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Sensitivity quantile distributions\
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Cell["\<\

Michele Vallisneri and Chad R. Galley, Jan 17 2012\
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Jet Propulsion Laboratory, California Insitute of Technology
Copyright 2012. All rights reserved.
\
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Cell["\<\
This notebook may be used to compute the distribution of squared-SNRs and \
sensitivities to monochromatic gravitational wave sources distributed either \
isotropically or in a Galactic disk (for several models). The last section \
below gives an example of how to run the code. The previous sections are \
mostly function definitions for the motion of the spacecraft, the single-link \
response, various TDI observables and noises, and the code for Monte Carlo \
simulations of squared-SNRs and sensitivities for a given distribution of \
monochromatic sources. See Vallisneri & Galley (2012) for further exposition. 

The code may be extended to include chirp waveforms of inspiraling binaries, \
horizon distance computations, other source distributions and polarizations \
(e.g., Poincare), and alternative spacecraft configurations and orbits.\
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Define a stationary LISA. n vectors (i=1,...3) are light-propagation \
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Following Kr\[OAcute]lak A, Tinto M and Vallisneri M 2004 Phys. Rev. D 70 \
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Cell["\<\
Running the code:  An example for stationary LISA and a Galactic population \
of monochromatic sources\
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Cell["\<\
Draw 1000 samples from a population of monochromatic sources from the \
Galactic-disk. (We use 10^5 sources in the paper so, here, the statistics \
will not be as good.)\
\>", "Text",
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Cell["\<\
For the sensitivity of a single, monochromatic source (say, the first one of \
the above 1000 sources) one would execute the following:\
\>", "Text",
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Cell["\<\
More specifically, this would be the optimal squared-SNR for the observable \
X, including the partially subtracted Galactic WD noise, for the case when \
LISA is moving. The corresponding sensitivity plotted as a function of the \
frequency (fs, defined in section `Building table of frequency abscissae\
\[CloseCurlyQuote]) relative to a threshold squared-SNR of 5 is then \
\>", "Text",
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Computing the squared-SNRs of all the 1000 samples generated above can be \
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The corresponding sensitivities are, for a threshold SNR of 5 (not \
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 "There is a lot of information contained in ",
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 " but a convenient representation for all 1000 sources is via quantiles. For \
example, let\[CloseCurlyQuote]s plot the 5% and 95% quantiles (upper and \
lower red curves, respectively) along with the median (dashed black) and mean \
(solid black) curves using the inverse-RMS, as discussed in the paper. The \
plot below thus shows the spread in sensitivity of 90% of the sampled sources."
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(* End of internal cache information *)