Parsing a sequence of qubits

We develop a theoretical framework for frame synchronization, also known as block synchronization, in the quantum domain which makes it possible to attach classical and quantum metadata to quantum information over a noisy channel even when the information source and sink are frame-wise asynchronous. This eliminates the need of frame synchronization at the hardware level and allows for parsing qubit sequences during quantum information processing. Our framework exploits binary constant-weight codes that are self-synchronizing. Possible applications may include asynchronous quantum communication such as a self-synchronizing quantum network where one can hop into the channel at any time, catch the next coming quantum information with a label indicating the sender, and reply by routing her quantum information with control qubits for quantum switches all without assuming prior frame synchronization between users.Comment: 11 pages, 2 figures, 1 table. Final accepted version for publication in the IEEE Transactions on Information Theor

Experimental quantum key distribution with finite-key security analysis for noisy channels

In quantum key distribution implementations, each session is typically chosen long enough so that the secret key rate approaches its asymptotic limit. However, this choice may be constrained by the physical scenario, as in the perspective use with satellites, where the passage of one terminal over the other is restricted to a few minutes. Here we demonstrate experimentally the extraction of secure keys leveraging an optimal design of the prepare-and-measure scheme, according to recent finite-key theoretical tight-bounds. The experiment is performed in different channel conditions, and assuming two distinct attack models: individual attacks, or general quantum attacks. The request on the number of exchanged qubits is then obtained as a function of the key size and of the ambient quantum bit error rate. The results indicate that viable conditions for effective symmetric, and even one-time-pad, cryptography are achievable.Comment: 20 pages, 4 figure

Digital recording of performing arts: formats and conversion

B

Advanced information processing system: The Army fault tolerant architecture conceptual study. Volume 2: Army fault tolerant architecture design and analysis

Described here is the Army Fault Tolerant Architecture (AFTA) hardware architecture and components and the operating system. The architectural and operational theory of the AFTA Fault Tolerant Data Bus is discussed. The test and maintenance strategy developed for use in fielded AFTA installations is presented. An approach to be used in reducing the probability of AFTA failure due to common mode faults is described. Analytical models for AFTA performance, reliability, availability, life cycle cost, weight, power, and volume are developed. An approach is presented for using VHSIC Hardware Description Language (VHDL) to describe and design AFTA's developmental hardware. A plan is described for verifying and validating key AFTA concepts during the Dem/Val phase. Analytical models and partial mission requirements are used to generate AFTA configurations for the TF/TA/NOE and Ground Vehicle missions

PacTrack: The use of virtual environments in the identification and analysis of the neuronal correlates of fear, anxiety, and approach-avoidance behaviors

Electroencephalography (EEG) is a powerful tool that has proven itself essential in successfully discovering significant neuronal correlates underlying various cognitive and behavioral events, such as the hippocampal theta oscillation in memory and spatial navigation. A large negative deflection in potential has been observed as a critical component in modulating error in information processing, termed the ERN. A similar pattern has been found following positive feedback, though whether an analogous effect occurs in internally recognized success is unknown. Researchers have additionally found evidence that theta and gamma oscillations and their intersections play important roles in regulating general fear and anxiety. In this investigation, we study whether a significant deflection in potential occurs as a result of internally recognized success, as well as whether the neuronal correlates associated with fear and memory extend themselves to approach-avoidance behaviors, by observing scalp EEG in midfrontal cortex while playing Pac-Man, taking advantage of Pac-Man’s various behavioral events and states to simulate the above. We find evidence of the ERN following failure, though no significant evoked potential following similar internally recognized success events is observed. The theta and gamma oscillatory patterns modulating fear and anxiety are ascertained to hold true to novel approach-avoidance contexts, and preliminary evidence detecting a shift in oscillations following learning is marked. While EEG is typically performed in laboratory settings, our study shows the merits of and our increasing capability to gather EEG data in naturalistic environments, informing our ability to decode neuronal mechanisms in more everyday contexts and increasing the ethological validity of our work.Neuroscienc

Trunk Inclination Estimate During the Sprint Start Using an Inertial Measurement Unit: A Validation Study

The proper execution of the sprint start is crucial in determining the performance during a sprint race. In this respect, when moving from the crouch to the upright position, trunk kinematics is a key element. The purpose of this study was to validate the use of a trunk-mounted inertial measurement unit (IMU) in estimating the trunk inclination and angular velocity in the sagittal plane during the sprint start. In-laboratory sprint starts were performed by five sprinters. The local acceleration and angular velocity components provided by the IMU were processed using an adaptive Kalman filter. The accuracy of the IMU inclination estimate and its consistency with trunk inclination were assessed using reference stereophotogrammetric measurements. A Bland-Altman analysis, carried out using parameters (minimum, maximum, and mean values) extracted from the time histories of the estimated variables, and curve similarity analysis (correlation coefficient > 0.99, root mean square difference < 7 deg) indicated the agreement between reference and IMU estimates, opening a promising scenario for an accurate in-field use of IMUs for sprint start performance assessment

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

One of the challenges in modeling cognitive events from electroencephalogram (EEG) data is finding representations that are invariant to inter- and intra-subject differences, as well as to inherent noise associated with such data. Herein, we propose a novel approach for learning such representations from multi-channel EEG time-series, and demonstrate its advantages in the context of mental load classification task. First, we transform EEG activities into a sequence of topology-preserving multi-spectral images, as opposed to standard EEG analysis techniques that ignore such spatial information. Next, we train a deep recurrent-convolutional network inspired by state-of-the-art video classification to learn robust representations from the sequence of images. The proposed approach is designed to preserve the spatial, spectral, and temporal structure of EEG which leads to finding features that are less sensitive to variations and distortions within each dimension. Empirical evaluation on the cognitive load classification task demonstrated significant improvements in classification accuracy over current state-of-the-art approaches in this field.Comment: To be published as a conference paper at ICLR 201

Performance Analysis and Enhancement of Multiband OFDM for UWB Communications

In this paper, we analyze the frequency-hopping orthogonal frequency-division multiplexing (OFDM) system known as Multiband OFDM for high-rate wireless personal area networks (WPANs) based on ultra-wideband (UWB) transmission. Besides considering the standard, we also propose and study system performance enhancements through the application of Turbo and Repeat-Accumulate (RA) codes, as well as OFDM bit-loading. Our methodology consists of (a) a study of the channel model developed under IEEE 802.15 for UWB from a frequency-domain perspective suited for OFDM transmission, (b) development and quantification of appropriate information-theoretic performance measures, (c) comparison of these measures with simulation results for the Multiband OFDM standard proposal as well as our proposed extensions, and (d) the consideration of the influence of practical, imperfect channel estimation on the performance. We find that the current Multiband OFDM standard sufficiently exploits the frequency selectivity of the UWB channel, and that the system performs in the vicinity of the channel cutoff rate. Turbo codes and a reduced-complexity clustered bit-loading algorithm improve the system power efficiency by over 6 dB at a data rate of 480 Mbps.Comment: 32 pages, 10 figures, 1 table. Submitted to the IEEE Transactions on Wireless Communications (Sep. 28, 2005). Minor revisions based on reviewers' comments (June 23, 2006