Rao bounds
photons
energy
resources
counting
parity
phase shift
statistics

ASJC Scopus subject areas

  • General

Cite this

Quantum phase estimation using path-symmetric entangled states. / Lee, Su Yong; Lee, Chang Woo; Lee, Jaehak; Nha, Hyunchul.

In: Scientific Reports, Vol. 6, 30306, 26.07.2016.

Research output: Contribution to journalArticle

Lee, Su Yong ; Lee, Chang Woo ; Lee, Jaehak ; Nha, Hyunchul. / Quantum phase estimation using path-symmetric entangled states. In: Scientific Reports. 2016 ; Vol. 6.
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