Scientific Results

Witnessing entanglement without entanglement witness operators

Year: 2016

Authors: Pezzè L., Li Y., Li W., Smerzi A.

Autors Affiliation: Quantum Sci & Technol Arcetri, I-50125 Florence, Italy; CNR, Natl Inst Opt, I-50125 Florence, Italy; European Lab Nonlinear Spect, I-50125 Florence, Italy; Shanxi Univ, Inst Theoret Phys, Collaborat Innovat Ctr Extreme Opt, Taiyuan 030006, Peoples R China; Shanxi Univ, Dept Phys, Collaborat Innovat Ctr Extreme Opt, Taiyuan 030006, Peoples R China

Abstract: Quantum mechanics predicts the existence of correlations between composite systems that, although puzzling to our physical intuition, enable technologies not accessible in a classical world. Notwithstanding, there is still no efficient general method to theoretically quantify and experimentally detect entanglement of many qubits. Here we propose to detect entanglement by measuring the statistical response of a quantum system to an arbitrary nonlocal parametric evolution. We witness entanglement without relying on the tomographic reconstruction of the quantum state, or the realization of witness operators. The protocol requires two collective settings for any number of parties and is robust against noise and decoherence occurring after the implementation of the parametric transformation. To illustrate its user friendliness we demonstrate multipartite entanglement in different experiments with ions and photons by analyzing published data on fidelity visibilities and variances of collective observables.

Journal/Review: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Volume: 113 (41)      Pages from: 11459  to: 11464

More Information: This work was supported by the National Natural Science Foundation of China Grant 11374197, Program for Changjiang Scholars and Innovative Research Team Grant IRT13076, and The Hundred Talent Program of Shanxi Province (2012).
KeyWords: quantum entanglement; entanglement detection; quantum technology; Fisher information; trapped ions
DOI: 10.1073/pnas.1603346113

Citations: 20
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2019-10-13
References taken from IsiWeb of Knowledge: (subscribers only)
Connecting to view paper tab on IsiWeb: Click here
Connecting to view citations from IsiWeb: Click here

English