28,675 research outputs found
Simulating full-sky interferometric observations
Aperture array interferometers, such as that proposed for the Square
Kilometre Array (SKA), will see the entire sky, hence the standard approach to
simulating visibilities will not be applicable since it relies on a tangent
plane approximation that is valid only for small fields of view. We derive
interferometric formulations in real, spherical harmonic and wavelet space that
include contributions over the entire sky and do not rely on any tangent plane
approximations. A fast wavelet method is developed to simulate the visibilities
observed by an interferometer in the full-sky setting. Computing visibilities
using the fast wavelet method adapts to the sparse representation of the
primary beam and sky intensity in the wavelet basis. Consequently, the fast
wavelet method exhibits superior computational complexity to the real and
spherical harmonic space methods and may be performed at substantially lower
computational cost, while introducing only negligible error to simulated
visibilities. Low-resolution interferometric observations are simulated using
all of the methods to compare their performance, demonstrating that the fast
wavelet method is approximately three times faster that the other methods for
these low-resolution simulations. The computational burden of the real and
spherical harmonic space methods renders these techniques computationally
infeasible for higher resolution simulations. High-resolution interferometric
observations are simulated using the fast wavelet method only, demonstrating
and validating the application of this method to realistic simulations. The
fast wavelet method is estimated to provide a greater than ten-fold reduction
in execution time compared to the other methods for these high-resolution
simulations.Comment: 16 pages, 9 figures, replaced to match version accepted by MNRAS
(major additions to previous version including new fast wavelet method
Fast directional continuous spherical wavelet transform algorithms
We describe the construction of a spherical wavelet analysis through the
inverse stereographic projection of the Euclidean planar wavelet framework,
introduced originally by Antoine and Vandergheynst and developed further by
Wiaux et al. Fast algorithms for performing the directional continuous wavelet
analysis on the unit sphere are presented. The fast directional algorithm,
based on the fast spherical convolution algorithm developed by Wandelt and
Gorski, provides a saving of O(sqrt(Npix)) over a direct quadrature
implementation for Npix pixels on the sphere, and allows one to perform a
directional spherical wavelet analysis of a 10^6 pixel map on a personal
computer.Comment: 10 pages, 3 figures, replaced to match version accepted by IEEE
Trans. Sig. Pro
3D weak lensing with spin wavelets on the ball
We construct the spin flaglet transform, a wavelet transform to analyze spin
signals in three dimensions. Spin flaglets can probe signal content localized
simultaneously in space and frequency and, moreover, are separable so that
their angular and radial properties can be controlled independently. They are
particularly suited to analyzing of cosmological observations such as the weak
gravitational lensing of galaxies. Such observations have a unique 3D
geometrical setting since they are natively made on the sky, have spin angular
symmetries, and are extended in the radial direction by additional distance or
redshift information. Flaglets are constructed in the harmonic space defined by
the Fourier-Laguerre transform, previously defined for scalar functions and
extended here to signals with spin symmetries. Thanks to various sampling
theorems, both the Fourier-Laguerre and flaglet transforms are theoretically
exact when applied to bandlimited signals. In other words, in numerical
computations the only loss of information is due to the finite representation
of floating point numbers. We develop a 3D framework relating the weak lensing
power spectrum to covariances of flaglet coefficients. We suggest that the
resulting novel flaglet weak lensing estimator offers a powerful alternative to
common 2D and 3D approaches to accurately capture cosmological information.
While standard weak lensing analyses focus on either real or harmonic space
representations (i.e., correlation functions or Fourier-Bessel power spectra,
respectively), a wavelet approach inherits the advantages of both techniques,
where both complicated sky coverage and uncertainties associated with the
physical modeling of small scales can be handled effectively. Our codes to
compute the Fourier-Laguerre and flaglet transforms are made publicly
available.Comment: 24 pages, 4 figures, version accepted for publication in PR
Localisation of directional scale-discretised wavelets on the sphere
Scale-discretised wavelets yield a directional wavelet framework on the
sphere where a signal can be probed not only in scale and position but also in
orientation. Furthermore, a signal can be synthesised from its wavelet
coefficients exactly, in theory and practice (to machine precision).
Scale-discretised wavelets are closely related to spherical needlets (both were
developed independently at about the same time) but relax the axisymmetric
property of needlets so that directional signal content can be probed. Needlets
have been shown to satisfy important quasi-exponential localisation and
asymptotic uncorrelation properties. We show that these properties also hold
for directional scale-discretised wavelets on the sphere and derive similar
localisation and uncorrelation bounds in both the scalar and spin settings.
Scale-discretised wavelets can thus be considered as directional needlets.Comment: 28 pages, 8 figures, minor changes to match version accepted for
publication by ACH
Sparse image reconstruction on the sphere: analysis and synthesis
We develop techniques to solve ill-posed inverse problems on the sphere by
sparse regularisation, exploiting sparsity in both axisymmetric and directional
scale-discretised wavelet space. Denoising, inpainting, and deconvolution
problems, and combinations thereof, are considered as examples. Inverse
problems are solved in both the analysis and synthesis settings, with a number
of different sampling schemes. The most effective approach is that with the
most restricted solution-space, which depends on the interplay between the
adopted sampling scheme, the selection of the analysis/synthesis problem, and
any weighting of the l1 norm appearing in the regularisation problem. More
efficient sampling schemes on the sphere improve reconstruction fidelity by
restricting the solution-space and also by improving sparsity in wavelet space.
We apply the technique to denoise Planck 353 GHz observations, improving the
ability to extract the structure of Galactic dust emission, which is important
for studying Galactic magnetism.Comment: 11 pages, 6 Figure
Efficient analysis and representation of geophysical processes using localized spherical basis functions
While many geological and geophysical processes such as the melting of
icecaps, the magnetic expression of bodies emplaced in the Earth's crust, or
the surface displacement remaining after large earthquakes are spatially
localized, many of these naturally admit spectral representations, or they may
need to be extracted from data collected globally, e.g. by satellites that
circumnavigate the Earth. Wavelets are often used to study such nonstationary
processes. On the sphere, however, many of the known constructions are somewhat
limited. And in particular, the notion of `dilation' is hard to reconcile with
the concept of a geological region with fixed boundaries being responsible for
generating the signals to be analyzed. Here, we build on our previous work on
localized spherical analysis using an approach that is firmly rooted in
spherical harmonics. We construct, by quadratic optimization, a set of
bandlimited functions that have the majority of their energy concentrated in an
arbitrary subdomain of the unit sphere. The `spherical Slepian basis' that
results provides a convenient way for the analysis and representation of
geophysical signals, as we show by example. We highlight the connections to
sparsity by showing that many geophysical processes are sparse in the Slepian
basis.Comment: To appear in the Proceedings of the SPIE, as part of the Wavelets
XIII conference in San Diego, August 200
A fast multipole method for stellar dynamics
The approximate computation of all gravitational forces between
interacting particles via the fast multipole method (FMM) can be made as
accurate as direct summation, but requires less than
operations. FMM groups particles into spatially bounded cells and uses
cell-cell interactions to approximate the force at any position within the sink
cell by a Taylor expansion obtained from the multipole expansion of the source
cell. By employing a novel estimate for the errors incurred in this process, I
minimise the computational effort required for a given accuracy and obtain a
well-behaved distribution of force errors. For relative force errors of
, the computational costs exhibit an empirical scaling of . My implementation (running on a 16 core node) out-performs a
GPU-based direct summation with comparable force errors for .Comment: 21 pages, 15 figures, accepted for publication in Journal for
Computational Astrophysics and Cosmolog
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