12 research outputs found
Scientific Highlights of the HETE-2 Mission
The HETE-2 mission has been highly productive. It has observed more than 250
GRBs so far. It is currently localizing 25 - 30 GRBs per year, and has
localized 43 GRBs to date. Twenty-one of these localizations have led to the
detection of X-ray, optical, or radio afterglows, and as of now, 11 of the
bursts with afterglows have known redshifts. HETE-2 has confirmed the
connection between GRBs and Type Ic supernovae, a singular achievement and
certainly one of the scientific highlights of the mission so far. It has
provided evidence that the isotropic-equivalent energies and luminosities of
GRBs are correlated with redshift, implying that GRBs and their progenitors
evolve strongly with redshift. Both of these results have profound implications
for the nature of GRB progenitors and for the use of GRBs as a probe of
cosmology and the early universe. HETE-2 has placed severe constraints on any
X-ray or optical afterglow of a short GRB. It is also solving the mystery of
"optically dark' GRBs, and revealing the nature of X-ray flashes.Comment: 10 pages, 9 figures, to appear in proc. "The Restless High-Energy
Universe", Royal Tropical Institute, Amsterdam; revised text, added ref
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PIN diode array x-ray imaging. Final Technical report
We have completed constructing an x-ray camera based on a solid state imaging device and have obtained images of Omega laser targets. A Si PIN diode array is used. Objective of this project is to investigate the use of a PIN diode array readout device for obtaining images of 1-20 keV x-ray emission from laser targets. The PIN array detector was successfully used for obtaining hard x-ray images in the high powered laser environment and real time images of the x-ray emission from laser targets
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Atmospheric PSF Interpolation for Weak Lensing in Short Exposure Imaging Data
A main science goal for the Large Synoptic Survey Telescope (LSST) is to measure the cosmic shear signal from weak lensing to extreme accuracy. One difficulty, however, is that with the short exposure time ({approx_equal}15 seconds) proposed, the spatial variation of the Point Spread Function (PSF) shapes may be dominated by the atmosphere, in addition to optics errors. While optics errors mainly cause the PSF to vary on angular scales similar or larger than a single CCD sensor, the atmosphere generates stochastic structures on a wide range of angular scales. It thus becomes a challenge to infer the multi-scale, complex atmospheric PSF patterns by interpolating the sparsely sampled stars in the field. In this paper we present a new method, psfent, for interpolating the PSF shape parameters, based on reconstructing underlying shape parameter maps with a multi-scale maximum entropy algorithm. We demonstrate, using images from the LSST Photon Simulator, the performance of our approach relative to a 5th-order polynomial fit (representing the current standard) and a simple boxcar smoothing technique. Quantitatively, psfent predicts more accurate PSF models in all scenarios and the residual PSF errors are spatially less correlated. This improvement in PSF interpolation leads to a factor of 3.5 lower systematic errors in the shear power spectrum on scales smaller than {approx} 13, compared to polynomial fitting. We estimate that with psfent and for stellar densities greater than {approx_equal}1/arcmin{sup 2}, the spurious shear correlation from PSF interpolation, after combining a complete 10-year dataset from LSST, is lower than the corresponding statistical uncertainties on the cosmic shear power spectrum, even under a conservative scenario
Phenotypic integration: studying the ecology and evolution of complex phenotypes
Phenotypic integration refers to the study of complex patterns of covariation among functionally related traits in a given organism. It has been investigated throughout the 20th century, but has only recently risen to the forefront of evolutionary ecological research. In this essay, I identify the reasons for this late flourishing of studies on integration, and discuss some of the major areas of current endeavour: the interplay of adaptation and constraints, the genetic and molecular bases of integration, the role of phenotypic plasticity, macroevolutionary studies of integration, and statistical and conceptual issues in the study of the evolution of complex phenotypes. I then conclude with a brief discussion of what I see as the major future directions of research on phenotypic integration and how they relate to our more general quest for the understanding of phenotypic evolution within the neo-Darwinian framework. I suggest that studying integration provides a particularly stimulating and truly interdisciplinary convergence of researchers from fields as disparate as molecular genetics, developmental biology, evolutionary ecology, palaeontology and even philosophy of science