Methodology for developing photonic architectures
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photonics computers networks processors↗
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Silicon Photonics Parallel Processor for High Performance Computing and Sensor Networks: Phase I Final Report
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17 WIND ENERGY↗
Intelligent systems technology infrastructure for integrated systems
Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.
Lum, Henry, Jr.↗
On-demand directional microwave photon emission using waveguide quantum electrodynamics
Routing quantum information between non-local computational nodes is a foundation for extensible networks of quantum processors. Quantum information transfer between arbitrary nodes is generally mediated either by photons that propagate between them or by resonantly coupling nearby nodes. The utility is determined by the type of emitter, propagation channel and receiver. Conventional approaches involving propagating microwave photons have limited fidelity due to photon loss and are often unidirectional, whereas architectures that use direct resonant coupling are bidirectional in principle but can generally accommodate only a few local nodes. Here we demonstrate high-fidelity, on-demand, directional, microwave photon emission. We do this using an artificial molecule comprising two superconducting qubits strongly coupled to a bidirectional waveguide, effectively creating a chiral microwave waveguide. Quantum interference between the photon emission pathways from the molecule generates single photons that selectively propagate in a chosen direction. This circuit will also be capable of photon absorption, making it suitable for building interconnects within extensible quantum networks.
42 ENGINEERING↗
IceNet for FireBox - A Berkeley Warehouse-Scale Computer
Berkeley’s FireBox is a next-generation warehouse-scale computer (WSC) that utilizes the energy-efficiency and bandwidth density of integrated silicon-photonic interconnects to enable a new high-bandwidth and low-latency network fabric connecting thousands of compute nodes to petabytes of DRAM and Flash storage. The high bandwidth, low latency and high connectivity of FireBox’s WSC network fabric (IceNet) will enable dramatic improvements in the overall system energy efficiency enabling fine-grain power control on system resources (processors, links and memory/storage components). IceNet is a special 3-stage photonic Clos network architected to achieve ultra-low-latency connectivity between processor nodes and memory, drastically cutting down on the energy wasted in resource idling (processors and memory stalled due to pending network requests). This is achieved by integration of the first and last switch stages into processor/memory hub clients and by heavy over-provisioning of the high-radix middle switches (FlareSwitches). A key hardware component developed in this program is an active laser power management photonic integrated circuits called LightSpark. It interacts with the FlareSwitch and provides laser power to a subset of occupied switch ports, increasing the utilization of laser light in the photonic network by an order of magnitude. In addition to guiding the laser power where it is needed, the laser-power management module enables both wavelength and laser redundancy, significantly increasing the robustness of the system. The goal of the IceNet fabric is to enable communication between 1000s of processor nodes and PBs of memory/storage with <100ns latency, <10pJ/b wall-plug energy cost at multiple Pb/s of available connectivity bandwidth. These metrics represent two-orders of magnitude improvement with respect to the status of current data-center technology.
42 ENGINEERING↗
A 1-km photonic link connecting superconducting circuits in two dilution refrigerators
Superconducting quantum processors are a leading platform for implementing practical quantum computation algorithms. Although superconducting quantum processors with hundreds of qubits have been demonstrated, their further scale-up is constrained by the physical size and cooling power of dilution refrigerators. This constraint can be overcome by constructing a quantum network to interconnect qubits hosted in different refrigerators, which requires microwave-to-optical transducers to enable low-loss signal transmission over long distances. Although various designs and demonstrations have achieved high-efficiency and low-added-noise transducers, a coherent photonic link between separate refrigerators has not yet been realized. Here, in this work, we experimentally demonstrate coherent signal transfer between two superconducting circuits housed in separate dilution refrigerators, enabled by a pair of frequency-matched aluminium nitride electro-optic transducers connected via a 1-km telecom optical fibre. The optical frequency matching between two transducers is realized by an asymmetric photonic molecule design, and an overall 80 dB improvement in transduction efficiency over commercial electro-optic modulators is achieved, paving the way towards a fully quantum-enabled link. This work provides critical design guidelines for scalable superconducting quantum networks interconnected by photonic links.
nonlinear optics↗
Scaling the Ion Trap Quantum Processor
Trapped atomic ions are standards for quantum information processing, serving as quantum memories, hosts of quantum gates in quantum computers and simulators, and nodes of quantum communication networks. Quantum bits based on trapped ions enjoy a rare combination of attributes: They have exquisite coherence properties, they can be prepared and measured with nearly 100% efficiency, and they are readily entangled with each other through the Coulomb interaction or remote photonic interconnects. The outstanding challenge is the scaling of trapped ions to hundreds or thousands of qubits and beyond, at which scale quantum processors can outperform their classical counterparts in certain applications. We review the latest progress and prospects in that effort, with the promise of advanced architectures and new technologies, such as microfabricated ion traps and integrated photonics.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Diffractive optical computing in free space
Abstract Structured optical materials create new computing paradigms using photons, with transformative impact on various fields, including machine learning, computer vision, imaging, telecommunications, and sensing. This Perspective sheds light on the potential of free-space optical systems based on engineered surfaces for advancing optical computing. Manipulating light in unprecedented ways, emerging structured surfaces enable all-optical implementation of various mathematical functions and machine learning tasks. Diffractive networks, in particular, bring deep-learning principles into the design and operation of free-space optical systems to create new functionalities. Metasurfaces consisting of deeply subwavelength units are achieving exotic optical responses that provide independent control over different properties of light and can bring major advances in computational throughput and data-transfer bandwidth of free-space optical processors. Unlike integrated photonics-based optoelectronic systems that demand preprocessed inputs, free-space optical processors have direct access to all the optical degrees of freedom that carry information about an input scene/object without needing digital recovery or preprocessing of information. To realize the full potential of free-space optical computing architectures, diffractive surfaces and metasurfaces need to advance symbiotically and co-evolve in their designs, 3D fabrication/integration, cascadability, and computing accuracy to serve the needs of next-generation machine vision, computational imaging, mathematical computing, and telecommunication technologies.
36 MATERIALS SCIENCE↗
Phononic bus for coherent interfaces between a superconducting quantum processor, spin memory, and photonic quantum networks
A hybrid quantum system performs high-fidelity quantum state transduction between a superconducting (SC) microwave qubit and the ground state spin system of a solid-state artificial atom. This transduction is mediated via an acoustic bus connected by piezoelectric transducers to the SC microwave qubit. For SC circuit qubits and diamond silicon vacancy centers in an optimized phononic cavity, the system can achieve quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of SC circuit quantum computing and artificial atoms, the hybrid quantum system provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.
Englund, Dirk Robert↗
Analog optical computing primitives in silicon photonics
Optical computing accelerators help alleviate bandwidth and power consumption bottlenecks in electronics. In this paper, we show an approach to implementing logarithmic-type analog co-processors in silicon photonics and use it to perform the exponentiation operation and the recovery of a signal in the presence of multiplicative distortion. Finally, the function is realized by exploiting nonlinear-absorption-enhanced Raman amplification saturation in a silicon waveguide.
42 ENGINEERING↗
Neural network methods for radiation detectors and imaging
Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).
edge computing↗
Deterministic multi-qubit entanglement in a quantum network
High-fidelity deterministic quantum state transfer and multi-qubit entanglement are demonstrated in a quantum network comprising two superconducting quantum nodes one metre apart, with each node including three interconnected qubits. The generation of high-fidelity distributed multi-qubit entanglement is a challenging task for large-scale quantum communication and computational networks. The deterministic entanglement of two remote qubits has recently been demonstrated with both photons and phonons. However, the deterministic generation and transmission of multi-qubit entanglement has not been demonstrated, primarily owing to limited state-transfer fidelities. Here we report a quantum network comprising two superconducting quantum nodes connected by a one-metre-long superconducting coaxial cable, where each node includes three interconnected qubits. By directly connecting the cable to one qubit in each node, we transfer quantum states between the nodes with a process fidelity of 0.911 +/- 0.008. We also prepare a three-qubit Greenberger-Horne-Zeilinger (GHZ) state in one node and deterministically transfer this state to the other node, with a transferred-state fidelity of 0.656 +/- 0.014. We further use this system to deterministically generate a globally distributed two-node, six-qubit GHZ state with a state fidelity of 0.722 +/- 0.021. In this work, the GHZ state fidelities are clearly above the threshold of 1/2 for genuine multipartite entanglement, showing that this architecture can be used to coherently link together multiple superconducting quantum processors, providing a modular approach for building large-scale quantum computers.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Assessing Advanced Technology in CENATE
PNNL's Center for Advanced Technology Evaluation (CENATE) is a new U.S. Department of Energy center whose mission is to assess and facilitate access to emerging computing technology. CENATE is assessing a range of advanced technologies, from evolutionary to disruptive. Technologies of interest include the processor socket (homogeneous and accelerated systems), memories (dynamic, static, memory cubes), motherboards, networks (network interface cards and switches), and input/output and storage devices. CENATE is developing a multi-perspective evaluation process based on integrating advanced system instrumentation, performance measurements, and modeling and simulation. We show evaluations of two emerging network technologies: silicon photonics interconnects and the Data Vortex network. CENATE's evaluation also addresses the question of which machine is best for a given workload under certain constraints. We show a performance-power tradeoff analysis of a well-known machine learning application on two systems.
Tallent, Nathan R.↗
Photonic processing at NASA Ames Research Center
The Photonic Processing group is engaged in applied research on optical processors in support of the Ames vision to lead the development of autonomous intelligent systems. Optical processors, in conjunction with numeric and symbolic processors, are needed to provide the powerful processing capability that is required for many future agency missions. The research program emphasizes application of analog optical processing, where free-space propagation between components allows natural implementations of algorithms requiring a large degree of parallel computation. Special consideration is given in the Ames program to the integration of optical processors into larger, heterogeneous computational systems. Demonstration of the effective integration of optical processors within a broader knowledge-based system is essential to evaluate their potential for dependable operation in an autonomous environment such as space. The Ames Photonics program is currently addressing several areas of interest. One of the efforts is to develop an optical correlator system with two programmable spatial light modulators (SLMs) to perform distortion invariant pattern recognition. Another area of research is optical neural networks, also for use in distortion-invariant pattern recognition.
Ochoa, Ellen↗
Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks
As an optical processor, a diffractive deep neural network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light propagation through thin optical layers. With sufficient degrees of freedom, D2NNs can perform arbitrary complex-valued linear transformations using spatially coherent light. Similarly, D2NNs can also perform arbitrary linear intensity transformations with spatially incoherent illumination; however, under spatially incoherent light, these transformations are nonnegative, acting on diffraction-limited optical intensity patterns at the input field of view. Here, we expand the use of spatially incoherent D2NNs to complex-valued information processing for executing arbitrary complex-valued linear transformations using spatially incoherent light. Through simulations, we show that as the number of optimized diffractive features increases beyond a threshold dictated by the multiplication of the input and output space-bandwidth products, a spatially incoherent diffractive visual processor can approximate any complex-valued linear transformation and be used for all-optical image encryption using incoherent illumination. The findings are important for the all-optical processing of information under natural light using various forms of diffractive surface-based optical processors.
36 MATERIALS SCIENCE↗
Programmable photonic integrated meshes for modular generation of optical entanglement links
Abstract Large-scale generation of quantum entanglement between individually controllable qubits is at the core of quantum computing, communications, and sensing. Modular architectures of remotely-connected quantum technologies have been proposed for a variety of physical qubits, with demonstrations reported in atomic and all-photonic systems. However, an open challenge in these architectures lies in constructing high-speed and high-fidelity reconfigurable photonic networks for optically-heralded entanglement among target qubits. Here we introduce a programmable photonic integrated circuit (PIC), realized in a piezo-actuated silicon nitride (SiN)-in-oxide CMOS-compatible process, that implements an N × N Mach–Zehnder mesh (MZM) capable of high-speed execution of linear optical transformations. The visible-spectrum photonic integrated mesh is programmed to generate optical connectivity on up to N = 8 inputs for a range of optically-heralded entanglement protocols. In particular, we experimentally demonstrated optical connections between 16 independent pairwise mode couplings through the MZM, with optical transformation fidelities averaging 0.991 ± 0.0063. The PIC’s reconfigurable optical connectivity suffices for the production of 8-qubit resource states as building blocks of larger topological cluster states for quantum computing. Our programmable PIC platform enables the fast and scalable optical switching technology necessary for network-based quantum information processors.
47 OTHER INSTRUMENTATION↗
A Survey of Plasmas and Their Applications
Plasmas are everywhere and relevant to everyone. We bath in a sea of photons, quanta of electromagnetic radiation, whose sources (natural and artificial) are dominantly plasma-based (stars, fluorescent lights, arc lamps.. .). Plasma surface modification and materials processing contribute increasingly to a wide array of modern artifacts; e.g., tiny plasma discharge elements constitute the pixel arrays of plasma televisions and plasma processing provides roughly one-third of the steps to produce semiconductors, essential elements of our networking and computing infrastructure. Finally, plasmas are central to many cutting edge technologies with high potential (compact high-energy particle accelerators; plasma-enhanced waste processors; high tolerance surface preparation and multifuel preprocessors for transportation systems; fusion for energy production).
Eastman, Timothy E.↗
NASA Tech Briefs, March 2007
Topics include: Advanced Systems for Monitoring Underwater Sounds; Wireless Data-Acquisition System for Testing Rocket Engines; Processing Raw HST Data With Up-to-Date Calibration Data; Mobile Collection and Automated Interpretation of EEG Data; System for Secure Integration of Aviation Data; Servomotor and Controller Having Large Dynamic Range; Digital Multicasting of Multiple Audio Streams; Translator for Optimizing Fluid-Handling Components; AIRSAR Web-Based Data Processing; Pattern Matcher for Trees Constructed From Lists; Reducing a Knowledge-Base Search Space When Data Are Missing; Ground-Based Correction of Remote-Sensing Spectral Imagery; State-Chart Autocoder; Pointing History Engine for the Spitzer Space Telescope; Low-Friction, High-Stiffness Joint for Uniaxial Load Cell; Magnet-Based System for Docking of Miniature Spacecraft; Electromechanically Actuated Valve for Controlling Flow Rate; Plumbing Fixture for a Microfluidic Cartridge; Camera Mount for a Head-Up Display; Core-Cutoff Tool; Recirculation of Laser Power in an Atomic Fountain; Simplified Generation of High-Angular-Momentum Light Beams; Imaging Spectrometer on a Chip; Interferometric Quantum-Nondemolition Single-Photon Detectors; Ring-Down Spectroscopy for Characterizing a CW Raman Laser; Complex Type-II Interband Cascade MQW Photodetectors; Single-Point Access to Data Distributed on Many Processors; Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data; Computing a Stability Spectrum by Use of the HHT; Theoretical Studies of Routes to Synthesis of Tetrahedral N4; Estimation Filter for Alignment of the Spitzer Space Telescope; Antenna for Measuring Electric Fields Within the Inner Heliosphere; Improved High-Voltage Gas Isolator for Ion Thruster; and Hybrid Mobile Communication Networks for Planetary Exploration.
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