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9 results for “NANOGrav”
The NANOGrav 12.5-year Wideband Data Set (version 12yv4)
<p>The NANOGrav 12.5-year wideband data set (public release "12yv4") is the supplemental data set accompanying Alam et al. 2021, "The NANOGrav 12.5 yr Data Set: Wideband Timing of 47 Millisecond Pulsars," The Astrophysical Journal Supplement Series, 252, 5, DOI 10.3847/1538-4365/abc6a1. It contains wideband pulse times of arrival, models describing frequency-dependent template profiles, pulsar timing models, timing residuals, and clock files.</p> <p>Details about the contents of these files are contained in NANOGrav_12yv4_wideband/README, as well as in NANOGrav_12yv4_wideband/wideband/README.wideband. The narrowband version of this dataset (published in Alam et al. 2021, ApJS, 252, 4, DOI: 10.3847/1538-4365/abc6a0) can be found at Zenodo DOI: 10.5281/zenodo.4312297. Both the narrowband and wideband data sets are also available at <a href="http://data.nanograv.org">data.nanograv.org</a>.</p>
Single-pulsar search for eccentric SMBHBs using NANOGrav 12.5-year data of PSR J1909--3744: Posterior samples
<p>This repository contains posterior samples for a Bayesian single-pulsar search for nanohertz gravitational waves originating from eccentric supermassive binaries, done using the NANOGrav 12.5-year dataset for PSR J1909-3744. The analysis is presented in Susobhanan 2023 [https://arxiv.org/abs/2210.11454].</p>
The NANOGrav 12.5-year Narrowband Data Set (version 12yv4)
<p>The NANOGrav 12.5-year narrowband data set (public release "12yv4") is the supplemental data set accompanying Alam et al. 2021, "The NANOGrav 12.5 yr Data Set: Observations and Narrowband Timing of 47 Millisecond Pulsars," 2021, Astrophysical Journal Supplements, 252, 4, DOI: 10.3847/1538-4365/abc6a0. It contains narrowband pulse times of arrival, one-dimensional pulse templates, pulsar timing models, timing residuals, and clock files.</p> <p>Details about the contents of these files are contained in NANOGrav_12yv4_narrowband/README, as well as in NANOGrav_12yv4_narrowband/narrowband/README.narrowband. The wideband version of this dataset (published in Alam et al. 2021, ApJS, 252, 5, DOI: 10.3847/1538-4365/abc6a1) can be found at Zenodo DOI: 10.5281/zenodo.4312887. Both the narrowband and wideband data sets are also available at data.nanograv.org.</p> <p>Analysis of the 12.5-year narrowband dataset will be published in Arzoumanian et al. 2021, "The NANOGrav 12.5-year Data Set: Search for an Isotropic Gravitational-Wave Background," accepted for publication in ApJ Letters, 2020arXiv200904496A.</p>
Continuous Wave Analysis of the NANOGrav 15-Year Dataset
<p>This repository contains the data used in the analysis detailed within "<em>The NANOGrav 15-year Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries</em>" (DOI <a href="https://arxiv.org/abs/2306.16222">arXiv:2306.16222</a>). It also provides instruction on how one could reproduce those results on their own.</p> <ul> <li><code>jar</code> folder: contains pickled <code>enterprise</code> pulsar objects that contain each pulsar's TOA data and timing model information</li> <li><code>v1p1_all_dict.json</code>: dictionary with measured white noise and red noise parameters for each pulsar - used to fix white noise parameters when running QuickCW</li> <li><code>emp_dist_15yr_v1p1_bence_my_run_v4.3.pkl</code>: <code>enterprise_extension</code> <code>EmpiricalDistribution2D</code> objects for the amplitude and spectral index of each pulsar's red noise - used to make informed red noise proposals when running QuickCW</li> <li><code>pulsar_distances_15yr.pkl</code>: dictionary containing 3 element list for each pulsar specifying its distance [kpc], statistical error of distance [kpc], and method of distance measurement [PX for parallax or DM for dispersion measure]</li> <li><code>15yr_quickCW_detection.h5</code>: HDF5 file containing results from QuickCW detection runs (log uniform amplitude prior). Includes the following data: <ul> <li>MCMC samples (<code>samples_cold</code>)</li> <li>log likelihood values corresponding to those samples (<code>log_likelihood</code> )</li> <li>temperature ladder used for the parallel tempering (<code>Ts</code>)</li> <li>names of parameters corresponding to each column in the samples array (<code>par_names</code>)</li> <li>rate of different MCMC jumps being accepted (<code>acc_fraction</code>)</li> <li>diagonal fisher matrix used for some proposals (<code>fisher_diag</code>)</li> </ul> </li> <li><code>15yr_quickCW_UL.h5</code>: Same as <code>15yr_quickCW_detection.h5</code> but for upper limits based on runs with uniform amplitude prior.</li> <li><code>15yr_cw_3d_limits_v4.npz</code>: npz file containing limits as a function of frequency and sky location. Specifically it has the following arrays: <ul> <li><code>F_edges</code>: array specifying the edges of the frequency bins</li> <li><code>strain_limit_skies</code>: 2D array containing the strain upper limits as a function of frequency bin and sky pixel</li> <li><code>strain_limit_sky_sigmas</code>: 2D array containing 1-sigma statistical errors on the strain upper limits</li> <li><code>dist_limit_skies</code>: 2D array containing the luminosity distance limits in Mpc as a function of frequency bin and sky pixel</li> <li><code>dist_limit_sky_sigmas</code>: 2D array containing 1-sigma statistical errors on the distance limits in Mpc</li> </ul> </li> </ul>
The NANOGrav 15-Year Data Set
<pre><strong>The NANOGrav 15-Year Data Set Public release "v2.1.0" 2025/07/17</strong> <strong>OVERVIEW</strong> -------- This file contains "narrowband" and "wideband" TOAs and timing solutions for the NANOGrav 15-year data set, covering data taken from 2004 to mid-2020 using Arecibo, the Green Bank Telescope (GBT), and the Very Large Array (VLA) with ASP/GASP and PUPPI/GUPPI/YUPPI backend instrumentation. The observations, data reduction, and analysis procedures used to produce these data are described in detail in the accompanying paper, "The NANOGrav 15-year Data Set: Observations and Timing of 68 Millisecond Pulsars" (Agazie et al., 2023, ApJL 951 L9, DOI 10.3847/2041-8213/acda9a, arXiv:2306.16217).<br> This release is available at Zenodo (DOI 10.5281/zenodo.16051178).<br>You can also reference all versions (DOI 10.5281/zenodo.7967584). All *.par and *.tim files are ASCII and are formatted for use with standard pulsar timing packages such as tempo2 and PINT, except for profile template files which are FITS format (narrowband) or python pickle files (wideband).<br><br> For our narrowband results, we have included ASCII space-separated <br>tables of our post-fit timing model residuals for all of our pulsars <br>(both un-whitened and whitened). These are available as both full <br>and epoch-averaged formats. Correlation matrix files are available in three formats (*.txt, *.npz, and *.hdf5). See "description.txt" in both the narrowband and wideband ./correlations subdirectories for more details about these files. Questions about the contents of this data set can be addressed to Joe Swiggum (swiggumj@gmail.com) or comments@nanograv.org. <strong>DIRECTORY AND FILE STRUCTURE (FURTHER DETAILS BELOW)</strong> --------------------------------------------------- ./README This file. ./clock Files for tracing observatory-measured TOAs to clock standards. ./narrowband Directory containing the narrowband data set. Details are provided in README.narrowband in that directory. ./wideband Directory containing the wideband data set. Details are provided in README.wideband in that directory. ./correlations Directory containing the correlation matrix files for both the narrowband and wideband data. Details are provided in the /wideband/ and /narrowband/ subdirectories' description.txt files. <strong>SOFTWARE</strong> -------- This data set requires up-to-date installations of PINT or tempo2. Our original analysis used PINT v0.9.1 and tempo2 v2022.01.1. Up to date versions of these packages, as well as usage information and documentation can be found at the following repositories: PINT https://github.com/nanograv/PINT tempo2 https://bitbucket.org/psrsoft/tempo2 Note that we do not guarantee complete/correct functionality of these timing models in the older original tempo software package. Please also ensure that the clock files you are using cover the full range of the data set. Using the provided clock files (see below) will ensure this. All models included here are based on a generalized least squares (GLS) fit that includes a noise model with covariance between TOAs (ECORR/jitter parameters, if narrowband; RNAMP/RNIDX red noise parameters, if significant), as well as "traditional" EQUAD and EFAC parameters. Additional EFAC parameters for the wideband DM measurements are also included. All noise model parameters are included in the par files. <strong>CLOCK FILES</strong> ----------- The clock files used for our analysis are provided in the clock/ subdirectory. While the standard files distributed with tempo and tempo2 should be consistent with the clock files provided in the current release at the time of writing, this may be a source of inconsistent results in the future. Please see ./clock/README.clock directory for installation instructions. <strong>PLANNED REVISIONS</strong> ----------------- The initial release of the data set contained all fundamental data<br>products needed for pulsar timing analysis: Times of arrival (.tim<br>files), timing models (.par files), standard template profiles,<br>clock correction files, and noise modeling MCMC chains. In v2,<br>parameter correlation matrices were added, as well as alternate versions<br>of timing model parameter files ("NoRedNoise" and "predictive"). In v2.1, <br>post-fit timing residuals for our narrowband data set were made available. <br>A future release will add a number of other useful derived products as <br>mentioned in the paper, including dispersion measure time series. <strong>CHANGE LOG</strong> ----------<br>2025/07/17<br> Addition of the Timing Model Residual files for the <br> narrowband dataset, including overview plots (v2.1.0). 2023/09/19 Addition of "NoRedNoise" and "predictive" par files, correlation matrices, noise modeling chains (v2). 2023/07/01 Correction to tar.gz directory structure (v1.0.1). 2023/06/28 Initial public release (v1).</pre>
KDE Representations of the Gravitational Wave Background Free Spectra Present in the NANOGrav 15-Year Dataset
<p><i><strong>OVERVIEW</strong></i></p><p><i><strong>----------------</strong></i></p><p>This is a downloadable file of probability densities from KDEs (Kernel Density Estimator) of free spectrum analyses of the NANOGrav 15yr Dataset (DOI <a href="https://doi.org/10.5281/zenodo.7967584">10.5281/zenodo.7967584</a>) that can be used with the <a href="https://github.com/astrolamb/ceffyl">Ceffyl</a> and <a href="https://github.com/andrea-mitridate/PTArcade">PTArcade</a> packages. Please see the GitHub page for Ceffyl/PTArcade installation details and usage information.<br><br>Details on how this data product was produced can be found in <a href="https://journals.aps.org/prd/abstract/10.1103/PhysRevD.108.103019"><i>Lamb, Taylor & van Haasteren 2023 (DOI 10.1103/PhysRevD.108.103019).</i></a></p><p><i><strong>DIRECTORY AND FILE STRUCTURE</strong></i></p><p><i><strong>----------------------------------------------------</strong></i></p><p>Each directory contains a file with log-pdfs representing their corresponding free spectra (`density.npy`), the frequencies at which they were analysed (`freqs.npy`), the grid-points at which each log-pdf was computed (`log10rhogrid.npy`), frequency labels (`log10rholabels.txt`), analysis label (`pulsar_list.txt`), an array of bandwidths computed using the Sheather-Jones method (see Lamb et al. 2023; 'bandwidths.npy'), and a file with some metadata about the data (`log.txt`).</p><p>./30f_fs{cp}_ceffyl </p><ul><li>A representation of a 30 frequency CURN free spectrum.</li></ul><p>./30f_fs{hd}_ceffyl</p><ul><li>A representation of a 30 frequency HD-correlated free spectrum</li></ul><p>./30f_fs{hd+mp+dp}_ceffyl_hd-only</p><ul><li>A representation of an analysis that simultaneously modeled a HD-correlated free spectrum, a MP-correlated free spectrum, and a DP-correlated free spectrum. Only the HD component is represented here.</li></ul><p>./30f_fs{hd+mp+dp+cp}_ceffyl_hd-only</p><ul><li>A representation of an analysis that simultaneously modeled a HD-correlated free spectrum, a MP-correlated free spectrum, a DP-correlated free spectrum, and a CURN free spectrum. Only the HD component is represented here.</li></ul><p>./README</p><ul><li>this is a readme</li></ul><p><i><strong>SOFTWARE</strong></i></p><p><i><strong>------------------</strong></i></p><p>This data should ideally be used with the latest versions of:</p><ul><li><i><strong>ceffyl</strong></i> (https://github.com/astrolamb/ceffyl)</li><li><i><strong>PTArcade </strong></i>(https://github.com/andrea-mitridate/PTArcade)</li></ul><p><i><strong>PLANNED REVISIONS</strong></i></p><p><i><strong>---------------------------------</strong></i></p><p>None</p><p><i><strong>CHANGE LOG</strong></i></p><p><i><strong>----------------------</strong></i></p><p>10/12/2023 - updated KDE representations</p><p>A bug was found that produced a poor reflection at the lower prior boundary. Hence, data was being represented well at the lower prior boundary. This has now been corrected.</p>
Data Processing Pipeline and Products from the NANOGrav 12.5-Year Data Set: Dispersion Measure Mis-Estimation with Varying Bandwidths
<p>This Zenodo dataset contains the data processing pipeline, as well as the data products, corresponding to the scientific journal paper "NANOGrav 12.5-Year Data Set: Dispersion Measure Mis-Estimation with Varying Bandwidths". The processing pipeline is structured as follows:</p> <ol> <li>1_fit_dispersion_3terms.py reads the .tim files (containing the times-of-arrival), creates the broadband and narrowband datasets, and fits a dispersion model to both datasets using three parameters.</li> <li>2_plot_fits_differences.py creates the residual plots showing the differences in the fitted values of the parameters.</li> <li>3_autocovariance.py calculates the autocovariance function of the differences in the fitted values, and creates the corresponding plots.</li> <li>All the files starting with "plot" are convenience scripts for creating the plots presented in the paper.</li> <li>All the files starting with "sophia" are utility functions created by the authors that are used in the main pipeline.</li> <li>The folder "NANOGrav_12yv4" contains the dataset analyzed in this work.</li> <li>The folder "NG_timing_analysis" contains utility functions created by the NANOGrav collaboration that are used in the main pipeline.</li> </ol> <p>Please do not hesitate to send all your questions, concerns, or commentaries to sophia.sosa@nanograv.org</p>
KDE Representations of the Gravitational Wave Background Free Spectra Present in the NANOGrav 12.5-Year Dataset
<p><em><strong>OVERVIEW</strong></em></p> <p><em><strong>----------------</strong></em></p> <p>This is a downloadable file of probability densities from KDEs (Kernel Density Estimator) of the CRN free spectrum analysis of the <a href="https://nanograv.org/science/data/125-year-pulsar-timing-array-data-release">NANOGrav 12.5yr Dataset</a> that can be used with the <a href="https://github.com/astrolamb/ceffyl">Ceffyl</a> and <a href="https://github.com/andrea-mitridate/PTArcade">PTArcade</a> packages. Please see the GitHub page for Ceffyl/PTArcade installation details and usage information.<br><br>Details on how this data product was produced can be found in <a href="https://journals.aps.org/prd/abstract/10.1103/PhysRevD.108.103019"><em>Lamb, Taylor & van Haasteren 2023 (DOI 10.1103/PhysRevD.108.103019).</em></a></p> <p><em><strong>DIRECTORY AND FILE STRUCTURE</strong></em></p> <p><em><strong>----------------------------------------------------</strong></em></p> <p>The directory `ng12p5_ceffyl` contains a file with log-pdfs representing their corresponding free spectra (`density.npy`), the frequencies at which they were analysed (`freqs.npy`), the grid-points at which each log-pdf was computed (`log10rhogrid.npy`), frequency labels (`log10rholabels.txt`), analysis label (`pulsar_list.txt`), an array of bandwidths computed using the Sheather-Jones method (see Lamb et al. 2023; 'bandwidths.npy'), and a file with some metadata about the data (`log.txt`).</p> <p>Note: there are two copies of `ng12p5_ceffyl` in here by accident! Both are correct versions.</p> <p>The free spectrum was ran with a 30 frequency common uncorrelated free spectrum model (CRN FS) and a 30 frequency intrinsic red noise. <a href="https://nanograv.org/science/data/125-year-stochastic-gravitational-wave-background-search">The free spectrum can be found here</a>.</p> <p><em><strong>SOFTWARE</strong></em></p> <p><em><strong>------------------</strong></em></p> <p>This data should ideally be used with the latest versions of:</p> <ul> <li><em><strong>ceffyl</strong></em> (https://github.com/astrolamb/ceffyl)</li> <li><em><strong>PTArcade </strong></em>(https://github.com/andrea-mitridate/PTArcade)</li> </ul> <p><em><strong>PLANNED REVISIONS</strong></em></p> <p><em><strong>---------------------------------</strong></em></p> <p>None</p> <p><em><strong>CHANGE LOG</strong></em></p> <p><em><strong>----------------------</strong></em></p> <p>16/01/2024 - updated KDE representations</p> <p>A bug was found that produced a poor reflection at the lower prior boundary. Hence, data was being represented well at the lower prior boundary. This has now been corrected.</p>
The NANOGrav Search for Signals from New Physics: MCMC chains
<p>MCMC chains for the GWB analyses performed in the paper "<em>The NANOGrav 15 yr Data Set: Search for Signals from New Physics</em>". </p> <p>The data is provided in pickle format. Each file contains a NumPy array with the MCMC chain (with burn-in already removed), and a dictionary with the model parameters' names as keys and their priors as values. You can load them as</p> <pre><code class="language-python">with open ('path/to/file.pkl', 'rb') as pick: temp = pickle.load(pick) params = temp[0] chain = temp[1]</code></pre> <p>The naming convention for the files is the following:</p> <ul> <li><strong>igw</strong>: inflationary Gravitational Waves (GWs)</li> <li>sigw: scalar-induced GWs <ul> <li><strong>sigw_box</strong>: assumes a box-like feature in the primordial power spectrum.</li> <li><strong>sigw_delta</strong>: assumes a delta-like feature in the primordial power spectrum.</li> <li><strong>sigw_gauss</strong>: assumes a Gaussian peak feature in the primordial power spectrum.</li> </ul> </li> <li>pt: cosmological phase transitions <ul> <li><strong>pt_bubble</strong>: assumes that the dominant contribution to the GW productions comes from bubble collisions.</li> <li><strong>pt_sound</strong>: assumes that the dominant contribution to the GW productions comes from sound waves.</li> </ul> </li> <li>stable: stable cosmic strings <ul> <li><strong>stable-c</strong>: stable strings emitting GWs only in the form of GW bursts from cusps on closed loops.</li> <li><strong>stable-k</strong>: stable strings emitting GWs only in the form of GW bursts from kinks on closed loops.</li> <li><strong>stable</strong>-<strong>m</strong>: stable strings emitting monochromatic GW at the fundamental frequency.</li> <li><strong>stable-n</strong>: stable strings described by numerical simulations including GWs from cusps and kinks.</li> </ul> </li> <li>meta: metastable cosmic strings <ul> <li><strong>meta</strong>-<strong>l</strong>: metastable strings with GW emission from loops only.</li> <li><strong>meta-ls</strong> metastable strings with GW emission from loops and segments.</li> </ul> </li> <li><strong>super</strong>: cosmic superstrings.</li> <li>dw: domain walls <ul> <li><strong>dw-sm</strong>: domain walls decaying into Standard Model particles.</li> <li><strong>dw-dr</strong>: domain walls decaying into dark radiation.</li> </ul> </li> </ul> <p>For each model, we provide four files. One for the run where the new-physics signal is assumed to be the only GWB source. One for the run where the new-physics signal is superimposed to the signal from Supermassive Black Hole Binaries (SMBHB), for these files "_bhb" will be appended to the model name. Then, for both these scenarios, in the "compare" folder we provide the files for the hypermodel runs that were used to derive the Bayes' factors.</p> <p>In addition to chains for the stochastic models, we also provide data for the two deterministic models considered in the paper (ULDM and DM substructures). For the ULDM model, the naming convention of the files is the following (all the ULDM signals are superimposed to the SMBHB signal, see the discussion in the paper for more details)</p> <ul> <li><strong>uldm_e</strong>: ULDM Earth signal.</li> <li>uldm_p: ULDM pulsar signal <ul> <li><strong>uldm_p_cor</strong>: correlated limit</li> <li><strong>uldm_p_unc</strong>: uncorrelated limit</li> </ul> </li> <li>uldm_c: ULDM combined Earth + pulsar signal direct coupling <ul> <li><strong>uldm_c_cor</strong>: correlated limit</li> <li><strong>uldm_c_unc</strong>: uncorrelated limit</li> </ul> </li> <li>uldm_vecB: vector ULDM coupled to the baryon number <ul> <li><strong>uldm_vecB_cor:</strong> correlated limit</li> <li><strong>uldm_vecB_unc</strong>: uncorrelated limit </li> </ul> </li> <li>uldm_vecBL: vector ULDM coupled to B-L <ul> <li><strong>uldm_vecBL_cor:</strong> correlated limit</li> <li><strong>uldm_vecBL_unc</strong>: uncorrelated limit</li> </ul> </li> <li>uldm_c_grav: ULDM combined Earth + pulsar signal for gravitational-only coupling <ul> <li>uldm_c_grav_cor: correlated limit <ul> <li><strong>uldm_c_cor_grav_low</strong>: low mass region </li> <li><strong>uldm_c_cor_grav_mon</strong>: monopole region</li> <li><strong>uldm_c_cor_grav_low</strong>: high mass region</li> </ul> </li> <li><strong>uldm_c_unc</strong>: uncorrelated limit <ul> <li><strong>uldm_c_unc_grav_low</strong>: low mass region </li> <li><strong>uldm_c_unc_grav_mon</strong>: monopole region</li> <li><strong>uldm_c_unc_grav_low</strong>: high mass region</li> </ul> </li> </ul> </li> </ul> <p>For the substructure (static) model, we provide the chain for the marginalized distribution (as for the ULDM signal, the substructure signal is always superimposed to the SMBHB signal)</p>
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