NX01

Python code to perform isotropic, anisotropic (non-evolving/evolving) searches for gravitational-waves via pulsar-timing.

Perhaps you want the webpage?

Code list

• NX01_master.py: performs a full evolving-anisotropy GWB and noise analysis. Uses MultiNest or parallel-tempering sampling.
• NX01_singlePsr.py: performs a stochastic search for single-pulsar noise parameters within the reduced-rank time-frequency approximation. Uses MultiNest or parallel-tempering sampling.
• NX01_AnisCoefficients.py: utility file to create power-anisotropy basis-functions.
• NX01_utils.py: utility file.
• NX01_plot.py: plotting package, adapted and extended from PAL.
• NX01_psr.py: utility file which defines the pulsar class for storing all relevant variables.
• NX01_datafile.py: creates an hdf5 container to store all the information in the pulsar class. Useful for storing array products.
• NX01_jitter.pxy: cython code to perform Sherman-Morrison block noise-matrix inversions when handling ECORR (jitter).
• NX01_bayesutils.py: utilities file for generating plotting data.

Preliminaries

One important first thing to note is to make sure you have correctly updated your tempo2 clock files with the corresponding files packaged with the NANOGrav data download.

It is recommended that you initially open and follow the steps in the nanograv-pulsar-store.ipynb notebook, and produce your own PsrListings_GWB.txt and PsrListings_CW.txt. These latter files are lists of pulsars in the order with which they contribute to the stochastic background upper limit (_GWB.txt) and the single-source SNR (_CW.txt). Each pulsar is associated with a path to an hdf5 file (storing all pulsar properties), parfile, and timfile.

By following the steps in the notebook (only up until the cross-validation plotting between NX01 and PAL2) you will produce your own hdf5 files, which you should put in a directory of your choice. These hdf5 files will store everything you need for subsequent GW searches. Another important step in the notebook is to produce par files which are stripped of tempo2 EFAC, EQUAD, ECORR, RedAmp, and RedInd values. These values are replaced by mean values from Justin's previous single-pulsar analyses.

Single-pulsar noise analysis

It should be straightforward to perform a single-pulsar noise analysis out of the box.

Run python NX01_singlePsr.py --help for a list of all options.

An example run command would be:

python NX01_singlePsr.py
--parfile=./NANOGrav_9y/par/J1713+0747_NANOGrav_9yv1.t2.gls.strip.par
--timfile=./NANOGrav_9y/tim/J1713+0747_NANOGrav_9yv1.tim
--efacequad-sysflag=f --fullN --ptmcmc

Without the --ptmcmc option, the sampler will default to MultiNest.

If you have MPI installed you can parallelise by running the following:

mpirun -np 4 NX01_singlePsr.py
--parfile=./NANOGrav_9y/par/J1713+0747_NANOGrav_9yv1.t2.gls.strip.par
--timfile=./NANOGrav_9y/tim/J1713+0747_NANOGrav_9yv1.tim
--efacequad-sysflag=f --fullN --ptmcmc

where 4 cores will produce 4 temperature chains in the parallel-tempering MCMC sampling process. Without the --ptmcmc command, 4 cores would have been used to update the live points in MultiNest.

Gravitational-wave searches

It is recommended to read in pulsars from their respective hdf5 files, which you should have previously produced from the nanograv-pulsar-store.ipynb notebook.

Run python NX01_master.py --help for a list of all options.

An example run command would be:

python NX01_master.py --from-h5
--psrlist=./PsrListings_GWB.txt --nmodes=15
--incGWB --fix-slope --num_psrs=18 --fullN

which will perform a GW background upper-limit analysis (without correlations...to include correlations add --incCorr) on the 18 pulsars analyzed in the 9-year NANOGrav limit paper.

As in the single-pulsar analysis case, you can use MPI for the PTMCMC, however MultiNest functionality is not yet ready.