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At least 469 records · Page 26

Massively parallel neurocomputing for aerospace applications

An innovative hybrid, analog-digital charge-domain technology, for the massively parallel VLSI implementation of certain large scale matrix-vector operations, has recently been introduced. It employs arrays of Charge Coupled/Charge Injection Device cells holding an analog matrix of charge, which process digital vectors in parallel by means of binary, non-destructive charge transfer operations. The impact of this technology on massively parallel processing is discussed. Fundamentally new classes of algorithms, specifically designed for this emerging technology, as applied to signal processing, are derived.

Fijany, Amir↗

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a foreground that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about 5% of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about 10 times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a {\it foreground} that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about $5\%$ of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about $10$ times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evidence from Quasi-Periodic Oscillations for a Millisecond Pulsar in the Low Mass X-Ray Binary 4U 0614+091

We have detected quasi-periodic oscillations (QPOs) near 1 kHz from the low mass X-ray binary 4U 0614+091 in observations with RXTE. The observations span several months and sample the source over a large range of X-ray luminosity. In every interval QPOs are present above 400 Hz with fractional RMS amplitudes from 3 to 12% over the full PCA band. At high count rates, two high frequency QPOs are detected simultaneously. The difference of their frequency centroids is consistent with a constant value of 323 Hz in all observations. During one interval a third signal is detected at 328 +/- 2 Hz. This suggests the system has a stable 'clock' which is most likely the neutron star with spin period 3.1 msec. Thus, our observations of 4U 0614+091 and those of 4U 1728-34 provide the first evidence for millisecond pulsars within low-mass X-ray binary systems and reveal the 'missing-link' between millisecond radiopulsars and the late stages of binary evolution in low mass X-ray binaries. The constant difference of the high frequency QPOs sug,,ests a beat-frequency interpretation. In this model, the high frequency QPO is associated with the Keplerian frequency of the inner accretion disk and the lower frequency QPO is a 'beat' between the differential rotation frequency of the inner disk and the spinning neutron star. Assuming the high frequency QPO is a Keplerian orbital frequency for the accretion disk, we find a maximum mass of 1.9 solar mass and a maximum radius of 17 km for the neutron star.

Ford, E.↗

Magnetically driven coupling in relativistic radiation-mediated shocks

ABSTRACT The radiation drag in photon-rich environments of cosmic explosions can seed kinetic instabilities by inducing velocity spreads between relativistically streaming plasma components. Such microturbulence is likely imprinted on the breakout signals of radiation-mediated shocks. However, large-scale, transverse magnetic fields in the deceleration region of the shock transition can suppress the dominant kinetic instabilities by preventing the development of velocity separations between electron–positron pairs and a heavy ion species. We use a 1D five-fluid radiative transfer code to generate self-consistent profiles of the radiation drag force and plasma composition in the deceleration region. For increasing magnetization, our models predict rapidly growing pair multiplicities and a substantial radiative drag developing self-similarly throughout the deceleration region. We extract the critical magnetization parameter σc, determining the limiting magnetic field strength at which a three-species plasma can develop kinetic instabilities before reaching the isotropized downstream. For a relativistic, single ion plasma drifting with γu = 10 in the upstream of a relativistic radiation-mediated shock, we find the threshold σc ≈ 10−7 for the onset of microturbulence. Suppression of plasma instabilities in the case of multi-ion composition would likely require much higher values of σc. Identifying high-energy signatures of microturbulence in shock breakout signals and combining them with the magnetization limits provided in this work will allow a deeper understanding of the magnetic environment of cosmic explosions like supernovae, gamma-ray bursts, and neutron star binary mergers.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectrum-Sharing Scheme For Two BPSK Systems

Scheme proposed to enable two binary-phase-shift-keyed (BPSK) radio-communication systems to operate simultaneously in same frequency band. Estimate of interference spectrum generated in one of interference cancelers and subtracted from total spectrum of received signal + noise to obtain interference-free spectrum.

Gutierrez-Luaces, Benito O.↗

Seeking Counterparts to Advanced LIGO/Virgo Transients with Swift

Binary neutron star (NS) mergers are among the most promising astrophysical sources of gravitational wave emission for Advanced LIGO and Advanced Virgo, expected to be operational in 2015 . Finding electromagnetic counterparts to these signals will be essential to placing them in an astronomical context. The Swift satellite carries a sensitive X-ray telescope (XRT), and can respond to target-of-opportunity requests within 1-2 hours, and so is uniquely poised to find the X-ray counterparts to LIGO / Virgo triggers. Assuming NS mergers are the progenitors of short gamma-ray bursts (GRBs), some percentage of LIGO/Virgo triggers will be accompanied by X-ray band afterglows that are brighter than 10(exp -12) ergs/s/sq cm in the XRT band one day after the trigger time. We find that a soft X-ray transient of this flux is bright enough to be extremely rare, and so could be confidently associated with even a moderately localized GW signal. We examine two possible search strategies with the Swift XRT to find bright transients in LIGO/Virgo error boxes. In the first strategy, XRT could search a volume of space with a approx.100 Mpc radius by observing approx 30 galaxies over the course of a day, with sufficient depth to observe the expected X-ray afterglow. For an extended LIGO / Virgo horizon distance, the XRT could employ very short 100 s exposures to cover an area of approx 35 square degrees in about a day, and still be sensitive enough to image GW discovered GRB afterglows. These strategies demonstrate that the high X-ray luminosity of short GRBs and the relatively low X-ray transient background combine to make high confidence discoveries of X-ray band counterparts to GW triggers possible, though challenging, with current satellite facilities.

Kanner, Jonah↗

Lightweight Embedded Controller in Advanced FPGA SoC for Radar Signal Processing [Poster]

The objective of the project is to demonstrate that critical control functions can be implemented using little resources in modern microelectronics. A finite state machine (Figure 1) is implemented onto a field programmable gate array (FPGA). The functionality of the system is demonstrated by sending binary instructions to the controller. The controller transmits patterns through an LED, controls an electromechanical device, and uses pulse-width modulation (PWM) for radar functions.

42 ENGINEERING↗

Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults

Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and inform manual maneuver decisions. Our multi-modal display of this information provides speech output to issue control surface failure warnings to a lesser-used communication channel and provides graphical displays with pilot-selectable !eve!s of details to issues additional information about the failure. We also describe a potential presentation for flight envelope reduction that can be viewed separately or integrated with an existing attitude indicator instrument. Preliminary results suggest that the inductive approach is capable of detecting that a control surface has failed and determining the type of fault. Furthermore, preliminary evaluations suggest that the interface discloses a concise summary of this information to the pilot.

Spikovska, Lilly↗

Performance of a near-optimum receiver for optical antipodal signals

The well known photon-counting, heterodyning and homodyning optical receivers (operating over a free-space channel) do not achieve the performance of the optimum quantum receiver, which attains significantly lower error-probabilities than the above receiver structures. A demonstration and analysis are given of a binary antipodal optical receiver that exponentially approaches the performance of the optimum quantum receiver. A general mathematical model is developed, and subsequently used to evaluate the effects of external interference and internal error-sources on receiver performance.

Vilnrotter, V. A.↗

INITIAL STUDIES OF CAVITY FAULT PREDICTION AT JEFFERSON LABORATORY

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Vidyaratne, Lasitha↗

INITIAL STUDIES OF CAVITY FAULT PREDICTION AT JEFFERSON LABORATORY

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data

Vidyaratne, Lasitha↗

Thermal Effects in Binary Neutron Star Mergers

Abstract We study the impact of finite-temperature effects in numerical-relativity simulations of binary neutron star mergers with microphysical equations of state and neutrino transport in which we vary the effective nucleon masses in a controlled way. We find that, as the specific heat is increased, the merger remnants become colder and more compact due to the reduced thermal pressure support. Using a full Bayesian analysis, we demonstrate that this effect will be measurable in the postmerger gravitational wave signal with next-generation observatories at signal-to-noise ratios of 15.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Simulating Neutron Stars with Solid Quark Cores: Rotations, Oscillations, and Binary Mergers [Slides]

Neutron stars feature complexity from GR, QM, particle physics and nuclear physics effects which cannot be investigated in the lab up to the densities in their core. GWs from binary neutron star mergers are on the rise to provide more insight into the physics inside NSs. There is a possibility that involves crystalline, color-superconducting quark matter, with implications towards altering the GW signal if NSs harbor this exotic matter. There are no 3D dynamical simulations of solid quark matter inside Neutron stars. We perform the first 3D dynamical simulations of solid quark matter inside NSs. These are performed in the Newtonian Approximation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Photon counting and Laguerre detection.

In this correspondence maximum-likelihood binary detection theory is applied to an incoherent optical system model employing photodetectors governed by Laguerre counting statistics. It is shown that a maximum-likelihood Laguerre detector corresponds to a count comparison over each signaling interval. Laguerre error probabilities are presented and compared with those for Poisson counting.

Gagliardi, R. M.↗

Fault tolerance in space-based digital signal processing and switching systems: Protecting up-link processing resources, demultiplexer, demodulator, and decoder

Fault tolerance features in the first three major subsystems appearing in the next generation of communications satellites are described. These satellites will contain extensive but efficient high-speed processing and switching capabilities to support the low signal strengths associated with very small aperture terminals. The terminals' numerous data channels are combined through frequency division multiplexing (FDM) on the up-links and are protected individually by forward error-correcting (FEC) binary convolutional codes. The front-end processing resources, demultiplexer, demodulators, and FEC decoders extract all data channels which are then switched individually, multiplexed, and remodulated before retransmission to earth terminals through narrow beam spot antennas. Algorithm based fault tolerance (ABFT) techniques, which relate real number parity values with data flows and operations, are used to protect the data processing operations. The additional checking features utilize resources that can be substituted for normal processing elements when resource reconfiguration is required to replace a failed unit.

Redinbo, Robert↗

A generalization of binary minimum shift keying and staggered quadriphase shift keying modulation

A generalized modulation scheme, which includes minimum shift keying (MSK) and staggered quadriphase shift keying (SQPSK) as special cases, is analyzed. The general modulator is realized as a one-input, two-output sequence transducer whose outputs select the carrier signal for each band. This form of the modulator has the practical advantage of not requiring any RF filtering since there is no actual mixing of the carriers with the modulating signals. It is shown that the optimum demodulator (whether hard-decision or soft-decision) always can make its decisions from the received waveform over two bands when the interference is additive white Gaussian noise, thus generalizing a well-known result for hard decision demodulation of MSK and SQPSK signals. The power spectra of MSK and SQPSK signals are derived to isolate the role played by coherency between the modulating signals and the carriers.

Massey, J. L.↗

Optimizing Optical Searches for Supermassive Black Hole Binaries in Active Galactic Nuclei Light Curves: Fourier versus Bayesian Periodicity Detection

Simulations predict that supermassive black hole binaries (SMBHBs) will exhibit periodic brightness variations that may exceed the stochastic variability intrinsic to active galactic nuclei (AGN). In this paper, we simulate SMBHBs with damped random walk (DRW) AGN variability and an added sinusoidal signal from the orbital motion, and test three methods—a generalized Lomb–Scargle periodogram (GLSP), a nested Bayesian sampler (NBS), and a weighted wavelet z-transform (or WWZ)—to determine which is best at recovering the periodicity. Our simulated light curves follow the properties of the Catalina Real-Time Transient Survey (or CRTS), Legacy Survey of Space and Time (LSST), and Zwicky Transient Facility (ZTF) to best inform current and future SMBHB searches. We map a broad range of parameter space and identify which DRW-only light curves best mimic periodicity and pass each method’s model selection. The NBS performs best at detecting periodicity and filtering out DRW-only light curves. Combined candidate selection with both the NBS and GLSP significantly reduces false-positive rates (FPRs) with marginal impact on true-positive rates (TPRs). With this joint model selection pipeline, we find the lowest FPRs in ZTF-like simulations and the highest detection rates in LSST-like simulations. Using a modified computation of the false-alarm probability with GLSP, we efficiently triage LSST AGN light curves (∼10 7 light curves in ∼10–30 hr) and achieve TPRs and FPRs of ∼40% and ∼0.5%, respectively.

Banaszak, Sebastian M. [Vanderbilt Univ., Nashvill↗