2016
DOI: 10.1103/physrevlett.117.213602
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Nonclassicality Criteria in Multiport Interferometry

Abstract: Interference lies at the heart of the behavior of classical and quantum light. It is thus crucial to understand the boundaries between which interference patterns can be explained by a classical electromagnetic description of light and which, on the other hand, can only be understood with a proper quantum mechanical approach. While the case of two-mode interference has received a lot of attention, the multimode case has not yet been fully explored. Here we study a general scenario of intensity interferometry: … Show more

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Cited by 26 publications
(29 citation statements)
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“…However, the HBT test uses only single measurement layout among many where the nonclassicality of single photon states can manifest itself. Probably, many other linear optical (LO) schemes with single photon detectors can manifest single photon nonclassicality differently to that HBT test [17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…However, the HBT test uses only single measurement layout among many where the nonclassicality of single photon states can manifest itself. Probably, many other linear optical (LO) schemes with single photon detectors can manifest single photon nonclassicality differently to that HBT test [17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…But how does partial distinguishability impact on statistical quantifiers [9,12,32,33] of the fine structure of many-particle interference, in cases where the complexity of the dynamics (measured by the number of many-particle amplitudes which are dynamically superimposed) prevents a deterministic description, as in principle given, e.g., by evaluation of the full counting statistics? And to which extent can also such statistical quantifiers then be employed as diagnostic tools?…”
Section: Introductionmentioning
confidence: 99%
“…For instance, a more profound extension of the method that considers three-point correlations was explored in [98]. Finally, the approach based on the C-dataset is closely related to those that use the g (2) and g (3) functions [99,100].…”
Section: Statistical Signatures and Random Matrix Theorymentioning
confidence: 99%