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At least 955 records · Page 53

A Low-Memory Spectral-Correlation Analyzer for Digital QAM-SRRC Waveforms

Cyclostationary signal processing (CSP) provides the ability to estimate received waveforms' statistical features blindly. Quadrature amplitude modulated (QAM) waveforms, when filtered by the square-root-raised cosine (SRRC) pulse shape function, have cyclic features that CSP can exploit to detect waveform parameters such as symbol rate (SR) and center frequency (CF). The estimation of these SR-CF pairs enables a cognitive radio (CR) to perform spectrum sensing techniques such as spectrum sharing and interference mitigation. Here, we investigate a field-programmable gate array (FPGA) application of a blind symbol rate-center frequency estimator. First, this study provides a background on the theory behind the cyclic spectral density function (CSD), spectral correlation analyzers (SCA), and spectrum sensing. Following this is a discussion on the motivation for CubeSat spectrum sensing. An SCA implementation for low-memory devices, such as FPGA-based CubeSat, is then describes. The paper concludes by reporting the performance characteristics of the newly developed streaming-based SCA.

FPGA↗

Acoustic Radiation From a Superconducting Qubit: From Spontaneous Emission to Rabi Oscillations

Hybrid quantum systems that utilize controllable coupling between phonons and superconducting qubits could pave the way for a new generation of compact quantum memories and sensor technologies. However, the same electromechanical interaction mechanisms that enable coherent qubit-phonon coupling can also lead to decoherence due to the spontaneous phonon emission. In this paper we study the dynamics of a qubit coupled to an acoustic resonator by a piezoelectric film. By varying the surface topography of the resonator from rough to flat to shaped, we explore the crossover from fast decay of an excited qubit to quantum-coherent coupling between the qubit and an isolated phonon mode. The developed theoretical model allows us to establish and check quantitative links between the results obtained for the rough and shaped topographies. Discrepancy between the theory and the data for the flat resonator points to the imperfections of the studied device. Our experimental approach may be used for precision measurements of crystalline vibrations, the design of quantum memories, and the study of electromechanical contributions to dielectric loss.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Master-slave system with force feedback based on dynamics of virtual model

A master-slave system can extend manipulating and sensing capabilities of a human operator to a remote environment. But the master-slave system has two serious problems: one is the mechanically large impedance of the system; the other is the mechanical complexity of the slave for complex remote tasks. These two problems reduce the efficiency of the system. If the slave has local intelligence, it can help the human operator by using its good points like fast calculation and large memory. The authors suggest that the slave is a dextrous hand with many degrees of freedom able to manipulate an object of known shape. It is further suggested that the dimensions of the remote work space be shared by the human operator and the slave. The effect of the large impedance of the system can be reduced in a virtual model, a physical model constructed in a computer with physical parameters as if it were in the real world. A method to determine the damping parameter dynamically for the virtual model is proposed. Experimental results show that this virtual model is better than the virtual model with fixed damping.

Nojima, Shuji↗

A PIPS + SrI 2 (Eu) detector for atmospheric radioxenon monitoring

The PIPS–SrI 2 (Eu) is a prototype atmospheric radioxenon detection system designed at Oregon State University in support of international efforts towards monitoring clandestine nuclear weapon testing activities. This detector aims to address some shortcomings found in currently deployed beta–gamma atmospheric radioxenon detection systems, such as lackluster energy resolution and memory effect, by employing modern detection materials and readout. The system uses a PIPSBox, a silicon-based gas cell, for electron detection, and a pair of ultrabright, D-shaped SrI 2 (Eu) scintillators coupled to silicon photomultipliers for photon detection. A custom eight-channel digital pulse processor equipped with a field programmable gate-array (FPGA) identifies electron–photon coincidences between the volumes in near real-time. Gas samples of the four radioxenon isotopes of interest were independently measured with the PIPS–SrI 2 (Eu) detection system to determine energy resolution and efficiency. Application of FPGA-based coincidence discrimination in near real-time reduced the ambient background count rate by 95.85 ± 0.04%. Using parameters from the Xenon International gas processing unit and assuming a blank sample and zero memory effect the minimum detectable concentrations (MDCs) for the isotopes were calculated to be 0.12 ± 0.03, 0.27 ± 0.05, 0.15 ± 0.02, and 1.00 ± 0.08 mBq/m 3 air for 131m Xe, 133 Xe, 133m Xe, and 135 Xe, respectively. These MDC estimates compare well with other radioxenon detection systems employed in the International Monitoring System (IMS) and indicate that the PIPS–SrI 2 (Eu) is in compliance with the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO) sensitivity requirement of ≤ 1 mBq/m 3 for 133 Xe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Neurocognitive and physical functioning in the Seveso Women's Health Study

Highlights: • Little research exists on the neurotoxic effects of dioxins in older women. • TCDD was associated with grip strength but not other measures of physical function. • TCDD exposure was not adversely associated with working memory. • This relationship was not modified by menopause nor timing of TCDD exposure around menarche. • TCDD susceptibility may increase as the women age, warranting further research. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is neurotoxic in animals but few studies have investigated its effects on the human brain. Related dioxin-like compounds have been linked to poorer cognitive and motor function in older adults, with effects more pronounced in women, perhaps due to the loss of neuro-protective estrogen in menopause. On 10 July 1976, a chemical explosion in Seveso, Italy, resulted in one of the highest known residential exposures to TCDD. In 1996, we initiated the Seveso Women's Health Study, a retrospective cohort study of the health of the women who were newborn to 40 years old in 1976. Here, we investigate whether TCDD exposure is associated with physical functioning and working memory more than 20 years later. Individual TCDD concentration (ppt) was measured in archived serum collected soon after the explosion. In 1996 and 2008, we measured physical functioning (n=154) and working memory (n=459), respectively. We examined associations between serum TCDD and motor and cognitive outcomes with multivariate linear regression and semi-parametric estimators. A 10-fold increase in serum TCDD was not associated with walking speed (adjusted β=0.0006 ft/s, 95% Confidence Interval (CI): −0.13, 0.13), upper body mobility (adjusted β=−0.06, 95% CI: −0.36, 0.23), or manual dexterity (adjusted β=0.34, 95% CI: −0.65, 1.33). We observed an inverted U-shaped association in grip strength, with poorer strength in the lowest and highest TCDD exposure levels. There was no association between TCDD and the Wechsler digit and spatial span tests. Neither menopause status at assessment nor developmental timing of exposure modified associations between TCDD and working memory. Our findings, in one of the only studies of TCDD's effects on neuropsychological and physical functioning in women, do not indicate an adverse effect on these domains, with the exception of a U-shaped relationship with grip strength. Given the limited assessment and relative youth of the women at this follow-up, future work examining additional neuropsychological outcomes is warranted.

54 ENVIRONMENTAL SCIENCES↗

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗

LLRF System Analysis for the Fermilab PIP-II LINAC

Developing long-lived quantum processing units (QPUs) capable of supporting high-fidelity quantum operations is a crucial challenge on the path toward fault-tolerant quantum computing. TESLA-shaped superconducting RF (SRF) cavities, known for photon relaxation times on the order of seconds, provide an excellent foundation for 3D QPUs and quantum memory. This talk presents a novel design that leverages TESLA cavity modes coupled to ancillary transmon qubits, optimized to preserve coherence and control. By carefully engineering the package geometry, optimizing Hamiltonian parameters, and minimizing lossy participation ratios, we achieve photon relaxation times of over 16 ms and 20 ms for the two cavity modes, representing a significant improvement over previous multimode quantum memories. Despite the reduced coupling between the qubit and cavity modes, which is necessary to preserve long lifetimes, the platform supports robust and universal control schemes that are not limited by low coupling strength. We will also discuss how this architecture can lead to scalable, modular quantum computing systems.

Varghese, P. [Fermilab]↗

ATS-6 - Radio Beacon Experiment: The first years

The Radio Beacon Experiment aboard Applications Technology Satellite-6 (ATS-6) is designed to measure the total electron content and the ionospheric electron content between the satellite and ground. The spaceborne beacon transmits signals on frequencies of 40, 140, and 360 MHz with amplitude modulations of 1 MHz and/or 0.1 MHz for the measurement of modulation phase, Faraday rotation, and amplitude. The modulation phase delays are calibrated in the satellite and in the ground equipment, and the polarization of the emitted signals are predetermined by standard antenna range techniques. The design of the ATS-6 receiver in Boulder, Colorado, is discussed. The antennae are of the short backfire type described by Ehrenspeck (1967), with nominal gains of 13, 19, and 22 dB at 40, 140, and 360 MHz, respectively. Data recording and overall supervision of the receiver is carried out by a 16-bit minicomputer with 8 k of memory. Overall performance of the system is satisfactory. Sample data on the monthly median hourly values of the total electron content, plasmospheric content, and shape factor show distinct seasonal and diurnal variations.

Davies, K.↗

Flexible structure control laboratory development and technology demonstration

An experimental structure is described which was constructed to demonstrate and validate recent emerging technologies in the active control and identification of large flexible space structures. The configuration consists of a large, 20 foot diameter antenna-like flexible structure in the horizontal plane with a gimballed central hub, a flexible feed-boom assembly hanging from the hub, and 12 flexible ribs radiating outward. Fourteen electrodynamic force actuators mounted to the hub and to the individual ribs provide the means to excite the structure and exert control forces. Thirty permanently mounted sensors, including optical encoders and analog induction devices provide measurements of structural response at widely distributed points. An experimental remote optical sensor provides sixteen additional sensing channels. A computer samples the sensors, computes the control updates and sends commands to the actuators in real time, while simultaneously displaying selected outputs on a graphics terminal and saving them in memory. Several control experiments were conducted thus far and are documented. These include implementation of distributed parameter system control, model reference adaptive control, and static shape control. These experiments have demonstrated the successful implementation of state-of-the-art control approaches using actual hardware.

Vivian, H. C.↗

SEU hardened memory cells for a CCSDS Reed-Solomon encoder

A design technique to harden CMOS memory circuits against single event upset (SEU) in the space environment is reported. The design technique provides a recovery mechanism which is independent of the shape of the upsetting event. A RAM cell and flip-flop design are presented to demonstrate the method. The flip-flop was used in the control circuitry for a Reed-Solomon encoder designed for the Space Station and Explorer platforms.

Whitaker, Sterling↗

Methodology for sensitivity analysis, approximate analysis, and design optimization in CFD for multidisciplinary applications

The straightforward automatic-differentiation and the hand-differentiated incremental iterative methods are interwoven to produce a hybrid scheme that captures some of the strengths of each strategy. With this compromise, discrete aerodynamic sensitivity derivatives are calculated with the efficient incremental iterative solution algorithm of the original flow code. Moreover, the principal advantage of automatic differentiation is retained (i.e., all complicated source code for the derivative calculations is constructed quickly with accuracy). The basic equations for second-order sensitivity derivatives are presented; four methods are compared. Each scheme requires that large systems are solved first for the first-order derivatives and, in all but one method, for the first-order adjoint variables. Of these latter three schemes, two require no solutions of large systems thereafter. For the other two for which additional systems are solved, the equations and solution procedures are analogous to those for the first order derivatives. From a practical viewpoint, implementation of the second-order methods is feasible only with software tools such as automatic differentiation, because of the extreme complexity and large number of terms. First- and second-order sensitivities are calculated accurately for two airfoil problems, including a turbulent flow example; both geometric-shape and flow-condition design variables are considered. Several methods are tested; results are compared on the basis of accuracy, computational time, and computer memory. For first-order derivatives, the hybrid incremental iterative scheme obtained with automatic differentiation is competitive with the best hand-differentiated method; for six independent variables, it is at least two to four times faster than central finite differences and requires only 60 percent more memory than the original code; the performance is expected to improve further in the future.

Taylor, Arthur C., III↗

A Flexible-blocking Based Approach for Performance Tuning of Matrix Multiplication Routines for Large Matrices with Edge Cases

Efficient and scalable matrix operations are being highly demanding in the recent era of Machine Learning, Deep Learning, and Big Data Analytics. The two commonly used matrix-matrix operations in the Basic Linear Algebra Subprograms (BLAS) specification are General Matrix-Matrix multiplication (GEMM) and Symmetric Rank-k update (SYRK). The SYRK routine is a specialization of the GEMM routine, where half of the multiplications are skipped as the resultant matrix is known to be symmetric. Fortunately, several linear algebra libraries implement these BLAS routines quite efficiently. The libraries usually partition the input matrices into blocks and place them in processor caches, thus improving performance by leveraging the caches. However, the contemporary libraries are highly optimized for squarish matrices, but the performance degrades significantly for the matrices with edge case (strictly thin or strictly fat shapes) in the multicore machine. The primary reason is that the current state-of-the-art libraries make fixed block shapes based on a processor architecture, and do not consider the shape of the input matrices. In this paper, we propose a new blocking approach, we name it Flexible-blocking, to mitigate the scalability issues. In contrast to the contemporary libraries, our approach formulates the blocks of the input matrices based on the shapes of the matrices as well as the number of threads used in the implementation. Our proposed technique shows noticeable performance improvement on multicore shared-memory machines for the edge case matrices.

Hossain, Md Mosharaf↗

An image compression algorithm for a high-resolution digital still camera

The Electronic Still Camera (ESC) project will provide for the capture and transmission of high-quality images without the use of film. The image quality will be superior to video and will approach the quality of 35mm film. The camera, which will have the same general shape and handling as a 35mm camera, will be able to send images to earth in near real-time. Images will be stored in computer memory (RAM) in removable cartridges readable by a computer. To save storage space, the image will be compressed and reconstructed at the time of viewing. Both lossless and loss-y image compression algorithms are studied, described, and compared.

Nerheim, Rosalee↗

Proximity Portability and in Transit , M-to-N Data Partitioning and Movement in SENSEI [Book Chapter]

In high-performance parallel in situ processing, the term in transit processing refers to those configurations where data must move from a producer to a consumer that runs on separate resources. In the context of parallel and distributed computing on an HPC platform one of the central challenges is to determine a mapping of data from producer ranks to consumer ranks. This problem is complicated by the heterogeneity that arises in producer-consumer pairs, such as when producer and consumer codes have different levels of concurrency, different scaling characteristics, or different data models. The resulting mapping and movement of data from M producer to N consumer ranks can have a significant impact on aggregate application performance, particularly when the data consumer requires only a subset of the overall data for its task. This chapter focuses on the design considerations that underlie SENSEI’s implementation to this challenging problem. These design considerations extend the core SENSEI architecture and include ideas like the need to accommodate flexibility in the choice of different partitioning methods, the ability for a data consumer to request and receive only the subset of data needed for its particular operation, and the ability to leverage any of several different data transport tools. The idea of proximity portability, being able to use different data transport methods as part of an in transit workflow, is illustrated through the use of three different transport layers where switching from one transport tool to another is accomplished with only a configuration file change. Here, the chapter also includes a performance analysis summary showing the performance gains that are possible in terms of multiple metrics, such as memory footprint, time to solution, and amount of data moved, when using optimized partitioners in an in transit setting, gains that are made possible by the implementation shaped by specific design considerations.

Bethel, E. Wes↗

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗

Frequency scanning capaciflector for capacitively determining the material properties

A capaciflector sensor system scanned in frequency is used to detect the permittivity of the material of an object being sensed. A capaciflector sensor element, coupled to current-measuring voltage follower circuitry, is driven by a frequency swept oscillator and generates an output which corresponds to capacity as a function of the input frequency. This swept frequency information is fed into apparatus e.g. a digital computer for comparing the shape of the capacitance vs. frequency curve against characteristic capacitor vs. frequency curves for a variety of different materials which are stored, for example, in a digital memory of the computer or a database. Using a technique of pattern matching, a determination is made as to the identification of the material. Also, when desirable, the distance between the sensor and the object can be determined.

Campbell, Charles E.↗

Critical current oscillations of elliptical Josephson junctions with single-domain ferromagnetic layers

We report that josephson junctions containing ferromagnetic layers are of considerable interest for the development of practical cryogenic memory and superconducting qubits. Such junctions exhibit a ground-state phase shift of π for certain ranges of ferromagnetic layer thicknesses. We present studies of Nb based micron-scale elliptically shaped Josephson junctions containing ferromagnetic barriers of Ni 81 Fe 19 or Ni 65 Fe 15 Co 20 . By applying an external magnetic field, the critical current of the junctions is found to follow characteristic Fraunhofer patterns and display sharp switching behavior suggestive of single-domain magnets. The high quality of the Fraunhofer patterns enables us to extract the maximum value of the critical current even when the peak is shifted significantly outside the range of the data due to the magnetic moment of the ferromagnetic layer. The maximum value of the critical current oscillates as a function of the ferromagnetic barrier thickness, indicating transitions in the phase difference across the junction between values of zero and π. Lastly, we compare the data to previous work and to models of the 0-π transitions based on existing theories.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Aerodynamic Shape Optimization of Supersonic Aircraft Configurations via an Adjoint Formulation on Parallel Computers

This work describes the application of a control theory-based aerodynamic shape optimization method to the problem of supersonic aircraft design. The design process is greatly accelerated through the use of both control theory and a parallel implementation on distributed memory computers. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is then implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) Standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on higher order computational fluid dynamics methods (CFD). In our earlier studies, the serial implementation of this design method was shown to be effective for the optimization of airfoils, wings, wing-bodies, and complex aircraft configurations using both the potential equation and the Euler equations. In our most recent paper, the Euler method was extended to treat complete aircraft configurations via a new multiblock implementation. Furthermore, during the same conference, we also presented preliminary results demonstrating that this basic methodology could be ported to distributed memory parallel computing architectures. In this paper, our concern will be to demonstrate that the combined power of these new technologies can be used routinely in an industrial design environment by applying it to the case study of the design of typical supersonic transport configurations. A particular difficulty of this test case is posed by the propulsion/airframe integration.

Reuther, James↗