Understanding synthesis imaging dynamic range

We develop a general framework for quantifying the many different contributions to the noise budget of an image made with an array of dishes or aperture array stations. Each noise contribution to the visibility data is associated with a relevant correlation timescale and frequency bandwidth so that the net impact on a complete observation can be assessed. All quantities are parameterised as function of observing frequency and the visibility baseline length. We apply the resulting noise budget analysis to a wide range of existing and planned telescope systems that will operate between about 100 MHz and 5 GHz to ascertain the magnitude of the calibration challenges that they must overcome to achieve thermal noise limited performance. We conclude that calibration challenges are increased in several respects by small dimensions of the dishes or aperture array stations. It will be more challenging to achieve thermal noise limited performance using 15 m class dishes rather than the 25 m dishes of current arrays. Some of the performance risks are mitigated by the deployment of phased array feeds and more with the choice of an (alt,az,pol) mount, although a larger dish diameter offers the best prospects for risk mitigation. Many improvements to imaging performance can be anticipated at the expense of greater complexity in calibration algorithms. However, a fundamental limitation is ultimately imposed by an insufficient number of data constraints relative to calibration variables. The upcoming aperture array systems will be operating in a regime that has never previously been addressed, where a wide range of effects are expected to exceed the thermal noise by two to three orders of magnitude. Achieving routine thermal noise limited imaging performance with these systems presents an extreme challenge. The magnitude of that challenge is inversely related to the aperture array station diameter.Comment: 27 pages, 24 figures, accepted in A&A, final versio

Importance driven environment map sampling

In this paper we present an automatic and efficient method for supporting Image Based Lighting (IBL) for bidirectional methods which improves both the sampling of the environment, and the detection and sampling of important regions of the scene, such as windows and doors. These often have a small area proportional to that of the entire scene, so paths which pass through them are generated with a low probability. The method proposed in this paper improves this by taking into account view importance, and modifies the lighting distribution to use light transport information. This also automatically constructs a sampling distribution in locations which are relevant to the camera position, thereby improving sampling. Results are presented when our method is applied to bidirectional rendering techniques, in particular we show results for Bidirectional Path Tracing, Metropolis Light Transport and Progressive Photon Mapping. Efficiency results demonstrate speed up of orders of magnitude (depending on the rendering method used), when compared to other methods

Coherent imaging of a pure phase object with classical incoherent light

By using the ghost imaging technique, we experimentally demonstrate the reconstruction of the diffraction pattern of a {\em pure phase} object by using the classical correlation of incoherent thermal light split on a beam splitter. The results once again underline that entanglement is not a necessary feature of ghost imaging. The light we use is spatially highly incoherent with respect to the object ($\approx 2 \mu$m speckle size) and is produced by a pseudo-thermal source relying on the principle of near-field scattering. We show that in these conditions no information on the phase object can be retrieved by only measuring the light that passed through it, neither in a direct measurement nor in a Hanbury Brown-Twiss (HBT) scheme. In general, we show a remarkable complementarity between ghost imaging and the HBT scheme when dealing with a phase object.Comment: 13 pages, 11 figures. Published in Physical Review A. Replaced version fixes some problems with Figs. 1, 4 and 1

Compressed sensing imaging techniques for radio interferometry

Radio interferometry probes astrophysical signals through incomplete and noisy Fourier measurements. The theory of compressed sensing demonstrates that such measurements may actually suffice for accurate reconstruction of sparse or compressible signals. We propose new generic imaging techniques based on convex optimization for global minimization problems defined in this context. The versatility of the framework notably allows introduction of specific prior information on the signals, which offers the possibility of significant improvements of reconstruction relative to the standard local matching pursuit algorithm CLEAN used in radio astronomy. We illustrate the potential of the approach by studying reconstruction performances on simulations of two different kinds of signals observed with very generic interferometric configurations. The first kind is an intensity field of compact astrophysical objects. The second kind is the imprint of cosmic strings in the temperature field of the cosmic microwave background radiation, of particular interest for cosmology.Comment: 10 pages, 1 figure. Version 2 matches version accepted for publication in MNRAS. Changes includes: writing corrections, clarifications of arguments, figure update, and a new subsection 4.1 commenting on the exact compliance of radio interferometric measurements with compressed sensin