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The coherent transmission technology using digital signal processing and advanced modulation formats, is bringing networks closer to the theoretical capacity limit of optical fibres, the Shannon limit. The in-phase/quadrature electro-optic modulator that encodes information on both the amplitude and the phase of light, is one of the underpinning devices for the coherent transmission technology. Ideally, such modulator should feature a low loss, low drive voltage, large bandwidth, low chirp and compact footprint. However, these requirements have been only met on separate occasions. Here, we demonstrate integrated thin-film lithium niobate in-phase/quadrature modulators that fulfil these requirements simultaneously. The presented devices exhibit greatly improved overall performance (half-wave voltage, bandwidth and optical loss) over traditional lithium niobate counterparts, and support modulation data rate up to 320 Gbit s −1 . Our devices pave new routes for future high-speed, energy-efficient, and cost-effective communication networks. In-phase/quadrature (IQ) electro-optic modulators are underpinning devices for coherent transmission technology. Here the authors present IQ modulators in the lithium-niobate-on-insulator platform, which provide improved overall performance and advanced modulation formats for future coherent transmission systems.

Programmable photonic integrated circuits (PICs) are dense assemblies of tunable elements that provide flexible reconfigurability to enable different functions to be selected; however, due to manufacturing variations and thermal gradients that affect the optical phases of the elements, it is difficult to guarantee a stable correspondence between the electrical commands to the chip, and the function that it provides. Here we demonstrate a self-calibrating programmable PIC with full control over its complex impulse response, in the presence of thermal cross-talk between phase-tuning elements. Self-calibration is achieved by: (1) incorporating an optical reference path into the PIC; (2) using the Kramers–Kronig relationship to recover the phase response from amplitude measurements; and (3) applying a fast-converging self-calibration algorithm. We demonstrate dial-up signal processing functions with complex impulse responses using only 25 training iterations. This approach offers stable and accurate control of large-scale PICs, for demanding applications such as communications network reconfiguration, neuromorphic hardware accelerators and quantum computers.Researchers demonstrate a self-calibrating programmable photonic integrated circuit. The findings may be useful for the accurate control of large-scale photonic integrated circuits in applications such as light-based machine learning.

Planar digital image sensors facilitate broad applications in a wide range of areas 1 – 5 , and the number of pixels has scaled up rapidly in recent years 2 , 6 . However, the practical performance of imaging systems is fundamentally limited by spatially nonuniform optical aberrations originating from imperfect lenses or environmental disturbances 7 , 8 . Here we propose an integrated scanning light-field imaging sensor, termed a meta-imaging sensor, to achieve high-speed aberration-corrected three-dimensional photography for universal applications without additional hardware modifications. Instead of directly detecting a two-dimensional intensity projection, the meta-imaging sensor captures extra-fine four-dimensional light-field distributions through a vibrating coded microlens array, enabling flexible and precise synthesis of complex-field-modulated images in post-processing. Using the sensor, we achieve high-performance photography up to a gigapixel with a single spherical lens without a data prior, leading to orders-of-magnitude reductions in system capacity and costs for optical imaging. Even in the presence of dynamic atmosphere turbulence, the meta-imaging sensor enables multisite aberration correction across 1,000 arcseconds on an 80-centimetre ground-based telescope without reducing the acquisition speed, paving the way for high-resolution synoptic sky surveys. Moreover, high-density accurate depth maps can be retrieved simultaneously, facilitating diverse applications from autonomous driving to industrial inspections. A meta-imaging sensor detects an extra-fine 4D light field distribution using a vibrating microlens array, enabling high-resolution 3D photography up to a gigapixel with fast aberration correction, demonstrated on a telescope aimed at the Moon.

Radio-frequency interference is a growing concern as wireless technology advances, with potentially life-threatening consequences like interference between radar altimeters and 5 G cellular networks. Mobile transceivers mix signals with varying ratios over time, posing challenges for conventional digital signal processing (DSP) due to its high latency. These challenges will worsen as future wireless technologies adopt higher carrier frequencies and data rates. However, conventional DSPs, already on the brink of their clock frequency limit, are expected to offer only marginal speed advancements. This paper introduces a photonic processor to address dynamic interference through blind source separation (BSS). Our system-on-chip processor employs a fully integrated photonic signal pathway in the analogue domain, enabling rapid demixing of received mixtures and recovering the signal-of-interest in under 15 picoseconds. This reduction in latency surpasses electronic counterparts by more than three orders of magnitude. To complement the photonic processor, electronic peripherals based on field-programmable gate array (FPGA) assess the effectiveness of demixing and continuously update demixing weights at a rate of up to 305 Hz. This compact setup features precise dithering weight control, impedance-controlled circuit board and optical fibre packaging, suitable for handheld and mobile scenarios. We experimentally demonstrate the processor’s ability to suppress transmission errors and maintain signal-to-noise ratios in two scenarios, radar altimeters and mobile communications. This work pioneers the real-time adaptability of integrated silicon photonics, enabling online learning and weight adjustments, and showcasing practical operational applications for photonic processing.A real-time photonic chip with fully integrated signal processing path and co-packaged electronics can effectively address dynamic RF interference with picosecond latency, benefiting applications like telecommunications and transportation.

Single-photon detectors are ubiquitous in quantum information science and quantum sensing. They are key enabling technologies for numerous scientific discoveries and fundamental tests of quantum optics. Photon-number-revolving detectors are the ultimate measurement tool of light; however, few detectors so far can provide high-fidelity photon number resolution at few-photon levels. Here we demonstrate an on-chip detector that can resolve up to 100 photons by spatiotemporally multiplexing an array of superconducting nanowires along a single optical waveguide. The unparalleled photon number resolution paired with the high-speed response exclusively allows us to unveil the quantum photon statistics of a true thermal light source at an unprecedented level, which is realized by direct measurement of the higher-order correlation function g(N) (with values of N up to 15), observation of photon-subtraction-induced photon number enhancement and quantum-limited state discrimination against a coherent light source. Our detector provides a viable route towards various important applications, including photonic quantum computation and quantum metrology.Up to 100 photons are resolved by a waveguide-integrated and hybrid spatiotemporal-multiplexed superconducting nanowire single-photon detector array. Using this detector array, photon statistical behaviour for a true thermal and a coherent light source is verified.

Future wireless communication networks will need to handle data rates of tens or even hundreds of Gbit s−1 per link, requiring carrier frequencies in the unallocated THz spectrum1,2. In this context, seamless integration of THz links into existing fibre-optic infrastructures3 is of great importance to complement the inherent portability and flexibility advantages of wireless networks and the reliable and virtually unlimited capacity of optical transmission systems. On the technological level, this requires novel device and signal processing concepts for direct conversion of data streams between the THz and optical domains. Here, we demonstrate a THz link that is seamlessly integrated into a fibre-optic network using direct THz-to-optical (T/O) conversion at the wireless receiver. We exploit an ultra-broadband silicon-plasmonic modulator having a 3 dB bandwidth in excess of 0.36 THz for T/O conversion of a 50 Gbit s−1 data stream that is transmitted on a 0.2885 THz carrier over a 16-m-long wireless link. Optical-to-THz (O/T) conversion at the wireless transmitter relies on photomixing in a uni-travelling-carrier photodiode.

Coherent optical communications provides the largest data transmission capacity with the highest spectral efficiency and therefore has a remarkable potential to satisfy today’s ever-growing bandwidth demands. It relies on so-called in-phase/quadrature (IQ) electro-optic modulators that encode information on both the amplitude and the phase of light. Ideally, such IQ modulators should offer energy-efficient operation and a most compact footprint, which would allow high-density integration and high spatial parallelism. Here, we present compact IQ modulators with an active section occupying a footprint of 4 × 25 µm × 3 µm, fabricated on the silicon platform and operated with sub-1-V driving electronics. The devices exhibit low electrical energy consumptions of only 0.07 fJ bit −1 at 50 Gbit s −1 , 0.3 fJ bit −1 at 200 Gbit s −1 , and 2 fJ bit −1 at 400 Gbit s −1 . Such IQ modulators may pave the way for application of IQ modulators in long-haul and short-haul communications alike. Increasing bandwidth demands in optical communications requires components to be compact with energy-efficient operation. Here, the authors demonstrate plasmonic IQ modulators on a silicon photonics platform with phase shifters, operating with sub-1V electronics at 100 GBaud and low electrical energy consumption.

Adaptive optics (AO) is critical in astronomy, optical communications and remote sensing to deal with the rapid blurring caused by the Earth’s turbulent atmosphere. But current AO systems are limited by their wavefront sensors, which need to be in an optical plane non-common to the science image and are insensitive to certain wavefront-error modes. Here we present a wavefront sensor based on a photonic lantern fibre-mode-converter and deep learning, which can be placed at the same focal plane as the science image, and is optimal for single-mode fibre injection. By measuring the intensities of an array of single-mode outputs, both phase and amplitude information on the incident wavefront can be reconstructed. We demonstrate the concept with simulations and an experimental realisation wherein Zernike wavefront errors are recovered from focal-plane measurements to a precision of 5.1 × 10 −3   π radians root-mean-squared-error. Adaptive optics wavefront sensors need to be in a pupil plane and are insensitive to certain wavefront-error modes. The authors present a wavefront sensor based on a photonic lantern fibre-mode-converter and deep learning, which can be placed at the same focal plane accessing nondegenerate wavefront information and reconstructing the wavefront.

The symmetry of crystalline silicon inhibits a second-order optical nonlinear susceptibility, χ (2) , in complementary metal–oxide–semiconductor-compatible silicon photonic platforms. However, χ (2) is required for important processes such as phase-only modulation, second-harmonic generation (SHG) and sum/difference frequency generation. Here, we break the crystalline symmetry by applying direct-current fields across p–i–n junctions in silicon ridge waveguides and induce a χ (2) proportional to the large χ (3) of silicon. The obtained χ (2) is first used to perturb the permittivity (the direct-current Kerr effect) and achieve phase-only modulation. Second, the spatial distribution of χ (2) is altered by periodically patterning p–i–n junctions to quasi-phase-match pump and second-harmonic modes and realize SHG. We measure a maximum SHG efficiency of P 2 ω / P ω 2  = 13 ± 0.5% W −1 at λ ω  = 2.29 µm and with field-induced χ (2)  = 41 ± 1.5 pm V –1 . We expect such field-induced χ (2) in silicon to lead to a new class of complex integrated devices such as carrier-envelope offset frequency stabilizers, terahertz generators, optical parametric oscillators and chirp-free modulators. The application of d.c. fields across p–i–n junctions in silicon ridge waveguides leads to crystal symmetry breaking. This induces a second-order optical nonlinear susceptibility that enables phase-only modulation and second-harmonic generation with an efficiency of ∼13% W –1 at 2.29 µm.

In optical communication systems, fibre nonlinearity is the major obstacle in increasing the transmission capacity. Typically, digital signal processing techniques and hardware are used to deal with optical communication signals, but increasing speed and computational complexity create challenges for such approaches. Highly parallel, ultrafast neural networks using photonic devices have the potential to ease the requirements placed on digital signal processing circuits by processing the optical signals in the analogue domain. Here we report a silicon photonic–electronic neural network for solving fibre nonlinearity compensation in submarine optical-fibre transmission systems. Our approach uses a photonic neural network based on wavelength-division multiplexing built on a silicon photonic platform compatible with complementary metal–oxide–semiconductor technology. We show that the platform can be used to compensate for optical fibre nonlinearities and improve the quality factor of the signal in a 10,080 km submarine fibre communication system. The Q -factor improvement is comparable to that of a software-based neural network implemented on a workstation assisted with a 32-bit graphic processing unit. A neural network platform that incorporates photonic components can be used to predict optical fibre nonlinearities and improve the signal quality of submarine fibre communications.