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Multivariate discrimination in quantum target detection

Svihra, Peter·Zhang, Yingwen·Hockett, Paul·Ferrante, Steven·Sussman, Benjamin·England, Duncan·Nomerotski, Andrei
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Abstract

In this work, we describe a simple multivariate technique of likelihood ratios for improved discrimination of signal and background in multi-dimensional quantum target detection. Furthermore, the technique combines two independent variables, time difference and summed energy, of a photon pair from the spontaneous parametric down-conversion source into an optimal discriminant. The discriminant performance was studied in experimental data and in Monte-Carlo modelling with clear improvement shown compared to previous techniques. As novel detectors become available, we expect this type of multivariate analysis to become increasingly important in multi-dimensional quantum optics.

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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDSMonte Carlo methodsOptical deviceslight detection and rangingmeasuring instrumentsmultidimensional spatial data modelingparametric down conversionphotonic entanglementquantum opticsstatistical analysistelescopes

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Svihra, Peter, Zhang, Yingwen, Hockett, Paul, Ferrante, Steven, Sussman, Benjamin, England, Duncan, Nomerotski, Andrei. 2020-07-27. Multivariate discrimination in quantum target detection. https://doi.org/10.1063/5.0012429

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