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Non-Hermitian systems offer unique capabilities for manipulating light. Here, authors demonstrate non-reciprocal frequency conversion through non-Hermitian and nonlinear coupling, enabling high-efficiency photonic devices and exploration of non-Hermitian topology.

Characterising an optical quantum state confined in a cavity is not an easy task, as standard tomographic techniques works by interfering propagating fields and therefore encounters the problems relative to outcoupling the state. Here, the authors fill this gap for states generated within a nonlinear cavity featuring multiple steady states.

Scintillators are used for converting X-ray energy into visible light in imaging technologies. Here, the authors present a scalable fabrication approach for large-area nanostructured scintillators, and achieve six-fold enhancement in light yield compared to unpatterned scintillators.

A study demonstrates full energy–momentum matching, and enhanced interaction, between free electrons and photons through a continuum of flatband resonances, realized in a silicon-on-insulator photonic crystal slab.

Extracting light from silicon is a longstanding challenge. Here, the authors report an experimental demonstration of free-electron-driven light emission from silicon nanogratings and investigates the feasibility of a compact, all-silicon tunable light source integrated with a silicon field emitter array.

Intense squeezed light with focusable intensities of 0.1 TW cm⁻² is created by propagating a classical, intense and noisy input beam through an optical fibre. The noise 4 dB below the shot-noise level is achieved by selecting a set of wavelengths whose intensity fluctuations are maximally anticorrelated.

A large-scale photonic accelerator comprising more than 16,000 components integrated on a single chip to process MAC operations is described, demonstrating ultralow latency and reduced computing time compared with a commercially available GPU.

Probabilistic machine learning is an emerging computing paradigm which utilizes controllable random sources to encode uncertainty and enable statistical modelling. Here, authors harness quantum vacuum noise as a controllable random source to perform probabilistic inference and image generation.

Non-Abelian lattice gauge fields in photonic synthetic frequency dimensions can be used to study lattice physics in a scalable and programmable way.

Application-specific computational hardware helps to solve the limitations of conventional electronics in solving difficult calculation problems. Here the authors present a general heuristic algorithm to solve NP-Hard Ising problems in a photonics implementation.

Calculating the amount of radiation that can ultimately be extracted from free electrons near an arbitrary material structure is a challenge. Now, an upper limit to the spontaneous photon emission of electrons is demonstrated, regardless of geometry.

Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. We propose an experimentally viable photonic approach to solve arbitrary probabilistic computing problems, used e.g. for solving difficult combinatorial optimization problems.

The PCLA analyzes partially coherent light by optimizing output power through a series of self-configuring Mach-Zehnder interferometers, effectively decomposing the input light field into its incoherent components.