GPU Acceleration of Image Convolution using Spatially-varying Kernel

Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution technique is used. Particularly suitable for large-scale images is a computationally intensive spatially-varying kernel. The underlying algorithm is inherently massively parallel due to unique kernel generation at every pixel location. The spatially-varying kernel cannot be efficiently computed through the Convolution Theorem, and thus does not lend itself to acceleration by Fast Fourier Transform (FFT). This work presents results of accelerated implementation of the spatially-varying kernel image convolution in multi-cores with OpenMP and graphic processing units (GPUs). Typical speedups over ANSI-C were a factor of 50 and a factor of 1000 over the initial IDL implementation, demonstrating that the techniques are a practical and high impact path to terabyte-per-night image pipelines and petascale processing.Comment: 4 pages. Accepted to IEEE-ICIP 201

Simulating extreme-mass-ratio systems in full general relativity

We introduce a new method for numerically evolving the full Einstein field equations in situations where the spacetime is dominated by a known background solution. The technique leverages the knowledge of the background solution to subtract off its contribution to the truncation error, thereby more efficiently achieving a desired level of accuracy. We demonstrate the method by applying it to the radial infall of a solar-type star into supermassive black holes with mass ratios $\geq 10^6$. The self-gravity of the star is thus consistently modeled within the context of general relativity, and the star's interaction with the black hole computed with moderate computational cost, despite the over five orders of magnitude difference in gravitational potential (as defined by the ratio of mass to radius). We compute the tidal deformation of the star during infall, and the gravitational wave emission, finding the latter is close to the prediction of the point-particle limit.Comment: 6 pages, 5 figures; added one figure, revised to match PRD RC versio

Direction-Dependent Polarised Primary Beams in Wide-Field Synthesis Imaging

The process of wide-field synthesis imaging is explored, with the aim of understanding the implications of variable, polarised primary beams for forthcoming Epoch of Reionisation experiments. These experiments seek to detect weak signatures from redshifted 21cm emission in deep residual datasets, after suppression and subtraction of foreground emission. Many subtraction algorithms benefit from low side-lobes and polarisation leakage at the outset, and both of these are intimately linked to how the polarised primary beams are handled. Building on previous contributions from a number of authors, in which direction-dependent corrections are incorporated into visibility gridding kernels, we consider the special characteristics of arrays of fixed dipole antennas operating around 100-200 MHz, looking towards instruments such as the Square Kilometre Array (SKA) and the Hydrogen Epoch of Reionization Arrays (HERA). We show that integrating snapshots in the image domain can help to produce compact gridding kernels, and also reduce the need to make complicated polarised leakage corrections during gridding. We also investigate an alternative form for the gridding kernel that can suppress variations in the direction-dependent weighting of gridded visibilities by 10s of dB, while maintaining compact support.Comment: 15 pages, 4 figures. Accepted for publication in JA

Cognitive visual tracking and camera control

Cognitive visual tracking is the process of observing and understanding the behaviour of a moving person. This paper presents an efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario. Such a high-level feedback control loop, which is the main novelty of our work, will serve to reduce uncertainties in the observed scene and to maximize the amount of information extracted from it. It is implemented with a distributed camera system using SQL tables as virtual communication channels, and Situation Graph Trees for knowledge representation, inference and high-level camera control. A set of experiments in a surveillance scenario show the effectiveness of our approach and its potential for real applications of cognitive vision

An all-sky search algorithm for continuous gravitational waves from spinning neutron stars in binary systems

Rapidly spinning neutron stars with non-axisymmetric mass distributions are expected to generate quasi-monochromatic continuous gravitational waves. While many searches for unknown, isolated spinning neutron stars have been carried out, there have been no previous searches for unknown sources in binary systems. Since current search methods for unknown, isolated neutron stars are already computationally limited, expanding the parameter space searched to include binary systems is a formidable challenge. We present a new hierarchical binary search method called TwoSpect, which exploits the periodic orbital modulations of the continuous waves by searching for patterns in doubly Fourier-transformed data. We will describe the TwoSpect search pipeline, including its mitigation of detector noise variations and corrections for Doppler frequency modulation caused by changing detector velocity. Tests on Gaussian noise and on a set of simulated signals will be presented.Comment: 22 pages, 10 figures, 1 table, Submitted to Classical and Quantum Gravit