High Resolution Flicker-Noise-Free Frequency Measurements of Weak Microwave Signals

Amplification is usually necessary when measuring the frequency instability of microwave signals. In this work, we develop a flicker noise free frequency measurement system based on a common or shared amplifier. First, we show that correlated flicker phase noise can be cancelled in such a system. Then we compare the new system with the conventional by simultaneously measuring the beat frequency from two cryogenic sapphire oscillators with parts in 10^15 fractional frequency instability. We determine for low power, below -80 dBm, the measurements were not limited by correlated noise processes but by thermal noise of the readout amplifier. In this regime, we show that the new readout system performs as expected and at the same level as the standard system but with only half the number of amplifiers. We also show that, using a standard readout system, the next generation of cryogenic sapphire oscillators could be flicker phase noise limited when instability reaches parts in 10^16 or betterComment: Accepted for publication in IEEE Transactions on Microwave Theory & Technique

Collective learning and optimal consensus decisions in social animal groups.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.This research was supported by a National Science Foundation Graduate Research Fellowship and National Science Foundation Doctoral Dissertation Improvement Grant 1210029 to ABK, a National Sciences and Engineering Research Council of Canada Fellowship to NM, and National Science Foundation Award PHY-0848755 and EAGER Grant IOS-1251585, Office of Naval Research Award N00014-09-1-1074, Army Research Office Grant W911NG-11-1-0385, and Human Frontiers Science Program Award RGP0065/2012 to IDC

Influence of dynamic content on visual attention during video advertisements

Purpose Dynamic advertising, including television and online video ads, demands new theory and tools developed to understand attention to moving stimuli. The purpose of this study is to empirically test the predictions of a new dynamic attention theory, Dynamic Human-Centred Communication Systems Theory, versus the predictions of salience theory. Design/methodology/approach An eye-tracking study used a sample of consumers to measure visual attention to potential areas of interest (AOIs) in a random selection of unfamiliar video ads. An eye-tracking software feature called intelligent bounding boxes (IBBs) was used to track attention to moving AOIs. AOIs were coded for the presence of static salience variables (size, brightness, colour and clutter) and dynamic attention theory dimensions (imminence, motivational relevance, task relevance and stability). Findings Static salience variables contributed 90% of explained variance in fixation and 57% in fixation duration. However, the data further supported the three-way interaction uniquely predicted by dynamic attention theory: between imminence (central vs peripheral), relevance (motivational or task relevant vs not) and stability (fleeting vs stable). The findings of this study indicate that viewers treat dynamic stimuli like real life, paying less attention to central, relevant and stable AOIs, which are available across time and space in the environment and so do not need to be memorised. Research limitations/implications Despite the limitations of small samples of consumers and video ads, the results of this study demonstrate the potential of two relatively recent innovations, which have received limited emphasis in the marketing literature: dynamic attention theory and IBBs. Practical implications This study documents what does and does not attract attention to video advertising. What gets attention according to salience theory (e.g. central location) may not always get attention in dynamic advertising because of the effects of relevance and stability. To better understand how to execute video advertising to direct and retain attention to important AOIs, advertisers and advertising researchers are encouraged to use IBBs. Originality/value This study makes two original contributions: to marketing theory, by showing how dynamic attention theory can predict attention to video advertising better than salience theory, and to marketing research, showing the utility of tracking visual attention to moving objects in video advertising with IBBs, which appear underutilised in advertising research

Colloquium: Comparison of Astrophysical and Terrestrial Frequency Standards

We have re-analyzed the stability of pulse arrival times from pulsars and white dwarfs using several analysis tools for measuring the noise characteristics of sampled time and frequency data. We show that the best terrestrial artificial clocks substantially exceed the performance of astronomical sources as time-keepers in terms of accuracy (as defined by cesium primary frequency standards) and stability. This superiority in stability can be directly demonstrated over time periods up to two years, where there is high quality data for both. Beyond 2 years there is a deficiency of data for clock/clock comparisons and both terrestrial and astronomical clocks show equal performance being equally limited by the quality of the reference timescales used to make the comparisons. Nonetheless, we show that detailed accuracy evaluations of modern terrestrial clocks imply that these new clocks are likely to have a stability better than any astronomical source up to comparison times of at least hundreds of years. This article is intended to provide a correct appreciation of the relative merits of natural and artificial clocks. The use of natural clocks as tests of physics under the most extreme conditions is entirely appropriate; however, the contention that these natural clocks, particularly white dwarfs, can compete as timekeepers against devices constructed by mankind is shown to be doubtful.Comment: 9 pages, 2 figures; presented at the International Frequency Control Symposium, Newport Beach, Calif., June, 2010; presented at Pulsar Conference 2010, October 12th, Sardinia; accepted 13th September 2010 for publication in Reviews of Modern Physic

GNSS Spoof Detection Using Shipboard IMU Measurements

A variety of approaches have been proposed in the literature to detect spooing of Global Navigation Satellite Systems (GNSS). These approaches vary widely based upon the assumed capabilities and a priori knowledge of the spoofer. This paper considers a method to detect spoofing based on comparing the relative (not absolute) platform trajectory estimated by the GNSS receiver to the relative trajectory developed from IMU measurements (specifically pitch and roll from a gyro compass). The primary contribution of this paper is the development and analysis of a GNSS spoofing detection algorithm that exploits the unknown (to the spoofer) “high” frequency pitch/roll motion of the ship as seen by a commercial-off-the-shelf (COTS) receiver and an inertial measurement unit (IMU) that may already be in use onboard ships. We focus on generalized likelihood ratio tests using simple models of the GNSS and gyro measurements. Further, we avoid using a navigation filter, such as the extended Kalman filter, on the measurements; instead, the algorithm directly employs the instantaneous trajectories. Experimental results are shown using a commercial GNSS receiver with data from a GNSS simulator with IMU capability. The length of time and amount of motion required to achieve low probabilities of false alarm and missed detection are analyzed