AMiBA is the largest hexapod astronomical telescope in current operation. We present a description of this novel hexapod mount with its main mechanical components -- the support cone, universal joints, jack screws, and platform -- and outline the con
trol system with the pointing model and the operating modes that are supported. The AMiBA hexapod mount performance is verified based on optical pointing tests and platform photogrammetry measurements. The photogrammetry results show that the deformations in the inner part of the platform are less than 120 micron rms. This is negligible for optical pointing corrections, radio alignment and radio phase errors for the currently operational 7-element compact configuration. The optical pointing error in azimuth and elevation is successively reduced by a series of corrections to about 0.4 arcmin rms which meets our goal for the 7-element target specifications.
We describe methods used to validate data from the Y.T. Lee Array for Microwave Background Anisotropy (AMiBA), an interferometric array designed to measure the Sunyaev-Zeldovich effect and the anisotropy of the Cosmic Microwave Background (CMB). We p
erform several statistical tests on data from pointed galaxy cluster observations taken in 2007 and noise data from long-term blank sky observations and measurements with the feeds covered by the absorbers. We apply power spectrum analysis, cross power spectrum analysis among different outputs with different time lags in our analog correlator, and sample variance law tests to noise data. We find that (1) there is no time variation of electronic offsets on the time scale of our two-patch observations (~10 minutes); (2) noise is correlated by less than 10% between different lags; and (3) the variance of noise scales with the inverse of time. To test the Gaussianity of the data, we apply Kolmogorov-Smirnov (K-S) tests to cluster data, and find that a 5% significance level efficiently detects data sets with known hardware problems without rejecting an excess of acceptable data. We also calculate third- and fourth-order moments and cumulants for the noise residual visibilities and find that about 95% of our data are within the 99% confidence regions of Gaussianity.
