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Conditional quantum plasmonic sensing

delete2022-06-15
delete8
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OA
AI
F
Fatemeh Mostafavi
Z
Zeinab Jafari
M
M. L. Lollie
C
Chenglong You *
I
Israel De Leon
O
Omar S. Magaña‐Loaiza
DOI:10.1515/nanoph-2022-0160delete
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摘要

摘要

En 中文
The possibility of using weak optical signals to perform sensing of delicate samples constitutes one of the main goals of quantum photonic sensing. Furthermore, the nanoscale confinement of electromagnetic near fields in photonic platforms through surface plasmon polaritons has motivated the development of highly sensitive quantum plasmonic sensors. Despite the enormous potential of plasmonic platforms for sensing, this class of sensors is ultimately limited by the quantum statistical fluctuations of surface plasmons. Indeed, the fluctuations of the electromagnetic field severely limit the performance of quantum plasmonic sensing platforms in which delicate samples are characterized using weak near-field signals. Furthermore, the inherent losses associated with plasmonic fields levy additional constraints that challenge the realization of sensitivities beyond the shot-noise limit. Here, we introduce a protocol for quantum plasmonic sensing based on the conditional detection of plasmons. We demonstrate that the conditional detection of plasmonic fields, via plasmon subtraction, provides a new degree of freedom to control quantum fluctuations of plasmonic fields. This mechanism enables improvement of the signal-to-noise ratio of photonic sensors relying on plasmonic signals that are comparable to their associated field fluctuations. Consequently, the possibility of using weak plasmonic signals to sense delicate samples, while preserving the sample properties, has important implications for molecule sensing, and chemical detection.
Keyword:
particle subtraction
quantum measurement
quantum plasmonic sensing

期刊

Nanophotonics 封面图
Nanophotonics
IF:
6.6
论文数:
3.0K
被引数:
1.6W

机构

L
louisiana state university system
学者数:
2.3W
论文数: 2.0W
被引数: 15
L
Louisiana State University
学者数:
9.8K
论文数: 8.0K
被引数: 1.6W
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