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149 results for “supernova”
Core collapse supernova yield from the post-processing of a long-term 3D simulation
<p>This dataset accompanies the publication<i> "Production of 44Ti and Iron-group Nuclei in the Ejecta of 3D Neutrino-driven Supernovae"</i> published in the <i>Astrophysical Journal Letters</i> Volume <strong>957</strong>, Issue 2, id.L25.</p><p>The dataset consists of an ACII text file that contains the isotopic yields from the post-processing of a 3D long-term supernova simulation for a 18.88 solar mass progenitor model. The yields are given in units of solar masses. </p><p><strong>Important: The dataset does not include the full stellar yield. </strong>It only represents the inner 0.142 solar masses. The total ejecta mass is expected to be larger. </p><p>The dataset is also available on the websites of the Max-Planck Institute for Astrophysics in Garching, Germany: https://wwwmpa.mpa-garching.mpg.de/ccsnarchive/data/Sieverding2023/</p><p>The results have been obtained using the open source nuclear reaction network code <a href="https://github.com/starkiller-astro/XNet">XNet.</a></p><p>Calculations have been performed on the supercomputing cluster Cobra the Max-Planck Computing and Data Facility (MPCDF) in Garching, Germany. </p>
Datasets for "Pulsational pair-instability supernovae in gravitational-wave and electromagnetic transients" from Hendriks et al 2023.
<p>Data related to the paper "Pulsational pair-instability supernovae in gravitational-wave and electromagnetic transients" by Hendriks et al 2023 <a href="https://doi.org/10.1093/mnras/stad2857">https://doi.org/10.1093/mnras/stad2857</a>.</p><ul><li>`EVENTS_V2.2.2_SEMI_HIGH_RES*.tar.gz: main PPISN prescription variation simulation results for the GW mergers. These contain configurations for the populations and the convolved merger results which in turn contain merger rates, merger properties and events that preceded the mergers (RLOF episodes, SNe). These results are used in figures 2, 3, 6, and 7. Figure 8 uses the SFR used in one of these simulations.</li><li>`EVENTS_V2.2.2_MID_RES*.tar.gz`: PPISNe prescription variation results for the transient rate evolution. These contain configurations for the populations and the convolved merger results which in turn contain merger rates, merger properties and events that preceded the mergers (RLOF episodes, SNe). These results are used in figure 4.</li><li>`grid_single_mass_metallicity_data.tar.gz`: data containing single-star remnant-mass data as a function of initial mass vs. final mass for our fiducial model and three variations: Farmer 2019 PPISN prescription, M_extra_ppisn_ML=10 Msun (i.e. where 10 solarmass of additional mass loss occur for each PPISN), M_co_shift_ppisn=-5 Msun (i.e. the CO core mass range that undergoes PPISN is shifted to lower masses by 5 solarmass). This data is used in figure 5.</li><li>`schematic_overview_data.tar.gz`: data containing single-star remnant-mass data as a function of pre-SN core mass for our fiducial models and several variations: Farmer 2019 PPISN prescription, M_extra_ppisn_ML = 5 Msun, M_co_shift_ppisn=-5 Msun, M_co_shift_ppisn=+5 Msun. This data is used in figure 1.</li><li>`paper_ppisne_scripts-main.tar.gz`: git-repository that contains the routines to generate the figures. The readme in this script should contain enough information, but relevant to the data here: the user needs to store the files contained in this zenodo repository in a directory that they point to at with an environment variable called `paper_PPISNe_Hendriks2023_data_dir`. These scripts are also hosted on <a href="https://gitlab.com/dhendriks/paper_ppisne_scripts">https://gitlab.com/dhendriks/paper_ppisne_scripts</a></li></ul>
Insights into non-axisymmetric instabilities in three-dimensional rotating supernova models with neutrino and gravitational-wave signatures
<p>The data of the gravitational wavefroms of core-collapse supernovae, which are used in Takiwaki, Kotake, and Foglizzo, (2021), Monthly Notices of the Royal Astronomical Society, Volume 508, Issue 1, pp.966-985</p>
Universal relation for supernova gravitational waves
<p><span> </span>The data of the gravitational wavefroms of core-collapse supernovae, which are used in Sotani, Takiwaki and Togashi (2021), Physical Review D, Volume 104, Issue 12, article id.123009</p> <p>Data Format:</p> <p>The data are in ASCII format and the two columns are1:time time since bounce in sec</p> <p>2:hplus plus polarization of the GW amplitude. We assume the source distance of 10 kpc.</p> <p>The data are sampled at ~10 kHz, but, the sampling is not uniform in time. Therefore resampling might be necessary.</p>
Constraining properties of the next nearby core-collapse supernova with multi-messenger signals: multi-messenger signals
<p>1D FLASH simulations with STIR, for alpha_lambda = 1.23, 1.25, and 1.27. Run with SFHo EOS, M1 with 12 energy groups.</p> <p>For more information on these simulations, see Warren, Couch, O'Connor, & Morozova (arXiv:1912.03328) and Couch, Warren, & O'Connor (2020).</p> <p>Includes the multi-messenger data from the STIR simulations. The filename indicates the turbulent mixing parameter a and progenitor mass m of the simulation. Columns are time [s], shock radius [cm], explosion energy [ergs], electron neutrino mean energy [MeV], electron neutrino rms energy [MeV], electron neutrino luminosity [10^51 ergs/s], electron antineutrino mean energy [MeV], electron antineutrino rms energy [MeV], electron antineutrino luminosity [10^51 ergs/s], x neutrino mean energy [MeV], x neutrino rms energy [MeV], x neutrino luminosity [10^51 ergs/s], gravitational wave frequency from eigenmode analysis of the protoneutron star structure [Hz]. Note that the x neutrino luminosity is for <strong>one</strong> neutrino flavor - to get the total mu/tau neutrino and antineutrino luminosities requires multiplying this number by 4.</p> <p>v1.1 - removed unnecessary duplicate files</p> <p>v1.2 - upload failed. Obsolete.</p> <p>v1.3 - packaging alpha values as separate tar files for easy download.</p>
The data behind the ApJ article "Environmental Dependence of Type Ia Supernovae in Low-Redshift Galaxy Clusters"
<p>Data from "Environmental Dependence of Type Ia Supernovae in Low-Redshift Galaxy Clusters", <a href="https://ui.adsabs.harvard.edu/abs/2023arXiv230601088L/abstract">NASA ADS</a></p><p>inner_cluster_data.csv and outer_cluster_data.csv include the SALT3 mB, x1, and c parameter values, distance moduli and Hubble residuals (with _1 referring to Figure 9 and _2 referring to Figure 10), outlier designation from MCMC procedure, host cluster, host cluster redshift (with Hubble diagram version converted to frame of CMB), host cluster r500, projected separation from cluster center, NED Host galaxy name, photometrically-derived estimate for host mass, host or SN redshift used in analysis, and the Host SFR category (Q: quiescent, SF: star-forming, GV: green valley) for our cluster SNe Ia.</p><p>sf_field.csv and quiescent_field.csv contain SALT parameter values, distance moduli and Hubble residuals (from Figure 10), host galaxy sSFR and mass measurements, and host redshifts (all spectroscopic, also with Hubble diagram converted values) for SNe Ia in our field samples.</p><p>full_cluster.csv contains the data from the table in the appendix of the paper.</p><p>The inner_cluster_/outer_cluster_mcmc_samples.csv files contain the samples needed to reproduce the corner plot for Figure 10.</p><p>The Python scripts recreate the figures from the paper given the above data. The details for which columns and constraints needed to reproduce the figures are included in these files.</p>
Data for Figure 1 of Taubenberger 2017, "The Extremes of Thermonuclear Supernovae"
<p>Data needed to recreate Figure 1 of Taubenberger S., <a href="https://ui.adsabs.harvard.edu/abs/2017hsn..book..317T/abstract">"The Extremes of Thermonuclear Supernovae"</a>, in A. W. Alsabti, P. Murdin, eds., “Handbook of Supernovae”, Springer, ISBN: 978-3-319-20794-0 (2017). A detailed README is included.</p>
Earth's atmosphere protects the biosphere from nearby supernovae
<p>Dataset for manuscript: "Earth’s atmosphere protects the biosphere from nearby supernovae".</p> <p>Communications Earth & Environment</p> <p>DOI: <a href="https://doi.org/10.1038/s43247-024-01490-9" target="_blank" rel="noopener noreferrer">10.1038/s43247-024-01490-9</a></p> <div><span>CONTRIBUTORS: </span>Theodoros Christoudias; Jasper Kirkby; Dominik Stolzenburg; Andrea Pozzer; Eva Sommer; Guy P. Brasseur; Markku Kulmala; Jos Lelieveld</div>
Stellar Mass Black Hole Formation and Multimessenger Signals from Three-dimensional Rotating Core-collapse Supernova Simulations
<p>Gravitational waveforms from <a href="https://ui.adsabs.harvard.edu/abs/2021ApJ...914..140P/abstract">Pan et al. (2021) .</a></p> <p>They are the 40 solar mass model from Woosley & Heger 2007 with different<br>initial rotational speeds:</p> <p>Model NR: Omega_0 = 0.0 rad/sec<br>Model SR: Omega_0 = 0.5 rad/sec<br>Model FR: Omega_0 = 1.0 rad/sec</p> <p>/* File content */</p> <p>They are 5 files for each simulation.</p> <p>Files "data_s40_[model]_d3_[Cross/Plus][Equator/Pole].d" are GW strains for different<br>mode of polarization [h_plus or h_cross] and viewing angles [equator or pole].</p> <p>1st column is time [s] in postbounce. <br>2nd column s the GW strain, assuming d=10 kpc.<br> <br>Files "data_s40_[model]_d3_Idotdot.d" are the second time derivative of the<br>quadruple moments.</p> <p>1st: postbounce time [s] <br>2nd: Idd_xx [cgs]<br>3rd: Idd_xy = Idd_yx [cgs]<br>4th: Idd_yy = Idd_yy [cgs]<br>5th: Idd_zx = Idd_zx [cgs]<br>6th: Idd_zy = Idd_zy [cgs]<br>7th: Idd_zz = Idd_zz [cgs]</p> <p> </p>
First Study of the Supernova Remnant Population in the Large Magellanic Cloud with eROSITA
<p>Aims. The all-sky survey carried out by the extended Roentgen Survey with an Imaging Telescope Array (eROSITA) on board Spektrum-Roentgen-Gamma (Spektr-RG, SRG) has provided us with spatially and spectrally resolved X-ray data of the entire Large Magellanic Cloud (LMC) and its immediate surroundings in the soft X-ray band down to 0.2 keV with an average angular resolution</p> <p>of 26′′ in the field of view. In this work, we have studied the supernova remnants (SNRs) and candidates in the LMC using data from the first four all-sky surveys (eRASS:4). From the X-ray data in combination with results at other wavelengths, we obtain information about the SNRs, their progenitors, and the surrounding interstellar medium (ISM). The study of the entire population of SNRs in a galaxy helps us to understand the underlying stellar populations, the environments, in which the SNRs are evolving, and the stellar feedback on the ISM.</p> <p>Methods. The eROSITA telescopes are the best instruments currently available for the study of extended soft sources like SNRs in an entire galaxy due to their large field of view and high sensitivity in the softer part of the X-ray band. We applied the Gaussian gradient magnitude (GGM) filter to the eROSITA images of the LMC to highlight the edges of the shocked gas in order to find new SNRs. We visually compared the X-ray images with those of their optical and radio counterparts to investigate the true nature of the extended emission. The X-ray emission is evaluated using the contours with respect to the background, while for the optical we used line ratio</p> <p>diagnostics, and non-thermal emission in the radio images. We used the Magellanic Cloud Emission Line Survey (MCELS) for the optical data. For the radio comparison, we used data from the Australian Square Kilometre Array Pathfinder (ASKAP) survey of the LMC. Using the star formation history (SFH) derived from the near-IR photometry of the VISTA survey of the Magellanic Clouds (VMC) we have investigated the possible progenitor type of the new SNRs and SNR candidates in our sample. Results. We present the most updated catalogue of SNRs in the LMC. Previously known SNRs and candidates were detected with 1σ significance down to a surface brightness of Σ [0.2–5.0 keV] = 3.0 × 10−15 erg s−1 cm−2 arcmin−2 and were examined. The eROSITA data have allowed us to confirm one of the previous candidates as an SNR. We confirm three newly detected extended sources as new SNRs, while we propose 13 extended sources as new X-ray SNR candidates. We also present the analysis of the follow-up</p> <p>XMM-Newton observation of MCSNR J0456–6533 discovered with eROSITA. Among the new candidates, we propose J0614–7251 (4eRASSU J061438.1−725112) as the first X-ray SNR candidate in the outskirts of the LMC.</p>
Stellar Evolution Models from "Finding the Fuse: Prospects for the Detection and Characterization of Hydrogen-Rich Core-Collapse 5 Supernova Precursor Emission with the LSST"
<p>These data consist of all runs from the Modules for Experiments in Stellar Astrophysics (MESA; Paxton et al. 2011, 2013, 2015, 2018, 2019) code, used to construct radius priors for modeling supernova precursor emission in<em> <a href="https://arxiv.org/abs/2408.13314">Finding the Fuse: Prospects for the Detection and Characterization of Hydrogen-Rich Core-Collapse 5 Supernova Precursor Emission with the LSST</a></em> (Gagliano+2024, submitted). </p> <p>The contents of the data files are detailed in the file <strong>ReadmeMESA.txt</strong>. Additional detail concerning the simulations can be found in Section 2.2 of the linked publication. </p>
Insights into non-axisymmetric instabilities in three-dimensional rotating supernova models with neutrino and gravitational-wave signatures
<p>Those are movies of numerical supernova models, which appear in Takiwaki, Kotake, and Foglizzo, (2021), Monthly Notices of the Royal Astronomical Society, Volume 508, Issue 1, pp.966-985</p>
Emission line models for the lowest mass core-collapse supernovae - I. Case study of a 9 M⊙ one-dimensional neutrino-driven explosion
<p>Model spectra of the 9 Msun iron-core model, and the pure H toy model, 200-600d. Distance 10 Mpc assumed.</p>
Long-duration Superluminous Supernovae at Late Times
<p>Single-composition models in three flavours (pure O, OMg, C burn). Zone mass, power level, and clumping free parameters. Distance 10 Mpc assumed.</p>
The Young Supernova Experiment Data Release 1 (YSE DR1) Light Curves
<p>This is the official Zenodo data release of the Young Supernova Experiment Public Data Release 1 (YSE DR1) light curves associated with the paper, <em>"The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae</em><em>"</em>.<em> </em>YSE DR1 is comprised of processed multi-color Pan-STARRS1 (PS1)-<em>griz</em> and Zwicky Transient Facility (ZTF)-<em>gr </em>photometry lightcurve files in the SNANA data format of 1975 transients with host galaxy associations, redshifts, spectroscopic/photometric classifications, and additional data products from November 24th, 2019 to December 20, 2021. See Aleo et al. (2022) for details. </p> <p>"yse_dr1_zenodo.tar.gz" -- All lightcurve data with no cut on signal to noise (S/N).</p> <p>"yse_dr1_zenodo_snr_geq_4.tar.gz" -- All lightcurve data with S/N >= 4. This can be used to recreate the analysis in Aleo et al. (2022).</p> <p>"parsnip_results_for_ysedr1_table_A1_full_for_online" -- The full version of Table~C2 in Aleo et al. (2022). The full ParSNIP (tertiary classification) results for YSE DR1.</p> <p>NOTE: An example tutorial on how to download the YSE DR1 data (full sample, spec sample, phot sample), grab metadata, and recreate a plot from the paper can be found <a href="https://github.com/patrickaleo/ysedr1_data_demos/blob/main/ysedr1_quick_tutorial.ipynb">on Github</a>. </p>
Core-Collapse Supernova
<p>Collection of certified trajectories, covering a wide range of<sup> </sup>core-collapse supernova nucleosynthesis conditions. Every trajectory comes with the selected initial abundances and other key information, such as the reference of the publication, the stellar region from where it was extracted, the mass of the progenitor star and its metallicity.</p>
Constraining properties of the next nearby core-collapse supernova with multi-messenger signals: gravitational wave frequency fits
<p>1D FLASH simulations with STIR, for alpha_lambda = 1.23, 1.25, and 1.27. Run with SFHo EOS, M1 with 12 energy groups.</p> <p>For more information on these simulations, see Warren, Couch, O'Connor, & Morozova (arXiv:1912.03328) and Couch, Warren, & O'Connor (2020).</p> <p>Includes fit to the gravitational wave peak frequency versus time post-bounce, for a functional fit of the form f = A*sqrt(t) + B*t + C, where the frequency f is in Hz and the time t is in seconds. The columns are: progenitor mass [M_sun], fit coefficient A, fit coefficient B, fit coefficient C, and the R^2 of the fit.</p>
dataset for "Non-LTE Synthetic Observables of a Multidimensional Model of Type Ia Supernovae"
<p>Included here are datafiles supplementary to the article "Non-LTE Synthetic Observables of a<br>Multidimensional Model of Type Ia Supernovae" (Boos, Dessart, Townsley, Shen), submitted <br>to ApJ/arxiv in October 2024. This is a revised version of the dataset using an improved<br>method to generate the 1D LTE observables (1D LTE and pseudo-2D non-LTE observables have<br>thus changed from the previous version).</p> <p>We include in this dataset the 2D double detonation ejecta model (produced in Boos et al. 2021),<br>as well as the 15 wedge profiles constructed from this model, which were used in the radiative<br>transfer calculations of this work. These profiles are provided in Sedona input format. The<br>headers/columns for the 1D profiles are as follows:<br>1: Sedona model type<br>2: num_cells, rmin, ejecta time, num_isos<br>3: isos<br>4-: v_r, rho, T, X_a, X_b, etc.</p> <p>We also include the synthetic spectra and photometry from this work. These synthetic observables<br>are given for each set of calculations (1D LTE, 2D LTE, 1D non-LTE, and pseudo-2D non-LTE) between<br> -3 and +15 d from maximum light. The photometry is given in absolute magnitude in the Vega system.<br>The spectra have been rebinned such that the bins are the same between the Sedona and CMFGEN<br>calculations. The flux in these spectral files is given for a distance of 1 kpc.</p> <p><br>-Samuel J. Boos (sjboos@crimson.ua.edu)</p>
Archival Datasets for SuperNova Artificial Inference by Lstm neural networks (SNAIL)
<p>The spectral-observation dataset (enclosed in the file archival_spec_observations.tar.gz) is comprised of 3091 observed spectra from 361 SNe Ia, largely contributed from CfA (Blondin et al. 2012), BSNIP (Silverman et al. 2012), CSP (Folatelli et al. 2013) and Supernova Polarimetry Program (Wang & Wheeler 2008; Cikota et al. 2019a; Yang et al. 2020).</p> <p>The spectral-template dataset (enclosed in the file archival_spec_templates.tar.gz) includes 361 spectral templates, each of them (covering -15 to +33d with wavelength from 3800 to 7200 A) was generated from the available spectroscopic observations of an individual SN via a LSTM neural network model.</p> <p>The auxiliary photometry dataset (enclosed in the file archival_phot_observations.tar.gz) provides the B & V light curves of these SNe (in total, 196 available SNe Ia), that were used to calibrate the synthetic B-V color of the observed spectra.</p> <p>In additional, the two master catalogs give the detailed information about the 361 SNe and their spectroscopic observations, respectively. </p> <p>These datasets are associated to the paper "Spectroscopic Studies of Type Ia Supernovae Using LSTM Neural Networks" (Hu et al. 2022, ApJ, accepted).</p>
Diffuse Supernova Neutrino Background search at Super-Kamiokande (arXiv:2109.11174, PRD 104, 122002)
<p>This is the data release for the PRD 104, 122002 article about the Diffuse Supernova Background search at Super-Kamiokande. The figures which can be reproduced with this release are listed in the README of the data_release folder.</p> <p>The spectral_analysis_npy.SKMC.tar.gz folder contains the files needed to reproduce the spectral analysis in section VII of the paper. To incorporate it to the spectral analysis code please follow the instructions given in the README of <a href="https://github.com/soso128/spectral_analysis">the spectral analysis Github folder</a>.</p>
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