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At least 91 records · Page 5

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability.

Source record↗

Distributed-Memory Sparse Deep Neural Network Inference Using Global Arrays

Partitioned Global Address Space (PGAS) models exhibit tremendous promise in developing efficient and productive distributed-memory parallel applications. They have been used extensively in scientific computations due to conveniently offering a ``shared-memory''-like model and convenient interfaces that separate communication with synchronization. Traditionally, PGAS communication models have been applied to dense/contiguously distributed data, but most modern applications depict varied levels of sparsity. Existing PGAS models require certain adaptations to support distributed sparse computations, since associated computations often require matrix arithmetic, in addition to data movement. The Global Arrays toolkit from Pacific Northwest National Laboratory (PNNL) is one of the earliest PGAS models to combine one-sided data communication and distributed matrix operations and is still used in the popular NWChem quantum chemistry suite. Recently, we have expanded the Global Arrays toolkit to support common sparse operations, like sparse matrix-dense matrix multiplies (SpMM), sparse matrix-sparse matrix multiplication (SpGEMM) and Sampled Dense-Dense Matrix Multiplication (SDDMM). As it turns out, these operations are the bedrock of sparse Deep Learning (DL); sparse deep neural networks and Graph Neural Networks (GNNs) have gained increasing attention recently in achieving speedups on training and inference with reduced memory footprints. Unlike scientific applications in High Performance Computing (HPC), modern (distributed-memory capable) DL toolkits often rely on non-standardized and closed-source vendor software optimizations, creating challenges in software-hardware co-design at scale. Our goal is to support a variety of distributed-memory sparse matrix operations and helper functions in the newly created Sparse Global Arrays (SGA), such that it is possible to build portable and productive Machine Learning scenarios for algorithm/software and hardware codesign purposes. Contemporary data-parallel schemes for training/inference are undergoing a major overhaul since model replication limits scalability and causes resource inefficiencies. As such, we have adopted tensor parallelism in decomposing the model and inputs, to mitigate memory issues. Current implementation is built on top of MPI and uses CPUs to maximize the portability across the platforms.

Distributed computing, machine learning↗

MQW Optical Feedback Modulators And Phase Shifters

Laser diodes equipped with proposed multiple-quantum-well (MQW) optical feedback modulators prove useful in variety of analog and digital optical-communication applications, including fiber-optic signal-distribution networks and high-speed, low-crosstalk interconnections among super computers or very-high-speed integrated circuits. Development exploits accompanying electro-optical aspect of QCSE - variation in index of refraction with applied electric field. Also exploits sensitivity of laser diodes to optical feedback. Approach is reverse of prior approach.

Jackson, Deborah J.↗

Efficient Routing of Quantum LDPC Codes on Programmable 2D Toric Architectures

Quantum low-density parity-check codes are promising candidates towards scalable fault-tolerant quantum computation. Among these, bivariate bicycle (BB) codes offer superior encoding rates and large code distance compared to surface codes. However, their requirement on long-range stabilizer measurements poses significant challenges for implementation on realistic hardware with limited connectivity, such as superconducting circuit platforms. In this work, we introduce a novel hardware-software co-design that leverages a programmable communication network architecture to address these limitations. Our approach utilizes a 2D toric network of oscillators as a flexible communication fabric linking qubits at each site. Such architecture significantly reduces the number of long-range couplers required from O ( n ) to O (√ n ). Dual-rail qubits, along with native gates including Swap-Wait-Swap gates and beamsplitter SWAPs, ensure that long-range two-qubit gates can be executed with high fidelity and low latency. To further enhance performance, our qubit layout and routing algorithm utilize symmetries of the codes and enable maximum parallelism for long-range two-qubit gates, maintaining a low syndrome extraction cycle duration and scalability over the code length. We perform circuit-level simulation with realistic noise modeling based on experimental hardware parameters, observing an logical error rate per logical qubit per cycle of 3.06% for [[18,4,4]] BB code, 2.6× less than the existing experimental result. These findings provide a practical roadmap and identify key technological advancements needed to achieve low-overhead fault-tolerant quantum computing at scale.

Liu, Kun [Yale Univ., New Haven, CT (United States↗

Parallelized telecom quantum networking with an ytterbium-171 atom array

The integration of quantum computers and sensors into a quantum network enables new capabilities in quantum information science. Most networks with atom-like qubits operate at visible or near-ultraviolet wavelengths and require conversion to the telecom band for long-distance communication, which reduces efficiency and potentially introduces noise. In this article we report high-fidelity entanglement between ytterbium-171 atoms and optical photons generated directly in the telecommunication band, where fibre loss is low. The nuclear spin of the atom is entangled with a single photon in the time-bin basis, yielding a high atom-measurement-corrected atom–photon Bell state fidelity. This can be further improved by addressing photon measurement errors. By imaging the atom array onto an optical fibre array, we also implement a parallelized networking protocol that can increase the remote entanglement rate proportionately with the number of channels. We also preserve coherence on a memory qubit during operations on communication qubits. These results support the integration of atomic systems into scalable quantum networks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nanoelectronics: Opportunities for future space applications

Further improvements in the performance of integrated electronics will eventually halt due to practical fundamental limits on our ability to downsize transistors and interconnect wiring. Avoiding these limits requires a revolutionary approach to switching device technology and computing architecture. Nanoelectronics, the technology of exploiting physics on the nanometer scale for computation and communication, attempts to avoid conventional limits by developing new approaches to switching, circuitry, and system integration. This presentation overviews the basic principles that operate on the nanometer scale that can be assembled into practical devices and circuits. Quantum resonant tunneling (RT) is used as the center-piece of the overview since RT devices already operate at high temperature (120 degrees C) and can be scaled, in principle, to a few nanometers in semiconductors. Near- and long-term applications of GaAs and silicon quantum devices are suggested for signal and information processing, memory, optoelectronics, and radio frequency (RF) communication.

Frazier, Gary↗

High-Q cavity interface for color centers in thin film diamond

Quantum information technology offers the potential to realize unprecedented computational resources via secure channels distributing entanglement between quantum computers. Diamond, as a host to optically-accessible spin qubits, is a leading platform to realize quantum memory nodes needed to extend such quantum links. Photonic crystal (PhC) cavities enhance light-matter interaction and are essential for an efficient interface between spins and photons that are used to store and communicate quantum information respectively. Here, we demonstrate one- and two-dimensional PhC cavities fabricated in thin-film diamonds, featuring quality factors (Q) of 1.8 × 10 5 and 1.6 × 10 5 , respectively, the highest Qs for visible PhC cavities realized in any material. Importantly, our fabrication process is simple and high-yield, based on conventional planar fabrication techniques, in contrast to the previous with complex undercut processes. We also demonstrate fiber-coupled 1D PhC cavities with high photon extraction efficiency, and optical coupling between a single SiV center and such a cavity at 4 K achieving a Purcell factor of 18. The demonstrated photonic platform may fundamentally improve the performance and scalability of quantum nodes and expedite the development of related technologies.

97 MATHEMATICS AND COMPUTING↗

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

97 MATHEMATICS AND COMPUTING↗

Control Implemented on Quantum Computers: Effects of Noise, Non-Determinism, and Entanglement

Quantum computing has advanced in recent years to the point that there are now some quantum computers and quantum simulators available to the public for use. In addition, quantum computing is beginning to receive attention within the process systems engineering community for directions such as machine learning and optimization. A logical next step for its evaluation within process systems engineering is for control, specifically, for computing control actions to be applied to process systems. In this work, we provide some initial studies regarding the implementation of control on quantum computers, including the implementation of a single-input/single-output proportional control law on a quantum simulator with noise, evaluation of potential impacts of non-determinism on theory for advanced control laws, and discussion of consequences of the way that entanglement works for next-generation manufacturing communication objectives.

Kip Nieman↗

Cybersecurity Considerations for Emerging Energy Technologies

AI, cloud computing, post-quantum cryptography, zero-trust architectures, microgrids, and virtual power plants. What do these things have in common? They are all emerging technologies in the clean energy space that will be a critical part of grid modernization efforts. As we work towards clean energy and decarbonization targets, these technologies, developed to solve real-world problems, will help us reach goals and achieve new efficiencies as the paradigm of grid operation shifts. However, there are growing concerns about the cybersecurity risks associated with these trending topics as they are used in critical infrastructure applications. This talk will cover gaps, challenges, and opportunities for the secure implementation of grid modernization solutions and novel energy applications of state-of-the-art networking and communications. Proactive risk mitigation strategies, including the application of cyber-informed engineering, will be discussed. Practical applications of these techniques will help provide countermeasures to the impact of cyberattacks on critical infrastructure technologies in a new, digitized grid landscape.

14 SOLAR ENERGY↗

Novel Highly Parallel and Systolic Architectures Using Quantum Dot-Based Hardware

VLSI technology has made possible the integration of massive number of components (processors, memory, etc.) into a single chip. In VLSI design, memory and processing power are relatively cheap and the main emphasis of the design is on reducing the overall interconnection complexity since data routing costs dominate the power, time, and area required to implement a computation. Communication is costly because wires occupy the most space on a circuit and it can also degrade clock time. In fact, much of the complexity (and hence the cost) of VLSI design results from minimization of data routing. The main difficulty in VLSI routing is due to the fact that crossing of the lines carrying data, instruction, control, etc. is not possible in a plane. Thus, in order to meet this constraint, the VLSI design aims at keeping the architecture highly regular with local and short interconnection. As a result, while the high level of integration has opened the way for massively parallel computation, practical and full exploitation of such a capability in many applications of interest has been hindered by the constraints on interconnection pattern. More precisely. the use of only localized communication significantly simplifies the design of interconnection architecture but at the expense of somewhat restricted class of applications. For example, there are currently commercially available products integrating; hundreds of simple processor elements within a single chip. However, the lack of adequate interconnection pattern among these processing elements make them inefficient for exploiting a large degree of parallelism in many applications.

Fijany, Amir↗

Quantum Key Distribution Applicability to Smart Grid Cybersecurity Systems

To meet the increasing demand for electricity and to have a more reliable and resilient electric grid against conventional and extreme events, grid modernization is more crucial now than ever before. This will require the development and deployment of devices that provide advanced communication capabilities. The overall efficiency, reliability, and resilience of the smart grid will be inextricably linked to the exchange of information between these devices. Unfortunately, the increased information flow will increase the potential attack surface and introduce new vulnerabilities. While a smarter grid will depend critically on information flow, these benefits will be accrued only if that information can be protected. Nowadays, information is secured in smart grids primarily through cryptography. However, with the increasing number of sophisticated attacks as well as the increasing computational power, the security of the “classical” cryptographic algorithms is threatened. Quantum information science offers solutions to this problem, specifically quantum key distribution (QKD), which provides a means for the generation and secure distribution of symmetric cryptographic keys. The security of QKD stems ultimately from the very nature of quantum physics. In this paper, we investigate the applicability of QKD to the various smart grid sectors and specific use cases. We have identified 18 smart grid use cases of interest for QKD suitability together with 7 QKD factors used for the assessment of the various use cases. For each use case, the impact to security of the loss of confidentiality, integrity, and/or availability is specified. In addition, the suitability of QKD is assessed for each use case with respect to multiple factors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Laboratory Characterization and Modeling of a Near-Infrared Enhanced Photomultiplier Tube

The photon-starved channel for optical communications from deep space requires the development of detector technology that can achieve photon-counting sensitivities with high bandwidth. In this article, a near-infrared enhanced photomultiplier tube (PMT) with a quantum e.ciency of 0.08 at a 1.06- m wavelength is characterized in the laboratory. A Polya distribution model is used to compute the probability distribution function of the emitted secondary photoelectrons from the PMT. The model is compared with measured pulse-height distributions with reasonable agreement. The model accounts for realistic device parameters, such as the individual dynode stage gains and a shape parameter that is representative of the spatial uniformity of response across the photocathode and dynodes. Bit-error rate (BER) measurements also are presented for 4- and 8-pulse-position modulation (PPM) modulation schemes with data rates of 20 to 30 Mb/s. A BER of 10-2 is obtained for a mean of 8 detected photons.

Biswas, A.↗

Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System

Despite quantum computing's rapid development, current systems remain limited in practical applications due to their limited qubit count and quality. Various technologies, such as superconducting, trapped ions, and neutral atom quantum computing technologies are progressing towards a fault tolerant era, however they all face a diverse set of challenges in scalability and control. Recent efforts have focused on multi-node quantum systems that connect multiple smaller quantum devices to execute larger circuits. Future demonstrations hope to use quantum channels to couple systems, however current demonstrations can leverage classical communication with circuit cutting techniques. This involves cutting large circuits into smaller subcircuits and reconstructing them post-execution. However, existing cutting methods are hindered by lengthy search times as the number of qubits and gates increases. Additionally, they often fail to effectively utilize the resources of various worker configurations in a multi-node system. To address these challenges, we introduce FitCut, a novel approach that transforms quantum circuits into weighted graphs and utilizes a community-based, bottom-up approach to cut circuits according to resource constraints, e.g., qubit counts, on each worker. FitCut also includes a scheduling algorithm that optimizes resource utilization across workers. Implemented with Qiskit and evaluated extensively, FitCut significantly outperforms the Qiskit Circuit Knitting Toolbox, reducing time costs by factors ranging from 3 to 2000 and improving resource utilization rates by up to 3.88 times on the worker side, achieving a system-wide improvement of 2.86 times.

Kan, Shuwen [Fordham University]↗

High-fidelity remote entanglement of trapped atoms mediated by time-bin photons

Abstract Photonic interconnects between quantum processing nodes are likely the only way to achieve large-scale quantum computers and networks. The bottleneck in such an architecture is the interface between well-isolated quantum memories and flying photons. We establish high-fidelity entanglement between remotely separated trapped atomic qubit memories, mediated by photonic qubits stored in the timing of their pulses. Such time-bin encoding removes sensitivity to polarization errors, enables long-distance quantum communication, and is extensible to quantum memories with more than two states. Using a measurement-based error detection process and suppressing a fundamental source of error due to atomic recoil, we achieve an entanglement fidelity of 97% and show that fundamental limits due to atomic recoil still allow fidelities in excess of 99.9%.

Science & Technology - Other Topics↗

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Sterling, Thomas↗

NASA in Silicon Valley

Whether looking back only a few years or more than a century, our world has been changing. Communication networks are more widespread and interconnected than at any other time in human history. Computing power that was only imagined a generation ago is now widely available and can fit in the palm of a hand. The miniaturization of the integrated circuit has brought us close to the limit of what is possible with silicon as we explore new possibilities in the quantum realm. For over 80 years, NASA’s Ames Research Center in California’s Silicon Valley has held a special place amidst such change. With change, there also is continuity. Since 1939, Ames contributions have fundamentally shaped fields of study related to aeronautics and space. The ingenuity and problem-solving capabilities of personnel at Ames have affected all our lives in numerous ways, from everyday air travel to how we envision the possibility of life on other worlds. This publication is a mere hint at the rich history of Ames, told primarily through images that capture some of the recurring threads that have intertwined over that time. A bibliography points the reader to more detailed histories of Ames published over the years. They are excellent resources and, like all historical work, unavoidably incomplete. Our standing invitation in the present is to preserve what we can to help us understand where we are and how we arrived.

History↗

Toward a 2D Local Implementation of Quantum Low-Density Parity-Check Codes

Geometric locality is an important theoretical and practical factor for quantum low-density parity-check (qLDPC) codes that affects code performance and ease of physical realization. For device architectures restricted to two-dimensional (2D) local gates, naively implementing the high-rate codes suitable for low-overhead fault-tolerant quantum computing incurs prohibitive overhead. In this work, we present an error-correction protocol built on a bilayer architecture that aims to reduce operational overheads when restricted to 2D local gates by measuring some generators less frequently than others. We investigate the family of bivariate-bicycle qLDPC codes and show that they are well suited for a parallel syndrome-measurement scheme using fast routing with local operations and classical communication (LOCC). Through circuit-level simulations, we find that in some parameter regimes, bivariate-bicycle codes implemented with this protocol have logical error rates comparable to the surface code while using fewer physical qubits. Published by the American Physical Society 2025

Berthusen, Noah (ORCID:0000000275862786)↗