Coherent integrations, fringe modeling, and bootstrapping with the NPOI

Details Coherent integrations, fringe modeling, and bootstrapping with the NPOI Coherent integrations, fringe modeling, and bootstrapping with the NPOI

Jul 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006spie.6268e..47j&link_type=abstract

Advances in Stellar Interferometry. Edited by Monnier, John D.; Schöller, Markus; Danchi, William C.. Proceedings of the SPIE,

Computer Science

2

Scientific paper

Atmospheric turbulence is a major impediment to ground-based optical interferometry. It causes fringes to move on ms time-scales, forcing very short exposures. Because of the semi-random phase shifts, the traditional approach averages exposure power spectra to build signal-to-noise ratio (SNR). This incoherent average has two problems: (1) A bias of correlated noise is introduced which must be subtracted. The smaller the visibility/the fainter the target star, the more diffcult bias subtraction becomes. SNR builds only slowly in this case. Unfortunately, these most difficult small visibility baselines contain most of the image information. (2) Baseline phase information is discarded. These are serious challenges to imaging with ground based optical interferometers. But if we were able to determine fringe phase, we could shift and integrate all the short exposures. We would then eliminate the bias problem, improve the SNR, and we would have preserved most of the phase information. This coherent averaging becomes possible with multi-spectral measurements. The group delay presents one option for determining phase. A more accurate approach is to use a time-dependent model of the fringe. For the most interesting low-visibility baselines, the atmospheric phase information can be bootstrapped from phase determinations on high-visibility baselines using the closure relation. The NPOI, with 32 spectral channels and a bootstrapping configuration, is well-suited for these approaches. We will illustrate how the fringe modeling approach works, compare it to the group-delay approach, and show how these approaches can be used to derive bias-free visibility amplitude and phase information. Coherent integration provides the highest signal-to-noise (SNR) improvement precisely in the situations where SNR builds most slowly using incoherent averaging. Coherent integration also produces high-SNR phase measurements which are calibration-free and thus have high real uncertainties as well. In this paper we will show how to coherently integration on NPOI data, and how to use baseline visibilities and calibrate coherently integrated visibility amplitudes.

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