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At least 1,765 records · Page 98

Separate visual representations for perception and for visually guided behavior

Converging evidence from several sources indicates that two distinct representations of visual space mediate perception and visually guided behavior, respectively. The two maps of visual space follow different rules; spatial values in either one can be biased without affecting the other. Ordinarily the two maps give equivalent responses because both are veridically in register with the world; special techniques are required to pull them apart. One such technique is saccadic suppression: small target displacements during saccadic eye movements are not preceived, though the displacements can change eye movements or pointing to the target. A second way to separate cognitive and motor-oriented maps is with induced motion: a slowly moving frame will make a fixed target appear to drift in the opposite direction, while motor behavior toward the target is unchanged. The same result occurs with stroboscopic induced motion, where the frame jump abruptly and the target seems to jump in the opposite direction. A third method of separating cognitive and motor maps, requiring no motion of target, background or eye, is the Roelofs effect: a target surrounded by an off-center rectangular frame will appear to be off-center in the direction opposite the frame. Again the effect influences perception, but in half of the subjects it does not influence pointing to the target. This experience also reveals more characteristics of the maps and their interactions with one another, the motor map apparently has little or no memory, and must be fed from the biased cognitive map if an enforced delay occurs between stimulus presentation and motor response. In designing spatial displays, the results mean that what you see isn't necessarily what you get. Displays must be designed with either perception or visually guided behavior in mind.

Bridgeman, Bruce↗

Real Time Phase Noise Meter Based on a Digital Signal Processor

A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

phase noise↗

Towards developing a compact model for magnetization switching in straintronics magnetic random access memory devices

Strain-mediated magnetization switching in a magnetic tunneling junction (MTJ) by exploiting a combination of piezoelectricity and magnetostriction has been proposed as an energy efficient alternative to spin transfer torque (STT) and field induced magnetization switching methods in MTJ-based magnetic random access memories (MRAM). Theoretical studies have shown the inherent advantages of strain-assisted switching, and the dynamic response of the magnetization has been modeled using the Landau-Lifshitz-Gilbert (LLG) equation. However, an attempt to use LLG for simulating dynamics of individual elements in large-scale simulations of multi-megabyte straintronics MRAM leads to extremely time-consuming calculations. Hence, a compact analytical solution, predicting the flipping delay of the magnetization vector in the nanomagnet under stress, combined with a liberal approximation of the LLG dynamics in the straintronics MTJ, can lead to a simplified model of the device suited for fast large-scale simulations of multi-megabyte straintronics MRAMs. In this work, a tensor-based approach is developed to study the dynamic behavior of the stressed nanomagnet. First, using the developed method, the effect of stress on the switching behavior of the magnetization is investigated to realize the margins between the underdamped and overdamped regimes. The latter helps the designer realize the oscillatory behavior of the magnetization when settling along the minor axis, and the dependency of oscillations on the stress level and the damping factor. Next, a theoretical model to predict the flipping delay of the magnetization vector is developed and tested against LLG-based numerical simulations to confirm the accuracy of findings. Lastly, the obtained delay is incorporated into the approximate solutions of the LLG dynamics, in order to create a compact model to liberally and quickly simulate the magnetization dynamics of the MTJ under stress. Using the developed delay equation, the efficiency of the straintronics switching over the STT method is highlighted by analytically investigating the energy-delay trade-off of both methodologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Polyakov model in ’t Hooft flux background: a quantum mechanical reduction with memory

We construct a compactification of Polyakov model on T 2 × $\mathbb{R}$ down to quantum mechanics which remembers non-perturbative aspects of field theory even at an arbitrarily small area. Standard compactification on small T 2 × $\mathbb{R}$ possesses a unique perturbative vacuum (zero magnetic flux state), separated parametrically from higher flux states, and the instanton effects do not survive in the Born-Oppenheimer approximation. By turning on a background magnetic GNO flux in co-weight lattice corresponding to a non-zero ’t Hooft flux, we show that N-degenerate vacua appear at small torus, and there are N - 1 types of flux changing instantons between them. We construct QM instantons starting with QFT instantons using the method of replicas. For example, SU(2) gauge theory with flux reduces to the double-well potential where each well is a fractional flux state. Despite the absence of a mixed anomaly, the vacuum structure of QFT and the one of QM are continuously connected. We also compare the quantum mechanical reduction of the Polyakov model with the deformed Yang-Mills, by coupling both theories to TQFTs. In particular, we compare the mass spectrum for dual photons and energy spectrum in the QM limit. We give a detailed description of critical points at infinity in the semi-classical expansion, and their role in resurgence structure.

nonperturbative effects↗

Effects of ISI and satellite channel nonlinearity on Viterbi demodulation/decoding

It is shown that, for convolutionally coded transmission over bandwidth-constrained channels, a mere reversal of the switching direction at the encoder output produces a change in the system bit error probability performance. This change is significant when the Viterbi demodulator/decoder is matched to the total channel memory and is more significant for linear channels than for nonlinear ones. The reversal of switching direction is a simple demonstration of the fact that the well-known optimum codes for the linear AGWN channel are no longer necessarily optimum for a bandwidth-constrained channel with or without the addition of channel nonlinearity. It is concluded that potentially significant performance improvement can be obtained by matching the encoder (through the appropriate choice of tap weights and modulo-2 summers) to the channel in addition to matching the demodulator/decoder to the channel for a given encoder.

Divsalar, D.↗

Spin-orbit torque magnetization switching of a three-terminal perpendicular magnetic tunnel junction

We report on the current-induced magnetization switching of a three-terminal perpendicular magnetic tunnel junction by spin-orbit torque and its read-out using the tunnelling magnetoresistance (TMR) effect. The device is composed of a perpendicular Ta/FeCoB/MgO/FeCoB stack on top of a Ta current line. The magnetization of the bottom FeCoB layer can be switched reproducibly by the injection of current pulses with density 5 × 10{sup 11} A/m{sup 2} in the Ta layer in the presence of an in-plane bias magnetic field, leading to the full-scale change of the TMR signal. Our work demonstrates the proof of concept of a perpendicular spin-orbit torque magnetic memory cell.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Conceptualizing impact assessment as a learning process

This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values. Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.

54 ENVIRONMENTAL SCIENCES↗

Unified computational model of transport in metal-insulating oxide-metal systems

In this paper, a unified physics-based model of electron transport in metal-insulator-metal (MIM) systems is presented. In this model, transport through metal-oxide interfaces occurs by electron tunneling between the metal electrodes and oxide defect states. Transport in the oxide bulk is dominated by hopping, modeled as a series of tunneling events that alter the electron occupancy of defect states. Electron transport in the oxide conduction band is treated by the drift–diffusion formalism and defect chemistry reactions link all the various transport mechanisms. It is shown that the current-limiting effect of the interface band offsets is a function of the defect vacancy concentration. These results provide insight into the underlying physical mechanisms of leakage currents in oxide-based capacitors and steady-state electron transport in resistive random access memory (ReRAM) MIM devices. An explanation of ReRAM bipolar switching behavior based on these results is proposed.

36 MATERIALS SCIENCE↗

A comparison of machine learning surrogate models of street-scale flooding in Norfolk, Virginia

Low-lying coastal cities, exemplified by Norfolk, Virginia, face the challenge of street flooding caused by rainfall and tides, which strain transportation and sewer systems and can lead to personal and property damage. While high-fidelity, physics-based simulations provide accurate predictions of urban pluvial flooding, their computational complexity renders them unsuitable for real-time applications. Using data from Norfolk rainfall events between 2016 and 2018, this study compares the performance of a previous surrogate model based on a random forest algorithm with two deep learning models: Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The comparison of deep learning to the random forest algorithm is motivated by the desire to utilize a machine learning architecture that allows for the future inclusion of common uncertainty quantification techniques and the effective integration of relevant, multi-modal features.

54 ENVIRONMENTAL SCIENCES↗

POLARIZED LINE FORMATION IN MOVING ATMOSPHERES WITH PARTIAL FREQUENCY REDISTRIBUTION AND A WEAK MAGNETIC FIELD

The dynamical state of the solar and stellar atmospheres depends on the macroscopic velocity fields prevailing within them. The presence of such velocity fields in the line formation regions strongly affects the polarized radiation field emerging from these atmospheres. Thus it becomes necessary to solve the radiative transfer equation for polarized lines in moving atmospheres. Solutions based on the “observer’s frame method” are computationally expensive to obtain, especially when partial frequency redistribution (PRD) in line scattering and large-amplitude velocity fields are taken into account. In this paper we present an efficient alternative method of solution, namely, the comoving frame technique, to solve the polarized PRD line formation problems in the presence of velocity fields. We consider one-dimensional planar isothermal atmospheres with vertical velocity fields. We present a study of the effect of velocity fields on the emergent linear polarization profiles formed in optically thick moving atmospheres. We show that the comoving frame method is far superior when compared to the observer’s frame method in terms of the computational speed and memory requirements.

79 ASTRONOMY AND ASTROPHYSICS↗

Colloquium : Physical properties of group-IV monochalcogenide monolayers

The state-of-the-art knowledge of ferroelectric and ferroelastic group-IV monochalcogenide monolayers is surveyed. These semiconductors feature remarkable structural and mechanical properties, such as a switchable in-plane spontaneous polarization, soft elastic constants, structural degeneracies, and thermally driven two-dimensional structural transformations. Additionally, these 2D materials display selective valley excitations, valley Hall effects, and persistent spin helix behavior. After a description of their Raman spectra, a discussion of optical properties arising from their lack of centrosymmetry (such as an unusually strong second-harmonic intensity, large bulk photovoltaic effects, photostriction, and tunable exciton binding energies) is provided as well. Here, the physical properties observed in these materials originate from (correlate with) their intrinsic and switchable electric polarization, and the physical behavior hereby reviewed could be of use in nonvolatile memory, valleytronic, spintronic, and optoelectronic devices: these 2D multiferroics enrich and diversify the 2D material toolbox.

2D ferroelectrics↗

Lattice Quantum Chromodynamics with Overlap Fermions on GPUs

Lattice quantum chromodynamics (QCD) calculations were one of the first applications to demonstrate the potential of GPUs in the area of high-performance computing; the nature of lattice QCD calculations matches well with the GPU's computational model. This article discusses ways to effectively use GPUs for lattice calculations using the overlap operator, a discretization that preserves chiral symmetry even at nonzero lattice spacing and makes possible lattice QCD simulations in the parameter region relevant to nuclear physics. The author shows that the large memory footprint of these codes requires the use of multiple GPUs in parallel and discusses methods for implementing this operator efficiently: hybrid CPU/GPU memory use for eigensolvers and MPI/OpenMP/CUDA parallelization strategies required to take full advantage of both GPU and CPU resources. He then compares the performance of codes on a GPU cluster and a CPU cluster with similar interconnects, discussing the strong scaling for problem sizes relevant to current lattice QCD simulations.

Computer Science↗

Exploring the Adoption Challenges of Post-Quantum Cryptography in EV Charging Infrastructure

The rapid evolution of electric vehicle (EV) technology and the corresponding growth of the Electric Vehicle Charging Infrastructure (EVCI) brings to light significant cybersecurity concerns, notably in the context of emerging post-quantum computing capabilities. This report, prepared by Pacific Northwest National Laboratory (PNNL) under the U.S. Department of Energy contract, delves into the challenges associated with integrating Post-Quantum Cryptography (PQC) into EVCI to safeguard against potential quantum computing threats. Post-quantum computers will eventually be able to invalidate technologies secured through public key cryptography. As part of this effort, the primary gaps and challenges in the EVCI were investigated with a focus on comparing traditional algorithms against PQC algorithms. One of the notable findings was that the P-521 algorithm was frequently surpassed in performance by PQC algorithms. This document provides a thorough examination of the hurdles the industry can expect when transitioning to PQC within the EVCI, such as interoperability concerns, the computational and memory demands of PQC algorithms, and the organizational readiness for such a transition. It emphasizes the necessity of a forward-thinking approach to cybersecurity, advocating for early and strategic engagement among EVCI stakeholders to ensure a seamless and cost-effective migration to quantum-resistant cryptographic standards. Through this report, the authors aim to catalyze awareness and action among policymakers, industry leaders, and cybersecurity professionals towards fortifying the EVCI against emerging quantum threats, thereby securing the infrastructure essential for the future of electric mobility.

33 ADVANCED PROPULSION SYSTEMS↗

Unitary Qubit Lattice Algorithms for Plasma Physics

This final technical report summarizes research conducted under DOE Award DE-SC0021653 to develop unitary Quantum Lattice Algorithms for modeling electromagnetic wave propagation and scattering in complex media, including plasmas. The project developed and validated quantum-inspired formulations of Maxwell's equations that preserve unitary evolution and can be evaluated on classical high-performance computing systems while providing a foundation for future quantum-computing implementations. Major accomplishments include the development of two- and three-dimensional algorithms for electromagnetic scattering; scalable, distributed-memory implementations demonstrated on the Perlmutter supercomputer; formulations for nonlinear lossless fluid dynamics and cold, lossless, inhomogeneous magnetized plasmas; and an explicit quantum algorithm for a time-discretized Lorenz model. Simulations reproduced a range of characteristic wave phenomena, including transient effects that are not readily apparent in conventional frequency-domain studies, demonstrating the effectiveness of the proposed approach for modeling complex electromagnetic and plasma systems. The work establishes a unified theoretical and computational framework for quantum and quantum-inspired simulation and provides a foundation for future implementation on fault-tolerant quantum systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reconfigurable modular computer networks for spacecraft on-board processing

The core electronics subsystems on unmanned spacecraft, which have been sent over the last 20 years to investigate the moon, Mars, Venus, and Mercury, have progressed through an evolution from simple fixed controllers and analog computers in the 1960's to general-purpose digital computers in current designs. This evolution is now moving in the direction of distributed computer networks. Current Voyager spacecraft already use three on-board computers. One is used to store commands and provide overall spacecraft management. Another is used for instrument control and telemetry collection, and the third computer is used for attitude control and scientific instrument pointing. An examination of the control logic in the instruments shows that, for many, it is cost-effective to replace the sequencing logic with a microcomputer. The Unified Data System architecture considered consists of a set of standard microcomputers connected by several redundant buses. A typical self-checking computer module will contain 23 RAMs, two microprocessors, one memory interface, three bus interfaces, and one core building block.

Rennels, D. A.↗

A kinematic model of ridge-transform geometry evolution

A simple kinematic model is used to study the effects of various parameters on the evolution of zero-offset transforms and very-long-offset transforms. Consideration is given to the effects of initial configuration, degree of asymmetry, and degree of bias in asymmetry on the generation of these ridge transform geometries and on the possible steady-state nature of the transform length spectra. Of the parameters tests, only lack of 'memory' of zero-offset transforms affects transform length distribution.

Stoddard, Paul R.↗

Controlling panel flutter using adaptive materials

The effectiveness of using adaptive materials to control panel flutter is examined. Adaptive materials are those whose strain or mechanical properties can be controlled by the application of an external stimulus. Two such material types are piezoelectric (ceramics or polymers) and shape memory alloys. These materials experience controllable strain when subjected to applied voltage and heat, respectively. The present study investigates the use of both material types to modify the flutter characteristics of a simply supported panel in supersonic flow. Piezoelectric materials respond quickly to applied voltages and can be used with feedback control for active vibration suppression. The adaptive process of the shape memory alloy used in this study (geometry and stiffness change) is a relatively low frequency phenomenon; therefore, it is considered for passive (on/off) control schemes only. Nondimensional parameters for these adaptive materials are used with linear panel models, yielding results which allow for a better understanding of their capabilities in controlling aeroelastic responses.

Scott, R. C.↗

Error latency measurements in symbolic architectures

Error latency, the time that elapses between the occurrence of an error and its detection, has a significant effect on reliability. In computer systems, failure rates can be elevated during a burst of system activity due to increased detection of latent errors. A hybrid monitoring environment is developed to measure the error latency distribution of errors occurring in main memory. The objective of this study is to develop a methodology for gauging the dependability of individual data categories within a real-time application. The hybrid monitoring technique is novel in that it selects and categorizes a specific subset of the available blocks of memory to monitor. The precise times of reads and writes are collected, so no actual faults need be injected. Unlike previous monitoring studies that rely on a periodic sampling approach or on statistical approximation, this new approach permits continuous monitoring of referencing activity and precise measurement of error latency.

Young, L. T.↗