[Users] Gravitational wave plot

Haas, Roland rhaas at illinois.edu
Sun Jan 27 17:52:44 CST 2019


Hello Meraj,

> I have succeeded to perform BBH simulation using
> "inspiral_qc0_d06_lres.par" file and the sketch of black hole tracks has
> also plotted. How can I plot its related gravitational wave?
I have not run the parfile myself, so please take the file names that I
give as "approximate", though I have tried to be accurate by looking up
the source code and parfile from the repo.

You can find gravitational wave data (the Weyl scalar Psi4) in the
files mp_Psi4_l2_m2_r100.asc which contains 3 columns of data: "time",
the real part of the 2,2 spherical harmonic mode of psi4 and the
imaginary part all extracted on a coordinate sphere of radius 100.

The files mp_Psi4_l2_m2_r80 and _r60 contain data extracted at radii 80
and 60 respectively. The other _lL_mM files contain different modes of
the gravitational waves.

To compute gravitational wave strain "h" you will have to integrate
psi4 twice (ideally the asymptotic value of r*psi4 at infinite distance
from the source). 

The relation is (up to an overall sign and me mixing up + and x
polarizations):

\ddot h_x - i \ddot h_= = \psi4

If you have access to Mathematica then please take a look at the
tutorial for the LIGO detction GW150914:
https://www.einsteintoolkit.org/gallery/bbh/index.html

You an also try PyCactusET:
https://bitbucket.org/DrWhat/pycactuset/src/default/PostCactus/ see its example notebook on gravitational waves:

https://bitbucket.org/DrWhat/pycactuset/src/default/PostCactus/doc/examples/notebooks/pc_example_gw.ipynb

or as a preview:

https://nbviewer.jupyter.org/urls/bitbucket.org/DrWhat/pycactuset/raw/feba8a56ae429430f8b196095945b0ed4e81aa82/PostCactus/doc/examples/notebooks/pc_example_gw.ipynb

Otherwise you can also use pyGWAnalysis:
https://svn.einsteintoolkit.org/pyGWAnalysis/trunk/ which can also do the integration (see https://svn.einsteintoolkit.org/pyGWAnalysis/trunk/Examples/integrate-modes-ffi.py ). f0 is some guess for the lowest expected frequency in the data. Likely for just an experiment you can leave it as is since the qc0 run is much shorter than what was (likely) used in the example.

Both SimulationTools and PyCactusET usually use the same integration
method at pyGWAnalysis (though they may offer alternatives as well).

Yours,
Roland

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