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arXiv · 2005.00612

Multivariate Discrimination in Quantum Target Detection

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

We describe a simple multivariate technique of likelihood ratios for improved discrimination of signal and background in multi-dimensional quantum target detection. 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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Peter Svihra, Yingwen Zhang, Paul Hockett, Steven Ferrante, Benjamin Sussman, Duncan England, Andrei Nomerotski. 2020-05-01. Multivariate Discrimination in Quantum Target Detection. https://doi.org/10.1063/5.0012429

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