12,838 research outputs found
Improving Sensitivity to Weak Pulsations with Photon Probability Weighting
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
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
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
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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