200 research outputs found
On the Evidence for Clustering in the Arrival Directions of AGASA's Ultrahigh Energy Cosmic Rays
Previous analyses of cosmic rays above 40 EeV observed by the AGASA
experiment have suggested that their arrival directions may be clustered.
However, estimates of the chance probability of this clustering signal vary
from 10^{-2} to 10^{-6} and beyond. It is essential that the strength of this
evidence be well understood in order to compare it with anisotropy studies in
other cosmic ray experiments. We apply two methods for extracting a meaningful
significance from this data set: one can scan for the cuts which optimize the
clustering signal, using simulations to determine the appropriate statistical
penalty for the scan. This analysis finds a chance probability of about 0.3%.
Alternatively, one can optimize the cuts with a first set of data, and then
apply them to the remaining data directly without statistical penalty. One can
extend the statistical power of this test by considering cross-correlation
between the initial data and the remaining data, as long as the initial
clustering signal is not included. While the scan is more useful in general, in
the present case only splitting the data set offers an unbiased test of the
clustering hypothesis. Using this test we find that the AGASA data is
consistent at the 8% level with the null hypothesis of isotropically
distributed arrival directions.Comment: 14 pages, 3 figures. Unbiased test expanded to include
cross-correlation between initial and later data sets for greater statistical
power; minor revisions to discussion. Accepted by Astropart. Phy
Angular Correlation Estimates for Ultrahigh Energy Cosmic Rays
Anisotropy in arrival directions of ultrahigh energy cosmic rays offers the
most direct way to search for the sources of these particles. We present
estimates of the angular correlation in the HiRes sample of stereo events above
10 EeV, and in the combined sample of HiRes and AGASA events above 40 EeV.Comment: 5 pages, 2 figures; to appear in the proceedings of DPF 2004,
Riverside, 26 - 31 Aug. 2004 (Int.J.Mod.Phys.A
Observational Constraints on Multi-messenger Sources of Gravitational Waves and High-energy Neutrinos
It remains an open question to what extent many of the astronomical sources
of intense bursts of electromagnetic radiation are also strong emitters of
non-photon messengers, in particular gravitational waves (GWs) and high-energy
neutrinos (HENs). Such emission would provide unique insights into the physics
of the bursts; moreover some suspected classes, e.g. choked gamma-ray bursts,
may in fact only be identifiable via these alternative channels. Here we
explore the reach of current and planned experiments to address this question.
We derive constraints on the rate of GW and HEN bursts per Milky Way equivalent
(MWE) galaxy based on independent observations by the initial LIGO and Virgo GW
detectors and the partially completed IceCube (40-string) HEN detector. We take
into account the blue-luminosity-weighted distribution of nearby galaxies,
assuming that source distribution follows the blue-luminosity distribution. We
then estimate the reach of joint GW+HEN searches using advanced GW detectors
and the completed cubic-km IceCube detector to probe the joint parameter space.
We show that searches undertaken by advanced detectors will be capable of
detecting, constraining or excluding, several existing models with one year of
observation
Search for Cross-Correlations of Ultra--High-Energy Cosmic Rays with BL Lacertae Objects
We present the results of searches for correlation between ultra--high-energy
cosmic rays observed in stereo mode by the High Resolution Fly's Eye (HiRes)
experiment and objects of the BL Lac subclass of active galaxies. In
particular, we discuss an excess of events correlating with confirmed BL Lacs
in the Veron 10th Catalog. As described in detail in Abbasi et al. (2005), the
significance level of these correlations cannot be reliably estimated due to
the a posteriori nature of the search, and the results must be tested
independently before any claim can be made. We identify the precise hypotheses
that will be tested with independent data.Comment: 4 pages. To be presented at the 2005 ICRC in Pune, India, in Augus
Methods for point source analysis in high energy neutrino telescopes
Neutrino telescopes are moving steadily toward the goal of detecting
astrophysical neutrinos from the most powerful galactic and extragalactic
sources. Here we describe analysis methods to search for high energy point-like
neutrino sources using detectors deep in the ice or sea. We simulate an ideal
cubic kilometer detector based on real world performance of existing detectors
such as AMANDA, IceCube, and ANTARES. An unbinned likelihood ratio method is
applied, making use of the point spread function and energy distribution of
simulated neutrino signal events to separate them from the background of
atmospheric neutrinos produced by cosmic ray showers. The unbinned point source
analyses are shown to perform better than binned searches and, depending on the
source spectral index, the use of energy information is shown to improve
discovery potential by almost a factor of two.Comment: pdfLaTeX, 16 pages, 12 figures. Submitted to Astroparticle Physic
Joint hierarchical models for sparsely sampled high-dimensional LiDAR and forest variables
Recent advancements in remote sensing technology, specifically Light Detection and Ranging (LiDAR) sensors, provide the data needed to quantify forest characteristics at a fine spatial resolution over large geographic domains. From an inferential standpoint, there is interest in prediction and interpolation of the often sparsely sampled and spatially misaligned LiDAR signals and forest variables. We propose a fully process-based Bayesian hierarchical model for above ground biomass (AGB) and LiDAR signals. The processbased framework offers richness in inferential capabilities, e.g., inference on the entire underlying processes instead of estimates only at pre-specified points. Key challenges we obviate include misalignment between the AGB observations and LiDAR signals and the high-dimensionality in the model emerging from LiDAR signals in conjunction with the large number of spatial locations. We offer simulation experiments to evaluate our proposed models and also apply them to a challenging dataset comprising LiDAR and spatially coinciding forest inventory variables collected on the Penobscot Experimental Forest (PEF), Maine. Our key substantive contributions include AGB data products with associated measures of uncertainty for the PEF and, more broadly, a methodology that should find use in a variety of current and upcoming forest variable mapping efforts using sparsely sampled remotely sensed high-dimensional data
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