Unveiling the Non-Abelian Statistics of D(S_{3}) Anyons Using a Classical Photonic Simulator.

Simulators can realize novel phenomena by separating them from the complexities of a full physical implementation. Here, we put forward a scheme that can simulate the exotic statistics of D(S_{3}) non-Abelian anyons with minimal resources. The qudit lattice representation of this planar code supports local encoding of D(S_{3}) anyons. As a proof-of-principle demonstration, we employ a classical photonic simulator to encode a single qutrit and manipulate it to perform the fusion and braiding properties of non-Abelian D(S_{3}) anyons. The photonic technology allows us to perform the required nonunitary operations with much higher fidelity than what can be achieved with current quantum computers. Our approach can be directly generalized to larger systems or to different anyonic models, thus enabling advances in the exploration of quantum error correction and fundamental physics alike.

Referenceless characterization of complex media using physics-informed neural networks.

In this work, we present a method to characterize the transmission matrices of complex scattering media using a physics-informed, multi-plane neural network (MPNN) without the requirement of a known optical reference field. We use this method to accurately measure the transmission matrix of a commercial multi-mode fiber without the problems of output-phase ambiguity and dark spots, leading to up to 58% improvement in focusing efficiency compared with phase-stepping holography. We demonstrate how our method is significantly more noise-robust than phase-stepping holography and show how it can be generalized to characterize a cascade of transmission matrices, allowing one to control the propagation of light between independent scattering media. This work presents an essential tool for accurate light control through complex media, with applications ranging from classical optical networks, biomedical imaging, to quantum information processing.

Simultaneously Sorting Overlapping Quantum States of Light.

The efficient manipulation, sorting, and measurement of optical modes and single-photon states is fundamental to classical and quantum science. Here, we realize simultaneous and efficient sorting of nonorthogonal, overlapping states of light, encoded in the transverse spatial degree of freedom. We use a specifically designed multiplane light converter to sort states encoded in dimensions ranging from d=3 to d=7. Through the use of an auxiliary output mode, the multiplane light converter simultaneously performs the unitary operation required for unambiguous discrimination and the basis change for the outcomes to be spatially separated. Our results lay the groundwork for optimal image identification and classification via optical networks, with potential applications ranging from self-driving cars to quantum communication systems.