Statistical Quadrature Evolution by Inference for Continuous-Variable Quantum Key Distribution

TL;DR

This paper introduces a statistical quadrature evolution method for multicarrier continuous-variable quantum key distribution, enhancing the estimation accuracy of quantum states using statistical inference techniques.

Contribution

It develops a Gaussian quadrature inference framework for CVQKD, providing a minimal error, stable estimation method that is easy to implement and adaptable to various protocols.

Findings

Provides a stable, minimal-error estimation of quantum state quadratures.

Offers a computationally efficient method suitable for experimental CVQKD.

Enhances information extraction from measurement data in CVQKD.

Abstract

We define the statistical quadrature evolution (QE) method for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD protocol uses Gaussian subcarrier quantum continuous variables (CVs) for information transmission. The QE scheme utilizes the theory of mathematical statistics and statistical information processing. The QE model is based on the Gaussian quadrature inference (GQI) framework to provide a minimal error estimate of the CV state quadratures. The QE block evaluates a unique and stable estimation of the non-observable continuous input from the measurement results and through the statistical inference method yielded from the GQI framework. The QE method minimizes the overall expected error by an estimator function and provides a viable, easily implementable, and computationally efficient way to maximize the extractable information from the observed data. The QE framework can be established in an arbitrary CVQKD protocol and measurement setting and is implementable by standard low-complexity functions, which is particularly convenient for experimental CVQKD.