NLO Leptoquark Production and Decay: The Narrow-Width Approximation and Beyond

We study the leptoquark model of Buchm\"uller, R\"uckl and Wyler, focusing on a particular type of scalar ($R_2$) and vector ($U_1$) leptoquark. The primary aim is to perform the calculations for leptoquark production and decay at next-to-leading order (NLO) to establish the importance of the NLO contributions and, in particular, to determine how effective the narrow-width-approximation (NWA) is at NLO. For both the scalar and vector leptoquarks it is found that the NLO contributions are large, with the larger corrections occurring for the case vector leptoquarks. For the scalar leptoquark it is found that the NWA provides a good approximation for determining the resonant peak, however the NWA is not as effective for the vector leptoquark. For both the scalar and vector leptoquarks there are large contributions away from the resonant peak, which are missing from the NWA results, and these make a significant difference to the total cross-section.Comment: 22 pages, 17 figure

Incremental Art: A Neural Network System for Recognition by Incremental Feature Extraction

Abstract Incremental ART extends adaptive resonance theory (ART) by incorporating mechanisms for efficient recognition through incremental feature extraction. The system achieves efficient confident prediction through the controlled acquisition of only those features necessary to discriminate an input pattern. These capabilities are achieved through three modifications to the fuzzy ART system: (1) A partial feature vector complement coding rule extends fuzzy ART logic to allow recognition based on partial feature vectors. (2) The addition of a F2 decision criterion to measure ART predictive confidence. (3) An incremental feature extraction layer computes the next feature to extract based on a measure of predictive value. Our system is demonstrated on a face recognition problem but has general applicability as a machine vision solution and as model for studying scanning patterns.Office of Naval Research (N00014-92-J-4015, N00014-92-J-1309, N00014-91-4100); Air Force Office of Scientific Research (90-0083); National Science Foundation (IRI 90-00530

An OpenSHMEM Implementation for the Adapteva Epiphany Coprocessor

This paper reports the implementation and performance evaluation of the OpenSHMEM 1.3 specification for the Adapteva Epiphany architecture within the Parallella single-board computer. The Epiphany architecture exhibits massive many-core scalability with a physically compact 2D array of RISC CPU cores and a fast network-on-chip (NoC). While fully capable of MPMD execution, the physical topology and memory-mapped capabilities of the core and network translate well to Partitioned Global Address Space (PGAS) programming models and SPMD execution with SHMEM.Comment: 14 pages, 9 figures, OpenSHMEM 2016: Third workshop on OpenSHMEM and Related Technologie

Honeywell's Compact, Wide-angle Uv-visible Imaging Sensor

Honeywell is currently developing the Earth Reference Attitude Determination System (ERADS). ERADS determines attitude by imaging the entire Earth's limb and a ring of the adjacent star field in the 2800-3000 A band of the ultraviolet. This is achieved through the use of a highly nonconventional optical system, an intensifier tube, and a mega-element CCD array. The optics image a 30 degree region in the center of the field, and an outer region typically from 128 to 148 degrees, which can be adjusted up to 180 degrees. Because of the design employed, the illumination at the outer edge of the field is only some 15 percent below that at the center, in contrast to the drastic rolloffs encountered in conventional wide-angle sensors. The outer diameter of the sensor is only 3 in; the volume and weight of the entire system, including processor, are 1000 cc and 6 kg, respectively

OpenCL + OpenSHMEM Hybrid Programming Model for the Adapteva Epiphany Architecture

There is interest in exploring hybrid OpenSHMEM + X programming models to extend the applicability of the OpenSHMEM interface to more hardware architectures. We present a hybrid OpenCL + OpenSHMEM programming model for device-level programming for architectures like the Adapteva Epiphany many-core RISC array processor. The Epiphany architecture comprises a 2D array of low-power RISC cores with minimal uncore functionality connected by a 2D mesh Network-on-Chip (NoC). The Epiphany architecture offers high computational energy efficiency for integer and floating point calculations as well as parallel scalability. The Epiphany-III is available as a coprocessor in platforms that also utilize an ARM CPU host. OpenCL provides good functionality for supporting a co-design programming model in which the host CPU offloads parallel work to a coprocessor. However, the OpenCL memory model is inconsistent with the Epiphany memory architecture and lacks support for inter-core communication. We propose a hybrid programming model in which OpenSHMEM provides a better solution by replacing the non-standard OpenCL extensions introduced to achieve high performance with the Epiphany architecture. We demonstrate the proposed programming model for matrix-matrix multiplication based on Cannon's algorithm showing that the hybrid model addresses the deficiencies of using OpenCL alone to achieve good benchmark performance.Comment: 12 pages, 5 figures, OpenSHMEM 2016: Third workshop on OpenSHMEM and Related Technologie