English

Revealing nonclassicality beyond Gaussian states via a single marginal distribution

Quantum Physics 2017-02-07 v1

Abstract

A standard method to obtain information on a quantum state is to measure marginal distributions along many different axes in phase space, which forms a basis of quantum state tomography. We theoretically propose and experimentally demonstrate a general framework to manifest nonclassicality by observing a single marginal distribution only, which provides a novel insight into nonclassicality and a practical applicability to various quantum systems. Our approach maps the 1-dim marginal distribution into a factorized 2-dim distribution by multiplying the measured distribution or the vacuum-state distribution along an orthogonal axis. The resulting fictitious Wigner function becomes unphysical only for a nonclassical state, thus the negativity of the corresponding density operator provides an evidence of nonclassicality. Furthermore, the negativity measured this way yields a lower bound for entanglement potential---a measure of entanglement generated using a nonclassical state with a beam splitter setting that is a prototypical model to produce continuous-variable (CV) entangled states. Our approach detects both Gaussian and non-Gaussian nonclassical states in a reliable and efficient manner. Remarkably, it works regardless of measurement axis for all non-Gaussian states in finite-dimensional Fock space of any size, also extending to infinite-dimensional states of experimental relevance for CV quantum informatics. We experimentally illustrate the power of our criterion for motional states of a trapped ion confirming their nonclassicality in a measurement-axis independent manner. We also address an extension of our approach combined with phase-shift operations, which leads to a stronger test of nonclassicality, i.e. detection of genuine non-Gaussianity under a CV measurement.

Keywords

Cite

@article{arxiv.1702.01387,
  title  = {Revealing nonclassicality beyond Gaussian states via a single marginal distribution},
  author = {Jiyong Park and Yao Lu and Jaehak Lee and Yangchao Shen and Kuan Zhang and Shuaining Zhang and M. Suhail Zubairy and Kihwan Kim and Hyunchul Nha},
  journal= {arXiv preprint arXiv:1702.01387},
  year   = {2017}
}

Comments

6 pages, 4 figures with Supplemental Information