12,838 research outputs found

    Improving Sensitivity to Weak Pulsations with Photon Probability Weighting

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    All gamma-ray telescopes suffer from source confusion due to their inability to focus incident high-energy radiation, and the resulting background contamination can obscure the periodic emission from faint pulsars. In the context of the Fermi Large Area Telescope, we outline enhanced statistical tests for pulsation in which each photon is weighted by its probability to have originated from the candidate pulsar. The probabilities are calculated using the instrument response function and a full spectral model, enabling powerful background rejection. With Monte Carlo methods, we demonstrate that the new tests increase the sensitivity to pulsars by more than 50% under a wide range of conditions. This improvement may appreciably increase the completeness of the sample of radio-loud gamma-ray pulsars. Finally, we derive the asymptotic null distribution for the H-test, expanding its domain of validity to arbitrarily complex light curves.Comment: 10 pages, 11 figures, published by ApJ; v2 fixes an error in Eq.

    A Pixel Vertex Tracker for the TESLA Detector

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    In order to fully exploit the physics potential of a e+e- linear collider, such as TESLA, a Vertex Tracker providing high resolution track reconstruction is required. Hybrid Silicon pixel sensors are an attractive sensor technology option due to their read-out speed and radiation hardness, favoured in the high rate TESLA environment, but have been so far limited by the achievable single point space resolution. A novel layout of pixel detectors with interleaved cells to improve their spatial resolution is introduced and the results of the characterisation of a first set of test structures are discussed. In this note, a conceptual design of the TESLA Vertex Tracker, based on hybrid pixel sensors is presentedComment: 20 pages, 11 figure

    Identification of Long-lived Charged Particles using Time-Of-Flight Systems at the Upgraded LHC detectors

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    We study the impact of picosecond precision timing detection systems on the LHC experiments' long-lived particle search program during the HL-LHC era. We develop algorithms that allow us to reconstruct the mass of such charged particles and perform particle identification using the time-of-flight measurement. We investigate the reach for benchmark scenarios as a function of the timing resolution, and find sensitivity improvement of up to a factor of ten, depending on the new heavy particle mass.Comment: 20 pages, 13 figure

    Eigenvalue-based Cyclostationary Spectrum Sensing Using Multiple Antennas

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    In this paper, we propose a signal-selective spectrum sensing method for cognitive radio networks and specifically targeted for receivers with multiple-antenna capability. This method is used for detecting the presence or absence of primary users based on the eigenvalues of the cyclic covariance matrix of received signals. In particular, the cyclic correlation significance test is used to detect a specific signal-of-interest by exploiting knowledge of its cyclic frequencies. The analytical threshold for achieving constant false alarm rate using this detection method is presented, verified through simulations, and shown to be independent of both the number of samples used and the noise variance, effectively eliminating the dependence on accurate noise estimation. The proposed method is also shown, through numerical simulations, to outperform existing multiple-antenna cyclostationary-based spectrum sensing algorithms under a quasi-static Rayleigh fading channel, in both spatially correlated and uncorrelated noise environments. The algorithm also has significantly lower computational complexity than these other approaches.Comment: 6 pages, 6 figures, accepted to IEEE GLOBECOM 201
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