[en] We investigate the contamination of the Sunyaev-Zel'dovich (SZ) effect for six galaxy clusters, A1689, A1995, A2142, A2163, A2261, and A2390, observed by the Y. T. Lee Array for Microwave Background Anisotropy in 2007. With the range of baselines used, we find that the largest effect (of order 13%-50% of the central SZ flux density) comes from primary anisotropies in the cosmic microwave background and exceeds the thermal noise in all six cases. Contamination from discrete radio sources is estimated to be at a level of 3%-60% of the central SZ flux density. We use the statistics of these contaminating sources to estimate and correct the errors in the measured SZ effects of these clusters.

[en] The Yuan-Tseh Lee Array for Microwave Background Anisotropy (AMiBA) is a co-planar interferometer array operating at a wavelength of 3 mm to measure the Sunyaev–Zel’dovich effect (SZE) of galaxy clusters at arcminute scales. The first phase of operation—with a compact 7-element array with 0.6 m antennas (AMiBA-7)—observed six clusters at angular scales from $5^{\mathrm{\prime <!--\; ???\; -->}}$ to ${23}^{\mathrm{\prime <!--\; ???\; -->}}$. Here, we describe the expansion of AMiBA to a 13-element array with 1.2 m antennas (AMiBA-13), its subsequent commissioning, and cluster SZE observing program. The most noticeable changes compared to AMiBA-7 are (1) array re-configuration with baselines ranging from 1.4 m to 4.8 m, allowing us to sample structures between $2^{\mathrm{\prime <!--\; ???\; -->}}$ and ${10}^{\mathrm{\prime <!--\; ???\; -->}}$, (2) 13 new lightweight carbon-fiber-reinforced plastic (CFRP) 1.2 m reflectors, and (3) additional correlators and six new receivers. Since the reflectors are co-mounted on and distributed over the entire six-meter CFRP platform, a refined hexapod pointing error model and phase error correction scheme have been developed for AMiBA-13. These effects—entirely negligible for the earlier central close-packed AMiBA-7 configuration—can lead to additional geometrical delays during observations. Our correction scheme recovers at least 80 ± 5% of the point-source fluxes. We, therefore, apply an upward correcting factor of 1.25 to our visibilities to correct for phase decoherence, and a ±5% systematic uncertainty is added in quadrature with our statistical errors. We demonstrate the absence of further systematics with a noise level consistent with zero in stacked uv-visibilities. From the AMiBA-13 SZE observing program, we present here maps of a subset of 12 clusters with signal-to-noise ratios above five. We demonstrate combining AMiBA-7 with AMiBA-13 observations on Abell 1689, by jointly fitting their data to a generalized Navarro–Frenk–White model. Our cylindrically integrated Compton-y values for five radii are consistent with results from the Berkeley-Illinois-Maryland Array, the Owens Valley Radio Observatory, the Sunyaev–Zel’dovich Array, and the Planck Observatory. We also report the first targeted SZE detection toward the optically selected cluster RCS J1447+0828, and we demonstrate the ability of AMiBA SZE data to serve as a proxy for the total cluster mass. Finally, we show that our AMiBA-SZE derived cluster masses are consistent with recent lensing mass measurements in the literature.

[en] We investigate the scaling relations between the X-ray and the thermal Sunyaev-Zel'dovich effect properties of clusters of galaxies, using data taken during 2007 by the Y. T. Lee Array for Microwave Background Anisotropy (AMiBA) at 94 GHz for the six clusters A1689, A1995, A2142, A2163, A2261, and A2390. The scaling relations relate the integrated Compton-y parameter Y ₂₅₀₀ to the X-ray-derived gas temperature T _e, total mass M ₂₅₀₀, and bolometric luminosity L_X within r ₂₅₀₀. Our results for the power-law index and normalization are both consistent with the self-similar model and other studies in the literature except for the Y ₂₅₀₀-L_X relation, for which a physical explanation is given though further investigation may be still needed. Our results not only provide confidence for the AMiBA project but also support our understanding of galaxy clusters.

[en] Clusters of galaxies have been extensively used to determine cosmological parameters. A major difficulty in making the best use of Sunyaev-Zel'dovich (SZ) and X-ray observations of clusters for cosmology is that using X-ray observations it is difficult to measure the temperature distribution and therefore determine the density distribution in individual clusters of galaxies out to the virial radius. Observations with the new generation of SZ instruments are a promising alternative approach. We use clusters of galaxies drawn from high-resolution adaptive mesh refinement cosmological simulations to study how well we should be able to constrain the large-scale distribution of the intracluster gas (ICG) in individual massive relaxed clusters using AMiBA in its configuration with 13 1.2 m diameter dishes (AMiBA13) along with X-ray observations. We show that non-isothermal β models provide a good description of the ICG in our simulated relaxed clusters. We use simulated X-ray observations to estimate the quality of constraints on the distribution of gas density, and simulated SZ visibilities (AMiBA13 observations) for constraints on the large-scale temperature distribution of the ICG. We find that AMiBA13 visibilities should constrain the scale radius of the temperature distribution to about 50% accuracy. We conclude that the upgraded AMiBA, AMiBA13, should be a powerful instrument to constrain the large-scale distribution of the ICG.

[en] This work describes cosmic microwave background (CMB) data analysis algorithms and their implementations, developed to produce a pixelized map of the sky and a corresponding pixel-pixel noise correlation matrix from time ordered data for a CMB mapping experiment. We discuss in turn algorithms for estimating noise properties from the time ordered data, techniques for manipulating the time ordered data, and a number of variants of the maximum likelihood map-making procedure. We pay particular attention to issues pertinent to real CMB data, and present ways of incorporating them within the framework of maximum likelihood map making. Making a map of the sky is shown to be not only an intermediate step rendering an image of the sky, but also an important diagnostic stage, when tests for and/or removal of systematic effects can efficiently be performed. The case under study is the MAXIMA-I data set. However, the methods discussed are expected to be applicable to the analysis of other current and forthcoming CMB experiments