7,965 research outputs found

    The CMS Discovery Potential of Supersymmetry within mSugra with two same sign muons

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    A detailed study of the same-sign muon signature within the mSUGRA model was performed. Selection criteria based on the missing transverse energy in the events and the jet and muon transverse momenta are applied to select the data sample. An excess of SUSY events over the standard model background processes can be statistically significant for many benchmark points for an integrated luminosity of less than 10 fb/sup -1detailed detector simulation, trigger emulation and reconstruction were performed

    Constraint Likelihood analysis for a network of gravitational wave detectors

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    We propose a coherent method for the detection and reconstruction of gravitational wave signals for a network of interferometric detectors. The method is derived using the likelihood functional for unknown signal waveforms. In the standard approach, the global maximum of the likelihood over the space of waveforms is used as the detection statistic. We identify a problem with this approach. In the case of an aligned pair of detectors, the detection statistic depends on the cross-correlation between the detectors as expected, but this dependence dissappears even for infinitesimally small misalignments. We solve the problem by applying constraints on thelikelihood functional and obtain a new class of statistics. The resulting method can be applied to the data from a network consisting of any number of detectors with arbitrary detector orientations. The method allows us reconstruction of the source coordinates and the waveforms of two polarization components of a gravitational wave. We study the performance of the method with numerical simulation and find the reconstruction of the source coordinates to be more accurate than in the standard approach.Comment: 13 pages, 6 figure

    Performance of the WaveBurst algorithm on LIGO data

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    In this paper we describe the performance of the WaveBurst algorithm which was designed for detection of gravitational wave bursts in interferometric data. The performance of the algorithm was evaluated on the test data set collected during the second LIGO Scientific run. We have measured the false alarm rate of the algorithm as a function of the threshold and estimated its detection efficiency for simulated burst waveforms.Comment: proceedings of GWDAW, 2003 conference, 13 pages, 6 figure

    A burst search for gravitational waves from binary black holes

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    Compact binary coalescence (CBC) is one of the most promising sources of gravitational waves. These sources are usually searched for with matched filters which require accurate calculation of the GW waveforms and generation of large template banks. We present a complementary search technique based on algorithms used in un-modeled searches. Initially designed for detection of un-modeled bursts, which can span a very large set of waveform morphologies, the search algorithm presented here is constrained for targeted detection of the smaller subset of CBC signals. The constraint is based on the assumption of elliptical polarisation for signals received at the detector. We expect that the algorithm is sensitive to CBC signals in a wide range of masses, mass ratios, and spin parameters. In preparation for the analysis of data from the fifth LIGO-Virgo science run (S5), we performed preliminary studies of the algorithm on test data. We present the sensitivity of the search to different types of simulated CBC waveforms. Also, we discuss how to extend the results of the test run into a search over all of the current LIGO-Virgo data set.Comment: 12 pages, 4 figures, 2 tables, submitted for publication in CQG in the special issue for the conference proceedings of GWDAW13; corrected some typos, addressed some minor reviewer comments one section restructured and references updated and correcte

    Variability of signal to noise ratio and the network analysis of gravitational wave burst signals

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    The detection and estimation of gravitational wave burst signals, with {\em a priori} unknown polarization waveforms, requires the use of data from a network of detectors. For determining how the data from such a network should be combined, approaches based on the maximum likelihood principle have proven to be useful. The most straightforward among these uses the global maximum of the likelihood over the space of all waveforms as both the detection statistic and signal estimator. However, in the case of burst signals, a physically counterintuitive situation results: for two aligned detectors the statistic includes the cross-correlation of the detector outputs, as expected, but this term disappears even for an infinitesimal misalignment. This {\em two detector paradox} arises from the inclusion of improbable waveforms in the solution space of maximization. Such waveforms produce widely different responses in detectors that are closely aligned. We show that by penalizing waveforms that exhibit large signal-to-noise ratio (snr) variability, as the corresponding source is moved on the sky, a physically motivated restriction is obtained that (i) resolves the two detector paradox and (ii) leads to a better performing statistic than the global maximum of the likelihood. Waveforms with high snr variability turn out to be precisely the ones that are improbable in the sense mentioned above. The coherent network analysis method thus obtained can be applied to any network, irrespective of the number or the mutual alignment of detectors.Comment: 13 pages, 6 figure

    Networks of gravitational wave detectors and three figures of merit

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    This paper develops a general framework for studying the effectiveness of networks of interferometric gravitational wave detectors and then uses it to show that enlarging the existing LIGO-VIRGO network with one or more planned or proposed detectors in Japan (LCGT), Australia, and India brings major benefits, including much larger detection rate increases than previously thought... I show that there is a universal probability distribution function (pdf) for detected SNR values, which implies that the most likely SNR value of the first detected event will be 1.26 times the search threshold. For binary systems, I also derive the universal pdf for detected values of the orbital inclination, taking into account the Malmquist bias; this implies that the number of gamma-ray bursts associated with detected binary coalescences should be 3.4 times larger than expected from just the beaming fraction of the gamma burst. Using network antenna patterns, I propose three figures of merit that characterize the relative performance of different networks... Adding {\em any} new site to the planned LIGO-VIRGO network can dramatically increase, by factors of 2 to 4, the detected event rate by allowing coherent data analysis to reduce the spurious instrumental coincident background. Moving one of the LIGO detectors to Australia additionally improves direction-finding by a factor of 4 or more. Adding LCGT to the original LIGO-VIRGO network not only improves direction-finding but will further increase the detection rate over the extra-site gain by factors of almost 2, partly by improving the network duty cycle... Enlarged advanced networks could look forward to detecting three to four hundred neutron star binary coalescences per year.Comment: 38 pages, 7 figures, 2 tables. Accepted for publication in Classical and Quantum Gravit

    Observing an intermediate-mass black hole GW190521 with minimal assumptions

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    On May 21, 2019 the Advanced LIGO and Advanced Virgo detectors observed a gravitational-wave transient GW190521, the heaviest binary black-hole merger detected to date with remnant mass of 142 Mm that was published recently. This observation is the first strong evidence for the existence of intermediate-mass black holes. The significance of this observation was determined by the coherent waveburst (cWB) search algorithm, which identified GW190521 with minimal assumptions of its source model. In this paper, we show the performance of cWB for the detection of the binary black-hole mergers without use of the signal templates, describe the details of the GW190521 detection, and establish the consistency of the model-agnostic reconstruction of GW190521 by cWB with the theoretical waveform model of a binary black hole

    A Study And Application of Face Recognition System

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    人脸识别是近几年来非常受关注的研究课题之一。这一研究领域综合了多个学科:图像处理、模式识别、计算机视觉、神经网络,心理学等等。人脸识别所要解决的问题可以概述如下:给定场景下的静态图像或动态图像序列,应用已知人脸库,从场景里识别一个或多个人。本文研究静态人脸图像识别,这个问题的解决包括:从场景中分割人脸(人脸检测),人脸区域的特征提取、识别或验证。在识别问题中,输入系统人脸图像是未知的人脸,系统将从人脸数据库中找出与输入一致的人脸。本文的主要研究工作:1.本文第一章主要研究与人脸识别相关的神经科学和计算机人脸识别的各种方法,探讨生物识别和计算机识别的相互联系,以及生物识别方法,特别是人脸识别技术...Machine recognition of human face still and video images is one of the active research areas including several disciplines such as image processing, pattern recognition, computer vision and neural networks, psychology and so forth. A general statement of the problem can be formulated as follows: Given still or video images of a scene, identify or verify one or more persons in the scene using a sto...学位:工学硕士院系专业:物理与机电工程学院机电工程系_测试计量技术及仪器学号:20032901
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