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89 results for “pulsars”
Survey for Pulsars and Extragalactic Radio Bursts V Dataset
<p>This dataset contains the the polarization-calibration profiles, ephemerides, and ToA files for the pulsars included in the SUPERB V project and associated article. Raw data are not included in this repository due to the large file sizes; data can be retrieved from the CSIRO Data Access Portal. </p>
The impact of Solar wind variability on pulsar timing
<p>Timing models, ToA files and DM time series (UTC_start_date, UTC_center_date, MJD, DMvariation, DMvariation_error, SolarElongation) used in the article "The impact of Solar wind variability on pulsar timing" (published in A&A, part of the Veni project SOLTRAC, 016.Veni.192.086)</p> <p> </p>
Burst timescales and luminosities as links between young pulsars and fast radio bursts Dataset
<p>The dataset to reproduce the results and plots in Nimmo et al. 2021b (<a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210511446N/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv210511446N/abstract</a>). The scripts to produce the plots can be found here: <a href="https://github.com/KenzieNimmo/FRB20200120E_timescales">https://github.com/KenzieNimmo/FRB20200120E_timescales</a></p> <p>The software used to make the data products are:</p> <ul> <li>SFXC (Keimpema et al. 2015;<a href="https://github.com/aardk/sfxc/"> https://github.com/aardk/sfxc/</a>) </li> <li>DSPSR (van Straten & Bailes 2011; <a href="http://dspsr.sourceforge.net/">http://dspsr.sourceforge.net/</a>)</li> <li>PSRCHIVE (Hotan et al. 2004; <a href="http://psrchive.sourceforge.net">http://psrchive.sourceforge.net</a>)</li> <li>numpy (Harris et al. 2020; <a href="https://numpy.org/install/">https://numpy.org/install/</a>)</li> </ul> <p>A complete list of the data products:</p> <ul> <li>8us/125kHz full polarisation archive files (dspsr) for all 5 bursts presented in the work (coherently and incoherently dedispersed to 87.75pc/cc). Created from filterbank data made using SFXC. Use load_file.load_archive from the above github link to load data into python as a numpy array. <ul> <li>pr141a_corr_no0069_8us_125kHz_FullPol_FullDedisp_dm87.75.cor2_Ef.ar.calib</li> <li>pr141a_corr_no0069_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib</li> <li>pr143a_corr_no0015_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib</li> <li>pr143a_corr_no0057_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib</li> <li>pr158a_corr_no0017_8us_125kHz_FullPol_FullDedisp_dm87.75.ar.calib</li> </ul> </li> <li>31.25ns/16MHz Stokes I filterbank data for B2, B3 and B4. Coherently and incoherently dedispersed to 87.7527pc/cc. Created using SFXC. <ul> <li>pr141a_corr_no0069_31.25ns_16MHz_StokesI_FullDedisp_dm87.7527_SFXC.cor2_Ef.fil</li> <li>pr143a_corr_no0015_31.25ns_16MHz_StokesI_FullDedisp_dm87.7527_SFXC.cor_Ef.fil</li> <li>pr143a_corr_no0057_31.25ns_16MHz_StokesI_FullDedisp_dm87.7527_SFXC.cor_Ef.fil</li> </ul> </li> <li>1us/500kHz Stokes I filterbank data for B2, B3 and B4. Coherently and incoherently dedispersed to 87.7527pc/cc. Created using SFXC. <ul> <li>pr141a_corr_no0069_1us_500kHz_StokesI_FullDedisp_dm87.7527_SFXC.cor2_Ef.fil</li> <li>pr143a_corr_no0015_1us_500kHz_StokesI_FullDedisp_dm87.7527_SFXC.cor_Ef.fil</li> <li>pr143a_corr_no0057_1us_500kHz_StokesI_FullDedisp_dm87.7527_SFXC.cor_Ef.fil</li> </ul> </li> <li>125ns/4MHz full pol archive file of burst B3. Coherently and incoherently dedispersed to 87.7527pc/cc. Created using dspsr from a filterbank file made by SFXC. <ul> <li>pr143a_corr_no0015_125ns_4000kHz_FullPol_FullDedisp_dm87.7527_SFXC.cor_Ef.calib</li> </ul> </li> </ul> <p>We also provide a number of numpy files containing analysis products for ease of reproducing the figures. </p> <ul> <li>2D autocorrelation functions of the dynamic spectra of all 5 bursts. Additionally we give the 2D Gaussian fits to the ACFs and the Lorentzian fits to the frequency ACFs (for measuring the scintillation bandwidth) <ul> <li>ACF_b*_8us_f8.npy</li> <li>fitACF_b*_8us_f8.npy</li> </ul> </li> <li>Peak signal-to-noise ratio (S/N) of burst B3 profile at 1us resolution as a function of dispersion measure (DM) with a Gaussian fit to the result <ul> <li>pr143a_corr_no0015_500ns_1000kHz_StokesI_FullDedisp_dm87.7527_DS.npy (500ns dynamic spectrum)</li> <li>DM_vs_peakSN_sfxc_IF1-11.npy</li> <li>DM_vs_peakSN_sfxc_IF1-11_fit.npy</li> </ul> </li> <li>Power spectrum (PS) of 31.25ns profile of B2, B3 and B4 with the power law (PL) fits and power law+lorentzian (PL_lor) fit for B3 <ul> <li>PS_B2_IF4678_31.25ns.npy</li> <li>PS_B3_IF3568_31.25ns.f8.npy (downsampled by a factor of 8)</li> <li>PS_B3_IF3568_31.25ns.npy</li> <li>PS_B4_IF67910_31.25ns.npy</li> <li>PL_fit_B2.npy</li> <li>PL_fit_B3.npy</li> <li>PL_fit_B4.npy</li> <li>PL_lor_fit_B3.npy</li> </ul> </li> <li>Faraday spectra of B1, B2, B3, B4 <ul> <li>no0015_8us_125kHz_faradayspec.npy</li> <li>no0057_8us_125kHz_faradayspec.npy</li> <li>no0069_8us_125kHz_faradayspec.npy</li> <li>no0069_8us_125kHz_faradayspec_2.npy</li> </ul> </li> <li>Stokes Q and U spectra for B1, B2, B3, B4 and the corresponding joint QU fits <ul> <li>pr141a_corr_no0069_8us_125kHz_FullPol_FullDedisp_dm87.75.cor2_Ef.ar.calib_QUdata.npy</li> <li>pr141a_corr_no0069_8us_125kHz_FullPol_FullDedisp_dm87.75.cor2_Ef.ar.calib_QUfit.npy</li> <li>pr141a_corr_no0069_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib_QUdata.npy</li> <li>pr141a_corr_no0069_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib_QUfit.npy</li> <li>pr143a_corr_no0015_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib_QUdata.npy</li> <li>pr143a_corr_no0015_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib_QUfit.npy</li> <li>pr143a_corr_no0057_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib_QUdata.npy</li> <li>pr143a_corr_no0057_8us_125kHz_FullPol_FullDedisp_dm87.75.cor_Ef.ar.calib_QUfit.npy</li> </ul> </li> </ul> <p> </p> <p> </p>
A search for planetary companions around 800 pulsars from the Jodrell Bank pulsar timing programme
<p>####### Nitu et al 2022 #######<br> #### Supplementary material ####</p> <p>This folder contains the summarised mass limits plots ['allPSRs_masslims.pdf'], (linearised) mass posterior distributions, as well as the 95% mass limit, for each period bin of each pulsar.</p> <p>In each $PSR folder there are 9 $period-bin folders,<br> corresponding to the ranges in Table 1 of Nitu et al (2022) as follows:<br> 'p21to42'<br> 'p42to85'<br> 'p85to170'<br> 'p170to340'<br> 'p340to390'<br> 'p390to780'<br> 'p780to1560'<br> 'p1560to3120'</p> <p>In each of the $period-bin folders, there is:<br> - a plot of linearised mass posterior: 'all_masses_linprior.pdf'<br> - a masslim_werr_linprior.npy file containing values, in order, for:<br> [mPeriod(days) sPeriod(days) Masslimit(Me) errMasslimit(Me) Detection(3sigma)]<br> -- where the period range is [mPeriod-sPeriod, mPeriod+sPeriod]<br> -- Masslimit is the value of the mass limit, in Earth masses for that period bin<br> -- errMasslimit is NOT a complete uncertainty, but just due to binning the posterior,<br> and should not be used for anything except checking the binning is appropriate<br> -- Detection is whether our analysis flagged a detection, i.e. whether mean > 3*sigma<br> Note: to read .npy files, use numpy.load(filename) in python<br> - [not all] a masslim_linprior.txt with the same information as the .npy file</p>
Data for "Instability in supernova fallback disks and its effect on the formation of ultra long period pulsars"
<p>This dataset gives the monte-carlo simulated data used in its related article, where the folder names denote the corresponding models:</p> <ul> <li>mc_r300_ref: Using T=300K as the criteria for the disk neutralization (R_neu2), and partial instability; </li> <li>mc_r300_glo: Using T=300K as the criteria for the disk neutralization (R_neu2), and global instability;</li> <li>mc_r6500_ref: Using T=6500K as the criteria for the disk neutralization (R_neu1), and partial instability;</li> <li>mc_r6500_glo: Using T=6500K as the criteria for the disk neutralization (R_neu1), and global instability.</li> </ul> <p>Each folder contains four ".data" files, corresponding to the simulated data for different time points: 1 kyr, 10 kyr, 100 kyr and 1 Myr. These files can be easily read and used to replicate our MC results.</p> <p>Moreover, reproducing our results may require the following data columns from the files:</p> <ul> <li>"ids": "=1" represents the disk can form, while "=0" not;</li> <li>"da": "=1" represents the disk can exist, while "=0" not;</li> <li> <div>"mdisk0": the initial mass (unit: solar mass) of the fallback disk;</div> </li> <li> <div>"rf0": the initial outer radius (unit: Schwartzschild radius) of the fallback disk;</div> </li> <li> <div>"alpha0": the initial disk inclination angle of the fallback disk;</div> </li> <li> <div>"p0": the initial spin period of the neutron star;</div> </li> <li>"bns0": the initial magnetic field strength of the neutron star;</li> <li>"chi0": the initial magnetic inclination angle of the neutron star;</li> <li>"*_f": the values at the specific time point (i.e. 1 kyr, 10 kyr, 100 kyr or 1 Myr);</li> <li>"omegadot": the time derivative of spin angular velocity;</li> <li>"rin", "rco", and "rlc": the inner radius, the corotation radius and the light cylinder radius;</li> <li>"n1", "n2" and "n3": the accertion torque, the torque caused by the magnetic-disk interaction and the dipole radiation torque.</li> </ul> <p>Overall, this data repository is intended to facilitate the reproduction of the results related to the Monte Carlo simulations presented in the article: Instability in supernova fallback disks and its effect on the formation of ultra long period pulsars. If you encounter any issues while using the data, please feel free to contact us at this email: y.hr@smail.nju.edu.cn</p>
IQRM: real-time adaptive RFI masking for radio transient and pulsar searches
<p>This is repository of the data that were used for the analysis and results presented in "IQRM: real-time adaptive RFI masking for radio transient and pulsar searches" submitted to the Monthly Notices for the Royal Astronomical Society for publication. The readme file along with the data contains all the necessary information one would need to process the data. The data will be made available to everyone once the paper has been accepted for publication. If you are using data from this repository, please do not forget to cite the following paper:</p> <p>"IQRM: real-time adaptive RFI masking for radio transient and pulsar searches", V M Morello, K M Rajwade and B W Stappers, 2021, Monthly Notices of the Royal Astronomical Society, in press.</p>
The Thousand-Pulsar-Array programme on MeerKAT - X. Scintillation arcs of 107 pulsars
<p>Data used in the publication "The Thousand-Pulsar-Array programme on MeerKAT - X. Scintillation arcs of 107 pulsars" <a href="https://doi.org/10.1093/mnras/stac3149">https://doi.org/10.1093/mnras/stac3149</a>. This release includes both the raw and filtered dynamic spectra, as described in the manuscript.</p> <p>The pipeline used to process produce, filter, and analyse dynamic spectra starting from the pulsar archives is on github: https://github.com/ramain/meerkat-scintpipe</p>
Variable Scintillation Arcs in Millisecond Pulsars observed with the Large European Array for Pulsars
<p>Dynamic spectra used in "Variable Scintillation Arcs in Millisecond Pulsars observed with the Large European Array for Pulsars". </p> <p>The dynamic spectra are simple ascii (the same output produced by psrflux), produced as described in the manuscript. A function to read them in python is included on github: https://github.com/ramain/scintillation/blob/master/scintillation/dynspectools/dynspectools.py, and they should all be compatible with the scintools package.</p>
Datasets for Constraining the Parameter Regime of Pulsar Radio Emission
<p>The datasets support the figures in the paper <em>Refining pulsar radio emission due to streaming instabilities: Linear theory and PIC simulations </em>(figures <span class="math-tex">\(2\)</span> to <span class="math-tex">\(7\)</span>) and provide additional information discussed in Section <span class="math-tex">\(5\)</span> of the paper. They contain parametric studies investigating a relativistic dispersion relation for an electron-positron pair plasma near a pulsar. The investigated quantities are the maximum growth rates (max_growth_rate) in units of <span class="math-tex">\(10^{-3}\omega_\mathrm{p}\)</span>, an integrated value over the entire range of positive wave growth (int_growth_rate) in units of <span class="math-tex">\(10^{-3}\omega_\mathrm{p}\)</span>, the fractional bandwidth (bandwidth) in units of <span class="math-tex">\(\omega_\mathrm{p}\)</span>, the minimum and maximum values where the growth rate exceeds a threshold value of <span class="math-tex">\(2.8\times10^{-4}/\omega_\mathrm{p}\)</span> - which can be associated to effective wave growth - in units of <span class="math-tex">\(1 / d_\mathrm{e}\)</span> (k_thr_min and k_thr_max) as well as a relative deviation of the range between these two values and the entire range of positive wave growth (rel_dev). All of these parameters are investigated while changing a specific parameter in the dispersion relation (<span class="math-tex">\(\rho_0\)</span>, <span class="math-tex">\(\rho_1\)</span>, simultaneously <span class="math-tex">\(\rho_0\)</span> and <span class="math-tex">\(\rho_1\)</span>, <span class="math-tex">\(\epsilon_\mathrm{n}\)</span> and <span class="math-tex">\(\gamma_\mathrm{b}\)</span>, the latter once with <span class="math-tex">\(\epsilon_\mathrm{n}=10^{-3}\)</span> and once with fixed <span class="math-tex">\(n_0 = n_1 =1\)</span>and variable <span class="math-tex">\(\epsilon_\mathrm{n}=10^{-3}\)</span>). These parameters appear in the titles of the text files which contain the respective dataset.</p>
Pulsars detected in the GP survey in both imaging and beamforming searches.
<p><span>S</span><span>I</span><span> </span><span>is the mean flux density of the pulsars </span><span>in Stokes I image from this work, S</span><span>V</span><span> </span><span>is the Stokes V for the pulsars that were </span><span>detected in Stokes V image in this work and S</span><span>lit</span><span> </span><span>is the low-frequency flux density </span><span>available in the literature: ’M’ stands for MWA-image detection by Murphy et al.</span><span>(2017), ’X’ stands for MWA-incoherent beam detection by Xue et al. (2017), ’S’ </span><span>stands for MWA SMART survey detections by Bhat et al. (2023b) and ’K’ stands </span><span>for LOFAR detection by Kondratiev et al. (2016).</span><span> </span><span>α</span><span> </span><span>is the spectral index of the </span><span>pulsars.</span><span> </span><span>α</span><span> </span><span>is calculated using the flux densities of the pulsars in MWA Stokes I </span><span>image (154 MHz) and the RACS Stokes I image (888 MHz).</span></p>
Datasets for "Gravitational wave signal from primordial magnetic fields in the Pulsar Timing Array frequency band'
<p>The tar archive run_directories.zip contains the run directories for each run in Table 1 and the figures of the paper "Gravitational wave signal from primordial magnetic fields in the Pulsar Timing Array frequency band", by A. Roper Pol, C. Caprini, A. Neronov, D. Semikoz. The run directories, the plots, and the code to generate the plots can be found in https://github.com/AlbertoRoper/GW_turbulence.</p>
The TRAPUM Large Magellanic Cloud pulsar survey with MeerKAT I: Survey setup and first seven pulsar discoveries (Archive files)
<p>PSRCHIVE archive files of the seven new LMC radio pulsars as described in the paper <em>The TRAPUM Large Magellanic Cloud pulsar survey with MeerKAT I: Survey setup and first seven pulsar discoveries </em>(Prayag et al. 2024).</p>
The Chinese Pulsar Timing Array Data Release I: Single pulsar noise analysis
Open the record for dataset details and reuse information.
Study of PULSAR-ICI +/- IMSA101 in Patients with Oligoprogressive Solid Tumor Malignancies
ClinicalTrials.gov study NCT05846659. IPD Sharing: NO. Countries: 1. Publications: 0.
Study of PULSAR-ICI +/- IMSA101 in Patients With Oligometastatic NSCLC and RCC
ClinicalTrials.gov study NCT05846646. IPD Sharing: NO. Countries: 1. Publications: 0.
PULSAR LED - GIF E VIDEO PARA PROCESSAMENTO
<p>- GIF elaborado a partir do vídeo do experimento Circuito LED blinker, para simular um pulsar.<br>- Vídeo do experimento Circuito LED blinker para ser processado no software Tracker.<br><br>Fonte GIF: <a href="https://upload.wikimedia.org/wikipedia/commons/4/4d/Lightsmall-optimised.gif">A Cosmic Lighthouse - Michael Kramer</a> (University of Manchester)<br>Vídeo LED: Lucas Ferreira (UnB/MNPEF)</p> <p> </p> <p>Material desenvolvido para o artigo (no prelo) "DOS LEDS AOS PULSARES: UM EXPERIMENTO INTERATIVO DE BAIXO CUSTO PARA O ENSINO DE ASTRONOMIA E ASTROFÍSICA NA ESCOLA" (FERREIRA, ANDRADE, LANGHI, 2024).</p>
MeerTime Thousand Pulsar Array Data Release
<p>Data associated with the MeerTime Thousand Pulsar Array Data Release. Please cite Keith et al., MNRAS, (2024), <em>"The Thousand-Pulsar-Array programme on MeerKAT XIII: Timing, flux density, rotation measure and dispersion measure timeseries of 597 pulsars"</em> and refer to this paper for important details on this dataset.</p>
PULSAR Radiotherapy Plus Anti-PD-1 Therapy in Metastatic Abdominopelvic Tumors
ClinicalTrials.gov study NCT07383857. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Hormonal Receptor (HR)-Positive HER2 Negative Breast Cancer Patients Treated With Preoperative ELacestrant and PULSAR Radiotherapy
ClinicalTrials.gov study NCT07005882. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
PD-1 Combined With Chemotherapy and PULSAR in LAPC and Local Recurrence Patients
ClinicalTrials.gov study NCT06359275. IPD Sharing: NO. Countries: 1. Publications: 0.
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