Configuration file
The configuration file is a Python file that allows to adjust several parameters of the run. The parameters that can be set in the configuration file are:
pta_data
-
Default:
'NG15'
– This variable needs to be assigned to a string specifying the PTA dataset which will be used in the analysis. The datasets currently implemented in PTArcade are NANOGrav 15-year (pta_data = "NG15"
), NANOGrav 12.5-year (pta_data = "NG12"
), and IPTA DR2 (pta_data = "IPTA2"
). N_samples
-
Default:
int(2e6)
– This variable can be assigned to an integer specifying the number of points that will be generated by the Monte Carlo sampler.Thinning
In order to reduce the autocorrelation length, the MC chains are automatically thinned by a factor of 10. Therefore, the number of MC samples that will be saved is given by
N_samples
/10. mode
-
Default:
ceffyl
– PTArcade can be run in two modes:-
mode = "enterprise"
: In this configuration, the code will analyze the full PTA dataset in the time domain by using the numerical techniques implemented in ENTERPRISE. -
mode = "ceffyl"
: In this configuration, the code will analyze PTA data at the level of the Bayesian peridograms (1), and fit the user-specified signal to these periodograms using the numerical techniques implemented in Ceffyl.- Probability density reconstructions of the pulsar-timing-residual power-spectral-density at each frequency (commonly referred to as the "violin plot"). See here for more details.
Ceffyl and Deterministic Signals
The Ceffyl mode can only be used to analyze stochastic signals. If your signal is deterministic, you have to run the code in ENTERPRISE-mode.
Additional Citations
If you use PTArcade in ENTERPRISE-mode, please add the following citations:
@misc{enterprise, author = {Justin A. Ellis and Michele Vallisneri and Stephen R. Taylor and Paul T. Baker}, title = {ENTERPRISE: Enhanced Numerical Toolbox Enabling a Robust PulsaR Inference SuitE}, month = sep, year = 2020, howpublished = {Zenodo}, doi = {10.5281/zenodo.4059815}, url = {https://doi.org/10.5281/zenodo.4059815} } @misc{enterprise-ext, author = {Stephen R. Taylor and Paul T. Baker and Jeffrey S. Hazboun and Joseph Simon and Sarah J. Vigeland}, title = {enterprise_extensions}, year = {2021}, url = {https://github.com/nanograv/enterprise_extensions}, note = {v2.3.3} }
If you use PTArcade in Ceffyl mode, please cite
@misc{lamb2023need, title={The Need For Speed: Rapid Refitting Techniques for Bayesian Spectral Characterization of the Gravitational Wave Background Using PTAs}, author={William G. Lamb and Stephen R. Taylor and Rutger van Haasteren}, year={2023}, eprint={2303.15442}, archivePrefix={arXiv}, primaryClass={astro-ph.HE} }
-
out_dir
-
Default:
'./chains/'
– This variable can be assigned to a string to specify the output directory. resume
-
Default:
False
– Ifresume = True
, the code will look for MCMC chains in the output directory and, if it finds any, it will restart sampling from those instead of starting from scratch. Ifresume = True
, but no chains are found in the output directory, the sampler will start from scratch.Warning
If
resume = False
(which is the default value), any chain that is present in the output directory at the start of your run will be overwritten. mod_sel
-
Default:
False
– PTArcade can also be used to compare new-physics interpretations of PTA signals against the astrophysical interpretation in terms of SMBHBs. Ifmod_sel = True
, a model-indexing variable controlling which model likelihood is active at each MCMC iteration will be sampled along with the parameters of the competing model. This will then allow to derive the Bayes factor between models by simply taking the ratio of samples spent in each bin of the model-indexing variable.Get the Bayes factor
After running with
mod_sel = True
, you can easily derive the Bayes factor using the functionget_bf
defined in the PTArcadechains_utils
module.Mod sel and Ceffyl
At the moment
mod_sel
can only be used withmode="enterprise"
. We are currently working on adding themod_sel
option to the Ceffyl-mode. corr
-
Default:
False
– This parameter controls the inter-pulsar correlations for any user-specified stochastic signal. Ifcorr=False
, spatial correlations between pulsars are set to zero and the overlap reduction function is taken to be a delta function in the pulsar space. Ifcorr=True
, Hellings & Downs correlations are assumed.Running time
When
mode = "enterprise"
, running withcorr = True
is approximately one order of magnitude slower than running withcorr = False
. If you want to run withcorr = True
, we suggest either usingmode = "ceffyl"
or running the code on a cluster.NG12 and IPTA2 in ceffyl mode
For the NANOGrav 12.5-year and IPTA DR2 data sets, the KDEs for the free spectra were derived only without spatial correlations (for these data sets the inclusion of pulsar-correlations is not expected to impact the spectral reconstruction significantly). Therefore, for these datasets, ceffyl mode can run only with
corr=False
. red_components
-
Default:
30
– This variable can be assigned to an integer specifying the number of frequency components that will be used to model intrinsic red noise. (1)- Intrinsic red noise is modeled using a Fourier basis of frequencies \(i/T_{\textrm{obs}}\),
where \(i\) indexes the harmonics of the basis and \(T_{\textrm{obs}}\) is the timing baseline. The
red_components
parameter sets the harmonics at which this expansion is truncated.
- Intrinsic red noise is modeled using a Fourier basis of frequencies \(i/T_{\textrm{obs}}\),
where \(i\) indexes the harmonics of the basis and \(T_{\textrm{obs}}\) is the timing baseline. The
gwb_components
-
Default:
14
– This variable can be assigned to an integer specifying the number of frequency components that will be used to model common red noise. (1)- The common red noise produced induced by a GWB is modeled using a Fourier basis of
frequencies \(i/T_{\textrm{obs}}\), where \(i\) indexes the harmonics of the basis and
\(T_{\textrm{obs}}\) is the timing baseline. The
gwb_components
parameter sets the harmonics at which this expansion is truncated.
Suggested Number of GWB Components
We suggest using
gwb_components = 13
.We suggest using
gwb_components = 5
.We suggest using
gwb_components = 14
. - The common red noise produced induced by a GWB is modeled using a Fourier basis of
frequencies \(i/T_{\textrm{obs}}\), where \(i\) indexes the harmonics of the basis and
\(T_{\textrm{obs}}\) is the timing baseline. The
As we already mentioned, the GWB signal specified by the user can be superimposed with the signal from SMBHBs or compared to it. The GWB signal from SMBHBs is modeled as a power-law:
The prior distributions for \(A_{\textrm{BHB}}\) and \(\gamma_{\textrm{BHB}}\) can be controlled with the following parameters in the configuration file:
bhb_th_prior
-
Default:
True
– Ifbhb_th_prior = True
, the prior for the SMBHB signal parameters will be chosen to reflect predictions from astrophysical models. This is only relevant if you have selectedsmbhb = True
in the model file ormod_sel = True
in the configuration file. (1) A_bhb_logmin
-
Default:
-18
– Can be assigned to a floating point or integer number to set the lower bound of the log-uniform prior for the SMBHB-signal amplitude. This is only relevant ifbhb_th_prior = False
and you have selectedsmbhb = True
in the model file ormod_sel = True
in the configuration file. A_bhb_logmax
-
Default:
-14
– Can be assigned to a floating point or integer number to set the upper bound of the log-uniform prior for the SMBHB-signal amplitude. This is only relevant ifbhb_th_prior = False
and you have selectedsmbhb = True
in the model file ormod_sel = True
in the configuration file. gamma_bhb
-
Default:
None
– Can be assigned to a floating point or integer number to set the value of \(\gamma_{\textrm{BHB}}\). Ifgamma_bhb = None
, a uniform prior between \(0\) and \(7\) will be used instead.
Default Configuration File
If no configuration file is specified by the user, the following file will be used instead