Benchmarking Gaussian and non-Gaussian input states with a hybrid sampling platform
Michael Stefszky, Kai-Hong Luo, Jan-Lucas Eickmann, Simone Atzeni, Florian L\"utkewitte, Cheeranjiv Pandey, Fabian Schlue, Jonas Lammers, Mikhail Roiz, Timon Schapeler, Laura Ares, Milad Yahyapour, Alexander Kastner, Joschua Martinek, Michael Mittermair

TL;DR
This paper introduces the Paderborn Quantum Sampler (PaQS), a hybrid platform for benchmarking Gaussian and non-Gaussian input states in quantum sampling, demonstrating performance advantages of non-Gaussian states.
Contribution
The authors develop a versatile platform enabling direct comparison of Gaussian and non-Gaussian states in quantum sampling experiments with certification of quantum advantage.
Findings
Non-Gaussian states show clear performance gains in sampling tasks.
The platform performs experiments with eight input states in a 12-mode interferometer.
Semi-device-independent certification confirms quantum advantage.
Abstract
The original boson sampling paradigm-consisting of multiple single-photon input states, a large interferometer, and multi-channel click detection-was originally proposed as a photonic route to quantum computational advantage. Its non-Gaussian resources, essential for outperforming any classical system, are provided by single-photon inputs and click detection. Yet the drive toward larger experiments has led to the replacement of experimentally demanding single-photon sources with Gaussian states, thereby diminishing the available non-Gaussianity-a critical quantum resource. As the community broadens its focus from the initial sampling task to possible real-world applications, it becomes crucial to quantify the performance cost associated with reducing non-Gaussian resources and to benchmark sampling platforms that employ different input states. To address this need, we introduce the…
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