3,334 research outputs found
ARKCoS: Artifact-Suppressed Accelerated Radial Kernel Convolution on the Sphere
We describe a hybrid Fourier/direct space convolution algorithm for compact
radial (azimuthally symmetric) kernels on the sphere. For high resolution maps
covering a large fraction of the sky, our implementation takes advantage of the
inexpensive massive parallelism afforded by consumer graphics processing units
(GPUs). Applications involve modeling of instrumental beam shapes in terms of
compact kernels, computation of fine-scale wavelet transformations, and optimal
filtering for the detection of point sources. Our algorithm works for any
pixelization where pixels are grouped into isolatitude rings. Even for kernels
that are not bandwidth limited, ringing features are completely absent on an
ECP grid. We demonstrate that they can be highly suppressed on the popular
HEALPix pixelization, for which we develop a freely available implementation of
the algorithm. As an example application, we show that running on a high-end
consumer graphics card our method speeds up beam convolution for simulations of
a characteristic Planck high frequency instrument channel by two orders of
magnitude compared to the commonly used HEALPix implementation on one CPU core
while maintaining at typical a fractional RMS accuracy of about 1 part in 10^5.Comment: 10 pages, 6 figures. Submitted to Astronomy and Astrophysics.
Replaced to match published version. Code can be downloaded at
https://github.com/elsner/arkco
Fast, exact CMB power spectrum estimation for a certain class of observational strategies
We describe a class of observational strategies for probing the anisotropies
in the cosmic microwave background (CMB) where the instrument scans on rings
which can be combined into an n-torus, the {\em ring torus}. This class has the
remarkable property that it allows exact maximum likelihood power spectrum
estimation in of order operations (if the size of the data set is )
under circumstances which would previously have made this analysis intractable:
correlated receiver noise, arbitrary asymmetric beam shapes and far side lobes,
non-uniform distribution of integration time on the sky and partial sky
coverage. This ease of computation gives us an important theoretical tool for
understanding the impact of instrumental effects on CMB observables and hence
for the design and analysis of the CMB observations of the future. There are
members of this class which closely approximate the MAP and Planck satellite
missions. We present a numerical example where we apply our ring torus methods
to a simulated data set from a CMB mission covering a 20 degree patch on the
sky to compute the maximum likelihood estimate of the power spectrum
with unprecedented efficiency.Comment: RevTeX, 14 pages, 5 figures. A full resolution version of Figure 1
and additional materials are at http://feynman.princeton.edu/~bwandelt/RT
Compressed sensing for wide-field radio interferometric imaging
For the next generation of radio interferometric telescopes it is of
paramount importance to incorporate wide field-of-view (WFOV) considerations in
interferometric imaging, otherwise the fidelity of reconstructed images will
suffer greatly. We extend compressed sensing techniques for interferometric
imaging to a WFOV and recover images in the spherical coordinate space in which
they naturally live, eliminating any distorting projection. The effectiveness
of the spread spectrum phenomenon, highlighted recently by one of the authors,
is enhanced when going to a WFOV, while sparsity is promoted by recovering
images directly on the sphere. Both of these properties act to improve the
quality of reconstructed interferometric images. We quantify the performance of
compressed sensing reconstruction techniques through simulations, highlighting
the superior reconstruction quality achieved by recovering interferometric
images directly on the sphere rather than the plane.Comment: 15 pages, 8 figures, replaced to match version accepted by MNRA
Orthogonal transforms and their application to image coding
Imperial Users onl
The Unification and Decomposition of Processing Structures Using Lattice Theoretic Methods
The purpose of this dissertation is to demonstrate that lattice theoretic methods can be used to decompose and unify computational structures over a variety of processing systems. The unification arguments provide a better understanding of the intricacies of the development of processing system decomposition. Since abstract algebraic techniques are used, the decomposition process is systematized which makes it conducive to the use of computers as tools for decomposition. A general algorithm using the lattice theoretic method is developed to examine the structures and therefore decomposition properties of integer and polynomial rings. Two fundamental representations, the Sino-correspondence and the weighted radix representation, are derived for integer and polynomial structures and are shown to be a natural result of the decomposition process. They are used in developing systematic methods for decomposing discrete Fourier transforms and discrete linear systems. That is, fast Fourier transforms and partial fraction expansions of linear systems are a result of the natural representation derived using the lattice theoretic method. The discrete Fourier transform is derived from a lattice theoretic base demonstrating its independence of the continuous form and of the field over which it is computed. The same properties are demonstrated for error control codes based on polynomials. Partial fraction expansions are shown to be independent of the concept of a derivative for repeated roots and the field used to implement them
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