Synthesized N-Point Chopping Pattern Analysis of the Python Data

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Session 17 -- Instrumentation, Techniques and Surveys
Oral presentation, Monday, June 12, 1995, 2:00pm - 3:30pm

[17.04] Synthesized N-Point Chopping Pattern Analysis of the Python Data

D.L. Alvarez, M. Dragovan, J.E. Ruhl, J. Kovac, S.R. Platt, J. Peterson (Carnegie Mellon University, Princeton University, The University of Chicago)

We report initial results from a new analysis method for data taken with the Python microwave background anisotropy experiment.

The Python telescope performs a three-beam chop on the sky at multiple azimuth positions. The original analysis involved subtracting neighboring pairs of three-beam observations to produce a four-beam pattern on the sky.

This talk generalizes the original analysis in three ways and presents preliminary results of a reanalysis of the previous Python data.

First, we decompose the three-beam chop data into four independent modes. Two of these are signal modes which contain information from the sky. The other two are dark modes which have zero response to signals on the sky but non-zero response to instrumental effects.

Second, we allow more general methods of combining three-point observations (at neighboring azimuth positions and/or from independent detectors) to produce synthesized n-point chopping patterns.

Third, we synthesize n-beam chopping patterns which constitute optimal filters for estimating cosmological parameters.

This work was supported by the National Science Foundation under a cooperative agreement with the Center for Astrophysical Research in Antarctica (CARA), grant number NSF OPP 89-20223, M.D.'s PYI grant NSF AST 90-57089, and the James S. McDonnell Foundation. CARA is a National Science Foundation Science and Technology Center.

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