General simulation method for quantum-sensing systems

TL;DR

This paper introduces a comprehensive simulation method for quantum-sensing systems that incorporates experimental imperfections, enabling better alignment between theoretical predictions and real-world experimental results, and aiding in system optimization.

Contribution

The paper presents a novel simulation approach that models imperfections in quantum sensing, facilitating improved design, analysis, and post-processing of quantum imaging experiments.

Findings

Simulation accurately reproduces experimental data characteristics.

Method improves image quality through post-processing.

Provides a versatile tool for quantum sensor design and optimization.

Abstract

Quantum sensing encompasses highly promising techniques with diverse applications including noise-reduced imaging, super-resolution microscopy as well as imaging and spectroscopy in challenging spectral ranges. These detection schemes use biphoton correlations to surpass classical limits or transfer information to different spectral ranges. Theoretical analysis is mostly confined to idealized conditions. Therefore, theoretical predictions and experimental results for the performance of quantum-sensing systems often diverge. Here we present a general simulation method that includes experimental imperfections to bridge the gap between theory and experiment. We develop a theoretical approach and demonstrate the capabilities with the simulation of aligned and misaligned quantum-imaging experiments. The results recreate the characteristics of experimental data. We further use the simulation results to improve the obtained images in post-processing. As simulation method for general quantum-sensing systems, this work provides a first step towards powerful simulation tools for interactively exploring the design space and optimizing the experiment's characteristics.