Engineering topics
Publications and source records attributed to Williams, Brian.
We demonstrate all-optical routing of wavelength-multiplexed fiber-optic data streams. Utilizing an all-optical frequency processor, we show low-noise broadcasting and carrier-frequency hopping of binary data without optical-to-electrical conversion.
Quantum technologies promise to revolutionize information processing through dramatic computational speed-ups and ultimate security compared with classical counterparts. As matter-based qubit systems increase in size, however, counteracting decoherence becomes challenging and places limits on how large a stand-alone system can be. These limitations, coupled with the many quantum computing platforms under development, have led researchers to view modular architectures, connected by a quantum network, as a promising path to large-scale quantum computing. Our group reported in several studies this year, progress on multiple fronts in such systems, using photons as quantum information carriers in the frequency domain.
We propose an all-optical frequency processor (AFP) for transparent optical networking, based on optical pulse shaping and electro-optic phase modulation. We numerically examine the AFP for frequency channel hopping and broadcasting operations, and show the required number of components scales favorably with the network size.
A method for estimating the amplitude response of built-in smartphone microphone sensors is pre- sented. The method is intended to be accessible to the general public, and comparison calibration measurements are performed in a non-isolated environment using conventional consumer products. A double reference sensor scheme is set up, consisting of a MB3 digital microbarometer (reference over the 0.5–2 Hz octave bands) and the iPrecisionMic smartphone microphone (reference above the 2 Hz octave band). The amplitude response of the iPrecisionMic sensor is first evaluated over the 1–2000 Hz octave bands. The amplitude response of three Samsung Galaxy S8 built-in smart- phone microphone sensors is then measured over the 0.5–2000 Hz octave bands. The Redvox Infrasound Recorder application (app) for Android is used to measure acoustic signals with the built-in smartphone microphone sensors. Amplitude response models in terms of digital gain are estimated for the test sensors based on the results. Last, self-noise levels for the iPrecisionMic and Samsung Galaxy S8 microphones are estimated and compared to infrasound ambient noise models. Results show an experimental capability for estimating the amplitude response of built-in smartphone microphone sensors in a non-isolated environment with conventional consumer products.
We analyze the first experimental two-photon frequency-bin gate: a coincidence-basis CNOT. A novel characterization approach based on Bayesian machine learning is developed to estimate the gate performance with measurements in the logical basis alone.
The effects of low-energy helium plasma on surface evolution and restructuring of micro-porous tungsten and tungsten-rhenium micro-engineered materials was experimentally investigated. Tungsten foam samples of 45 and 80 Pores Per Inch (PPI) of three types of textured surface architecture (nodular W, dense Re-pillars, and W-coated Re-pillars) were exposed to low-energy helium plasma at 80 and 200 eV to fluence levels of 1, 2, and 7 x 10 25 m -2 at 1123 K. The sidewalls of Re pillars exhibited surface holes due to trapped helium while their tips were found to form complex nano-scale web structures, 100's of microns across, rather than nano-tendrils (fuzz) that are often observed in flat W samples. A nano-necklace bead/string structure was observed for the first time on Re pillars, likely driven by a high density of nano-meter size helium bubbles crowded near pillar tips. W-coated Re pillars exhibited typical fuzz nanostructures seen on flat and untextured W-foam, albeit much shorter. While the height of W-fuzz was found to depend on the square root of ion fluence, the nano-web height was found to be linearly dependent on ion fluence. The fuzz was found to grow much slower on nodular foams as compared to planar tungsten, by as much as 25% slower in the W-coated Re pillar samples. Weight loss due to ion sputtering was found to be significantly reduced in nodular foam as compared to planar tungsten, but was found to be more pronounced with Re pillars. Surface coverage by nano-webs may provide insulation against plasma disruptions and act as a passive Thermal Protection System (TPS) that may be ablated during severe plasma disruptions, thus protecting the underlying surface. W-pillars or W-coated Re-pillars are found to allow trapped helium to diffuse out of the surface instead of building up sub-surface stress.
This article presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.
The next generation of acoustic sensors is emerging to supplement legacy sensors traditionally used in regional and global networks. These devices operate under similar principles as traditional sensors, without the need of a separate external digitizer. The calibration of these sensors against their predecessors is crucial to the modernization of conventional technologies. This work describes the characterization of the next-generation MB3 digital microbarometer and the iPrecision smartphone microphone in a non-isolated calibration room across the infrasound (i.e., 0.01–20 Hz) range. The intent is to evaluate nominal instrument performance before deployment. A portable rotary subwoofer is used as a controllable infrasound source to generate single-tone sinusoidal and broadband noise pressure waves in a room configured for calibration purposes. For each device, comparison measurements are made, from which the digital sensitivity and the parametric response is developed. The results provide insight into the performance of the sensors in non-isolated environments. By overlapping the responses of the test sensors, digital sensor performance across the infrasound range can be benchmarked. These responses may serve as a double-reference scheme in future pressure measurements and digital calibrations of acoustic sensors.
Precision medicine and the continuous analysis of “Big data” promises to improve patient outcomes dramatically in the near future. Very recently, healthcare facilities have started to explore automatic collection of patient-specific physiological data with the aim of reducing nursing workload and decreasing manual data entry errors. In addition to those purposes, continuous physiological data can be used for the early detection and prevention of common, and possibly fatal, diseases. For instance, poor patient outcomes from sepsis, a leading cause of mortality in healthcare facilities and a major driver of hospital costs in the USA, can be mitigated when detected early using screening tools that monitor the changing dynamics of physiological data. However, the potential cost of collecting continuous physiological data remains a barrier to the widespread adoption of automated high-frequency data collection systems. In this paper, we perform cost-benefit analysis (CBA) of machine learning applied to various types of acquisition systems (with different collection intervals) to determine if the benefits of such systems will outweigh their implementation costs. Although such systems can be used in the detection of various complications, in order to showcase the immediate benefits, we focus on the early detection of sepsis, one of the major challenges of hospital systems. We present a general approach to conduct such analysis for a wide range of hospitals and highlight its applicability using a case study for a small hospital with 150 beds and 3000 annual patients where the acquisition system would collect data at 1-min intervals. Finally, we discuss how the analysis may help guide incentives/policies with regard to adopting automated data acquisition systems.
We demonstrate the first two-photon gate for frequency-bin qubits, using optical pulse shaping and electro-optic phase modulation. Our coincidence-basis CNOT has a fidelity of 0.9947 ± 0.0008 and shows controlled qubit flips in the computational basis.
Well-defined and stable quantum networks are essential to realize functional quantum communication applications. In particular, the quantum states must be precisely controlled to produce meaningful results. To counteract the unstable phase shifts in photonic systems, we apply local Bell state measurements to calibrate a non-local quantum channel. The calibration procedure is tested by applying a time encoded quantum key distribution procedure using entangled photons.
We present the design and implementation of a software-defined quantum networking protocol and software switch integrated with a numerical quantum channel simulator. Our protocol design leverages recent advances in the OpenFlow protocol that enable software-defined control and management of optical network traffic using side-channel metadata. We implement this design using customization of the open source vSwitch for optical network routing, and we test the implementation using a numerical simulator of the quantum channel alongside actual network traffic. Our results support the integration of quantum communication with existing optical transport methods.
We describe a multi-party quantum secret sharing protocol utilizing two-photon entangled states in which the source is one of the secret sharing participants. It is experimentally easier to realize than methods using GHZ states.
Quantum networks provide a versatile infrastructure for communication, computing, and sensing with quantum information. Novel sources and detectors for transmitting and receiving quantum states are critical elements in the development and eventual deployment of robust quantum networks. Alongside performance, the compatibility of quantum network devices with modern networking infrastructure is an important requirement for deployment. We present results on the integration of quantum communication using superdense coding transmitted over optical fiber links into network environments. Our approach takes advantage of a novel complete Bell-state measurement setup that relies on hyper-entanglement in the temporal and polarization degrees of freedom for a two-photon state emitted from a quantum light source. Using linear optics and common single-photon detectors, we record a single-qubit channel capacity of 1.665±0.018. We then demonstrate a full experimental implementation of hybrid, quantum-classical communication protocol for image transfer applications. Our devices integrate with existing fiber optical network and software-defined transmitters and receivers as part of a modular design to provide an extensible quantum communication system that can adapt to future quantum technology goals.
A method for fabricating a cellular tritium breeder component includes obtaining a reticulated carbon foam skeleton comprising a network of interconnected ligaments. The foam skeleton is then melt-infiltrated with a tritium breeder material, for example, lithium zirconate or lithium titanate. The foam skeleton is then removed to define a cellular breeder component having a network of interconnected tritium purge channels. In an embodiment the ligaments of the foam skeleton are enlarged by adding carbon using chemical vapor infiltration (CVI) prior to melt-infiltration. In an embodiment the foam skeleton is coated with a refractory material, for example, tungsten, prior to melt infiltration.
This milestone report documents work performed in CASL that was broadly focused on the use of validated high-fidelity simulation codes to inform, improve and calibrate low-fidelity codes to facilitate multiphysics coupling, design, performance analysis, and risk assessment. This high-to-low (Hi2Lo) initiative has the following objectives: employ physics encapsulated in high-fidelity codes to improve the functionality of low-fidelity codes, quantify biases in low-fidelity codes, develop and calibrate physical models and closure relations so that low-fidelity codes more accurately incorporate requisite physics, and develop low-fidelity codes that can be effectively coupled to simulate multiphysics behavior. In combination, these efforts are designed to impact both CIPS and DNB. For example, the development and experimental design-based Bayesian calibration of dynamic gas conductance models in CTFFuel will provide the capability to better model crud-induced power shifts. Whereas the present emphasis has focused on the high-fidelity codes STAR-CCM+ and BISON and low-fidelity codes CTF and CTFFuel, future emphasis will be expanded to include MAMBA. During the reporting period, Hi2Lo efforts focused on two broad components: demonstration of the experimental design-based Bayesian calibration framework to calibrate CTF using both STAR-generated synthetic data and experimental data, and the use of STAR to inform and improve the turbulence modeling and grid heat transfer modeling capabilities in CTF. A complementary milestone focused on the implementation and verification of fuel models in CTFFuel, for which we demonstrated initial calibration results. Future Hi2Lo work will focus on the use of the experimental design-based Bayesian calibration framework, demonstrated this year for STAR and CTF, to calibrate parameters in the fuel swelling, fuel irradiation-induced densification, and fuel relocation models in CTFFuel using both experimental and BISON-generated data. A second component will focus on the continued use of STAR to improve grid modeling capabilities in CTF.
No abstract available