RESUMEN

An on-chip asymmetric directional coupler (DC) can convert fundamental modes to higher-order modes and is one of the core components of mode-division multiplexing (MDM) technology. In this study, we propose that waveguides of the asymmetric DC can be trimmed by silicon ion implantation to tune the effective refractive index and facilitate mode conversion into higher-order modes. Through this method of tuning, transmission changes of up to 18 dB have been realized with one ion implantation step. In addition, adjusting the position of the ion implantation on the waveguide can provide a further degree of control over the transmission into the resulting mode. The results of this work present a promising new route for the development of high-efficiency, low-loss mode converters for integrated photonic platforms, and aim to facilitate the application of MDM technology in emerging photonic neuromorphic computing.

RESUMEN

Advancements in optical coherence control1-5 have unlocked many cutting-edge applications, including long-haul communication, light detection and ranging (LiDAR) and optical coherence tomography6-8. Prevailing wisdom suggests that using more coherent light sources leads to enhanced system performance and device functionalities9-11. Our study introduces a photonic convolutional processing system that takes advantage of partially coherent light to boost computing parallelism without substantially sacrificing accuracy, potentially enabling larger-size photonic tensor cores. The reduction of the degree of coherence optimizes bandwidth use in the photonic convolutional processing system. This breakthrough challenges the traditional belief that coherence is essential or even advantageous in integrated photonic accelerators, thereby enabling the use of light sources with less rigorous feedback control and thermal-management requirements for high-throughput photonic computing. Here we demonstrate such a system in two photonic platforms for computing applications: a photonic tensor core using phase-change-material photonic memories that delivers parallel convolution operations to classify the gaits of ten patients with Parkinson's disease with 92.2% accuracy (92.7% theoretically) and a silicon photonic tensor core with embedded electro-absorption modulators (EAMs) to facilitate 0.108 tera operations per second (TOPS) convolutional processing for classifying the Modified National Institute of Standards and Technology (MNIST) handwritten digits dataset with 92.4% accuracy (95.0% theoretically).

Asunto(s)

RESUMEN

Efficient fiber-to-chip couplers for multi-port access to photonic integrated circuits are paramount for a broad class of applications, ranging, e.g., from telecommunication to photonic computing and quantum technologies. Grating-based approaches are often desirable for providing out-of-plane access to the photonic circuits. However, on photonic platforms characterized by a refractive index ≃ 2 at telecom wavelength, such as silicon nitride or thin-film lithium niobate, the limited scattering strength has thus far hindered the achievement of coupling efficiencies comparable to the ones attainable in silicon photonics. Here we present a flexible strategy for the realization of highly efficient grating couplers on such low-index photonic platforms. To simultaneously reach a high scattering efficiency and a near-unitary modal overlap with optical fibers, we make use of self-imaging gratings designed with a negative diffraction angle. To ensure high directionality of the diffracted light, we take advantage of a metal back-reflector patterned underneath the grating structure by cryogenic deep reactive ion etching of the silicon handle. Using silicon nitride as a testbed material, we experimentally demonstrate coupling efficiency up to - 0.55 dB in the telecom C-band with high chip-scale device yield.

RESUMEN

Targeted manipulation of neural activity via light has become an indispensable tool for gaining insights into the intricate processes governing single neurons and complex neural networks. To shed light onto the underlying interaction mechanisms, it is crucial to achieve precise control of individual neural activity, as well as a spatial read-out resolution on the nanoscale. Here, a versatile photonic platform with subcellular resolution for stimulation and monitoring of in-vitro neurons is demonstrated. Low-loss photonic waveguides are fabricated on glass substrates using nanoimprint lithography and featuring a loss of only -0.9 ± 0.2 dB cm-1 at 489 nm and are combined with optical fiber-based waveguide-access and backside total internal reflection fluorescence microscopy. Neurons are grown on the bio-functionalized photonic chip surface and, expressing the light-sensitive ion channel Channelrhodopsin-2, are stimulated within the evanescent field penetration depth of 57 nm of the biocompatible waveguides. The versatility and cost-efficiency of the platform, along with the possible subcellular resolution, enable tailor-made investigations of neural interaction dynamics with defined spatial control and high throughput.

Asunto(s)

RESUMEN

Photonic integrated circuits (PICs) are revolutionizing the realm of information technology, promising unprecedented speeds and efficiency in data processing and optical communication. However, the nanoscale precision required to fabricate these circuits at scale presents significant challenges, due to the need to maintain consistency across wavelength-selective components, which necessitates individualized adjustments after fabrication. Harnessing spectral alignment by automated silicon ion implantation, in this work scalable and non-volatile photonic computational memories are demonstrated in high-quality resonant devices. Precise spectral trimming of large-scale photonic ensembles from a few picometers to several nanometres is achieved with long-term stability and marginal loss penalty. Based on this approach, spectrally aligned photonic memory and computing systems for general matrix multiplication are demonstrated, enabling wavelength multiplexed integrated architectures at large scales.

RESUMEN

Experiments in photonics, laser optics, and quantum technology require low-loss, thermal, and mechanical stability. While photonic integrated circuits on monolithic chips achieve interferometric stability, important nanophotonic material systems suffer from propagation loss, thermal drift, and noise that prevent, for example, precise frequency stabilization of resonators. Here we show that tantalum pentoxide (Ta2O5) on insulator micro-ring resonators combine quality factors beyond 1.8 Mio with vanishing temperature-dependent wavelength shift in a relevant 70 K to 90 K temperature range. Our Ta2O5-on-SiO2 devices will thus enable athermal operation at liquid nitrogen temperatures, paving the way for ultra-stable low-cost resonators, as desired for wavelength division multiplexing, on chip frequency stabilization and low-noise optical frequency comb generation.

RESUMEN

We present an adaptive optical neural network based on a large-scale event-driven architecture. In addition to changing the synaptic weights (synaptic plasticity), the optical neural network's structure can also be reconfigured enabling various functionalities (structural plasticity). Key building blocks are wavelength-addressable artificial neurons with embedded phase-change materials that implement nonlinear activation functions and nonvolatile memory. Using multimode focusing, the activation function features both excitatory and inhibitory responses and shows a reversible switching contrast of 3.2 decibels. We train the neural network to distinguish between English and German text samples via an evolutionary algorithm. We investigate both the synaptic and structural plasticity during the training process. On the basis of this concept, we realize a large-scale network consisting of 736 subnetworks with 16 phase-change material neurons each. Overall, 8398 neurons are functional, highlighting the scalability of the photonic architecture.

RESUMEN

Emerging photonic information processing systems require chip-level integration of controllable nanoscale light sources at telecommunication wavelengths. Currently, substantial challenges remain in the dynamic control of the sources, the low-loss integration into a photonic environment, and in the site-selective placement at desired positions on a chip. Here, we overcome these challenges using heterogeneous integration of electroluminescent (EL), semiconducting carbon nanotubes (sCNTs) into hybrid two dimensional - three dimensional (2D-3D) photonic circuits. We demonstrate enhanced spectral line shaping of the EL sCNT emission. By back-gating the sCNT-nanoemitter we achieve full electrical dynamic control of the EL sCNT emission with high on-off ratio and strong enhancement in the telecommunication band. Using nanographene as a low-loss material to electrically contact sCNT emitters directly within a photonic crystal cavity enables highly efficient EL coupling without compromising the optical quality of the cavity. Our versatile approach paves the way for controllable integrated photonic circuits.

RESUMEN

Scalable photonic quantum computing architectures pose stringent requirements on photonic processing devices. The needs for low-loss high-speed reconfigurable circuits and near-deterministic resource state generators are some of the most challenging requirements. Here, we develop an integrated photonic platform based on thin-film lithium niobate and interface it with deterministic solid-state single-photon sources based on quantum dots in nanophotonic waveguides. The generated photons are processed with low-loss circuits programmable at speeds of several gigahertz. We realize a variety of key photonic quantum information processing functionalities with the high-speed circuits, including on-chip quantum interference, photon demultiplexing, and reprogrammability of a four-mode universal photonic circuit. These results show a promising path forward for scalable photonic quantum technologies by merging integrated photonics with solid-state deterministic photon sources in a heterogeneous approach to scaling up.

RESUMEN

Integrated photonic circuits (PICs) have seen an explosion in interest, through to commercialization in the past decade. Most PICs rely on sharp resonances to modulate, steer, and multiplex signals. However, the spectral characteristics of high-quality resonances are highly sensitive to small variations in fabrication and material constants, which limits their applicability. Active tuning mechanisms are commonly employed to account for such deviations, consuming energy and occupying valuable chip real estate. Readily employable, accurate, and highly scalable mechanisms to tailor the modal properties of photonic integrated circuits are urgently required. Here, we present an elegant and powerful solution to achieve this in a scalable manner during the semiconductor fabrication process using existing lithography tools: by exploiting the volume shrinkage exhibited by certain polymers to permanently modulate the waveguide's effective index. This technique enables broadband and lossless tuning with immediate applicability in wide-ranging applications in optical computing, telecommunications, and free-space optics.

RESUMEN

Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved computational success. Here, we achieve this milestone by demonstrating an in-memory photonic-electronic dot-product engine, one that decouples electronic programming of phase-change materials (PCMs) and photonic computation. Specifically, we develop non-volatile electronically reprogrammable PCM memory cells with a record-high 4-bit weight encoding, the lowest energy consumption per unit modulation depth (1.7 nJ/dB) for Erase operation (crystallization), and a high switching contrast (158.5%) using non-resonant silicon-on-insulator waveguide microheater devices. This enables us to perform parallel multiplications for image processing with a superior contrast-to-noise ratio (≥87.36) that leads to an enhanced computing accuracy (standard deviation σ ≤ 0.007). An in-memory hybrid computing system is developed in hardware for convolutional processing for recognizing images from the MNIST database with inferencing accuracies of 86% and 87%.

RESUMEN

Superconducting nanowire single-photon detectors are an enabling technology for modern quantum information science and are gaining attractiveness for the most demanding photon counting tasks in other fields. Embedding such detectors in photonic integrated circuits enables additional counting capabilities through nanophotonic functionalization. Here, we show how a scalable number of waveguide-integrated superconducting nanowire single-photon detectors can be interfaced with independent fiber optic channels on the same chip. Our plug-and-play detector package is hosted inside a compact and portable closed-cycle cryostat providing cryogenic signal amplification for up to 64 channels. We demonstrate state-of-the-art multi-channel photon counting performance with average system detection efficiency of (40.5 ± 9.4)% and dark count rate of (123 ± 34) Hz for 32 individually addressable detectors at minimal noise-equivalent power of (5.1 ± 1.2) · 10-18 W/Hz. Our detectors achieve timing jitter as low as 26 ps, which increases to (114 ± 17) ps for high-speed multi-channel operation using dedicated time-correlated single photon counting electronics. Our multi-channel single photon receiver offers exciting measurement capabilities for future quantum communication, remote sensing, and imaging applications.

RESUMEN

The field of quantum information processing offers secure communication protected by the laws of quantum mechanics and is on the verge of finding wider application for the information transfer of sensitive data. To improve cost-efficiency, extensive research is being carried out on the various components required for high data throughput using quantum key distribution (QKD). Aiming for an application-oriented solution, we report the realization of a multichannel QKD system for plug-and-play high-bandwidth secure communication at telecom wavelengths. We designed a rack-sized multichannel superconducting nanowire single photon detector (SNSPD) system, as well as a highly parallelized time-correlated single photon counting (TCSPC) unit. Our system is linked to an FPGA-controlled QKD evaluation setup for continuous operation, allowing us to achieve high secret key rates using a coherent-one-way protocol.

RESUMEN

Efficiently collecting light from single-photon emitters is crucial for photonic quantum technologies. Here, we develop and use an ultralow fluorescence photopolymer to three-dimensionally print micrometer-sized elliptical lenses on individual precharacterized single-photon emitters in hexagonal boron nitride (hBN) nanocrystals, operating in the visible regime. The elliptical lens design beams the light highly efficiently into the far field, rendering bulky objective lenses obsolete. Using back focal plane imaging, we confirm that the emission is collimated to a narrow low-divergence beam with a half width at half-maximum of 2.2°. Using photon correlation measurements, we demonstrate that the single-photon character remains undisturbed by the polymer lens. The strongly directed emission and increased collection efficiency is highly beneficial for quantum optical experiments. Furthermore, our approach paves the way for a highly parallel fiber-based detection of single photons from hBN nanocrystals.

RESUMEN

Photonic integrated circuits (PICs) have enabled novel functionality in quantum optics, quantum information processing and quantum communication. PICs based on Silicon Nitride (Si3N4) provide low-loss passive components and are compatible with efficient superconducting nanowire single-photon detectors (SNSPDs). For realizing functional quantum photonic systems, the integration with active phase-shifters is needed which is challenging at the cryogenic temperatures needed for operating SNSPDs. Here we demonstrate a cryo-compatible phase shifter using a low-voltage opto-mechanical modulator and show joint operation with SNSPDs at 1.3 K. We achieve a half-wave voltage of 4.6 V, single-photon detection with 88% on-chip detection efficiency (OCDE) and a low timing jitter of 12.2 ps. Our approach allows for operating reconfigurable quantum photonic circuits with low dissipation in a cryogenic setting.

RESUMEN

With more and more aspects of modern life and scientific tools becoming digitized, the amount of data being generated is growing exponentially. Fast and efficient statistical processing, such as identifying correlations in big datasets, is therefore becoming increasingly important, and this, on account of the various compute bottlenecks in modern digital machines, has necessitated new computational paradigms. Here, we demonstrate one such novel paradigm, via the development of an integrated phase-change photonics engine. The computational memory engine exploits the accumulative property of Ge2Sb2Te5 phase-change cells and wavelength division multiplexing property of optics in delivering fully parallelized and colocated temporal correlation detection computations. We investigate this property and present an experimental demonstration of identifying real-time correlations in data streams on the social media platform Twitter and high-traffic computing nodes in data centers. Our results demonstrate the use case of high-speed integrated photonics in accelerating statistical analysis methods.

RESUMEN

Antimony sulfide, Sb2S3, is interesting as the phase-change material for applications requiring high transmission from the visible to telecom wavelengths, with its band gap tunable from 2.2 to 1.6 eV, depending on the amorphous and crystalline phase. Here we present results from an interlaboratory study on the interplay between the structural change and resulting optical contrast during the amorphous-to-crystalline transformation triggered both thermally and optically. By statistical analysis of Raman and ellipsometric spectroscopic data, we have identified two regimes of crystallization, namely 250°C ≤ T < 300°C, resulting in Type-I spherulitic crystallization yielding an optical contrast Δn ∼ 0.4, and 300 ≤ T < 350°C, yielding Type-II crystallization bended spherulitic structure with different dielectric function and optical contrast Δn ∼ 0.2 below 1.5 eV. Based on our findings, applications of on-chip reconfigurable nanophotonic phase modulators and of a reconfigurable high-refractive-index core/phase-change shell nanoantenna are designed and proposed.

RESUMEN

The ever-increasing demands for data processing and storage will require seamless monolithic co-integration of electronics and photonics. Phase-change materials are uniquely suited to fulfill this function due to their dual electro-optical sensitivity, nonvolatile retention properties, and fast switching dynamics. The extreme size disparity however between CMOS electronics and dielectric photonics inhibits the realization of efficient and compact electrically driven photonic switches, logic and routing elements. Here, the authors achieve an important milestone in harmonizing the two domains by demonstrating an electrically reconfigurable, ultra-compact and nonvolatile memory that is optically accessible. The platform relies on localized heat, generated within a plasmonic structure; this uniquely allows for both optical and electrical readout signals to be interlocked with the material state of the PCM while still ensuring that the writing operation is electrically decoupled. Importantly, by miniaturization and effective thermal engineering, the authors achieve unprecedented energy efficiency, opening up a path towards low-energy optoelectronic hardware for neuromorphic and in-memory computing.

RESUMEN

The use of nonlinear elements with memory as photonic computing components has seen a huge surge in interest in recent years with the rise of artificial intelligence and machine learning. A key component is the nonlinear element itself. A class of materials known as phase change materials has been extensively used to demonstrate the viability of such computing. However, such materials continue to have relatively slow switching speeds, and issues with cyclability related to phase segregation of phase change alloys. Here, using antimony (Sb) thin films with thicknesses less than 5 nm we demonstrate reversible, ultrafast switching on an integrated photonic platform with retention time of tens of seconds. We use subpicosecond pulses, the shortest used to switch such elements, to program seven distinct memory levels. This portends their use in ultrafast nanophotonic applications ranging from nanophotonic beam steerers to nanoscale integrated elements for photonic computing.

Asunto(s)

RESUMEN

We study degenerate spontaneous parametric downconversion in a structure composed of two linearly uncoupled resonators, in which the linear properties of the fundamental and second-harmonic field can be engineered independently. As an example, we show that in this system it is simple to generate photon pairs that are nearly uncorrelated in energy. These results extend the use of linearly uncoupled resonators to the case of second-order nonlinear interactions.