weighting-and-high-frequency-noise.html

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         title="Permalink to Weighting and high-frequency noise">Weighting and high-frequency noise</a></h2>
 
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    <abbr class="published" title="2008-11-15T00:41:00-07:00">
      2008/11/15
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      By <a class="url fn" href="https://keflavich.github.io/blog/author/adam-adamgginsburggmailcom.html">Adam (adam.g.ginsburg@gmail.com)</a>
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    <img alt="" src="http://1.bp.blogspot.com/_lsgW26mWZnU/SR4DzVCz1WI/AAAAAAAADfk/cJ70OPeqEzg/s400/psds.png" />
<p>Image of PSDs (with no normalization) of the raw (blue), delined and
exponential and polynomial subtracted (white), the noise timestream
(yellow), and the data (cyan).
The good: It looks like all of the powerline noise got into the noise
timestream and almost none in the data.
The bad: weighting is based on the noise timestream so it's possible
that the weights aren't quite right as a result
The weird: the data PSD. What's up with that? Apparently I'm
preferentially subtracting certain scales but I don't know why, unless
deconvolution is at fault.
Edit/Update: The deconvolution is definitely at fault. Here's the same
scan done without deconvolution:</p>
<img alt="" src="http://3.bp.blogspot.com/_lsgW26mWZnU/SR4ZM6FPfrI/AAAAAAAADf0/baHOQwedeqs/s400/psds2.png" />
<p>It should have been obvious; the cyan in the first plot is the PSD of
the deconvolution straight up, and that should have no high-frequency
structure...</p>

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