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8 results for “supermassive black hole”
The Accretion History of AGN I: Supermassive Black Hole Population Synthesis Model
<p>The X-ray Luminosity Function attached to this paper: https://ui.adsabs.harvard.edu/#abs/arXiv:1810.02298</p> <p>The python script contains instructions on how to calculate space densities using the numpy array.</p>
Mass-redshift dependency of Supermassive Black Hole Binaries for the Gravitational Wave Background
<p>These show the posterior distributions as supplementary material for arXiv:2305.18293 and doi:10.1093/mnras/stae1219</p> <p>The corner plots for the complete 20 parameters with amplitudes hc = 0.5e-15, 1e-15, 2e-15, 3e-15, and 4e-15 for both circular and eccentric population of SMBHBs are presented in the 'free_parameters' folder.</p> <p>The corner plots for the 16 parameters with amplitudes hc = 0.5e-15, 2e-15, and 4e-15 for both circular and eccentric population of SMBHBs using the fitted BH-bulge mass parameters from the simulations can be found in the 'simulation_parameters' folder.</p> <p>The posterior distributions are shown as black contours, while the prior distributions are denoted by light green lines. The top right inlay figure shows the median and central 2sigma range of the recovered characteristic spectrum, where the 5 points denote the frequency bins of 1/(25years), 2/(25years), 3/(25years), 4/(25years) and 5/(25years), which are used as the input data for the Bayesian analysis. To guide the eye the analytic sensitivity curve from the IPTA DR2 is also plotted.</p>
Data for the paper 'WISDOM Project - VI. Exploring the relation between supermassive black hole mass and galaxy rotation with molecular gas '
<p>This upload includes the data underlying the MNRAS paper Smith et al. (2020) entitled 'WISDOM Project - VI. Exploring the relation between supermassive black hole mass and galaxy rotation with molecular gas' (arXiv:2010.08565). The full author list is available from the paper, and we request that this paper is cited if this data is used in future publications.</p> <p>The upload includes machine-readable versions (csv) of Tables 3, 4, A1 and A2 of the paper. The upload also includes the calibrated spectra from the two observing programmes (191-18 at the IRAM 30m telescope and 2018-04a at the OSO 20m telescope), and the homogenised spectra used in the project. Full descriptions are given in the paper. </p> <p>Table 3: CubeData.csv; The table contains the determined line widths, inclinations, and SMBH masses used for the resolved sample of this project. The references from which the cubes were obtained, are listed in Table 3 of the paper.</p> <p>UnresolvedData.csv: Table 4; The table contains the determined line widths, inclinations, and SMBH masses used for the unresolved sample of this project. The references from which the spectra were obtained, are listed in Table 4 of the paper.</p> <p>IRAMData.csv: Table A1; The table contains a list of galaxies observed using the IRAM 30m telescope as part of project 191-18. For each galaxy the rms noise is listed, and for detected galaxies the spectrally-integrated line intensity measured over the specified velocity range given. The inferred molecular gas mass is also listed. </p> <p>OSO20mData.csv: Table A2; The table contains a list of galaxies observed using the OSO 20m telescope as part of project 2018-04a. For each galaxy the rms noise is listed, and for detected galaxies the spectrally-integrated line intensity measured over the specified velocity range given. The inferred molecular gas mass is also listed. </p> <p>IRAM30m_191-18.tar: Calibrated spectra from programme 191-18.</p> <p>OSO2018-04a.tar: Calibrated spectra from programme 2018-04a.</p> <p>ResolvedSample.tar: Homogenised spectra for the spatially-resolved sample. Note that some spectra were sourced from other works, the original references are given in the fits headers.</p> <p>UnresolvedSample.tar: Homogenised spectra for the spatially-unresolved sample. Note that some spectra were sourced from other works, the original references are given in the fits headers.</p>
Dataset and Code used in ApJ publication: "A novel approach to understanding the link between supermassive black holes and host galaxies"
<p>All the data of this paper is found under BH_M-sigma_compilation/Data</p> <p>The main data tables are found the at BH_M-sigma_compilation/Data/BHcompilation_updated.csv</p> <p>The SDSS data galSpecInfo-dr8.fits and galSpecLine-dr8.fits can be found at: <a href="https://www.sdss3.org/dr8/spectro/spectro_access.php" rel="nofollow">https://www.sdss3.org/dr8/spectro/spectro_access.php</a></p> <p>The main code for this paper is at BH_M-sigma_compilation/Code/Mixture_Upper_Limits and consists of the 3 files for the Stan model, R code and Python code respectively: model.stan stan_fit.r hurdle_model.ipynb</p> <p>The figures generated for the paper can be found at BH_M-sigma_compilation/Figures</p> <p>A novel approach to understanding the link between supermassive black holes and host galaxies © 2024 by Gabriel Sasseville is licensed under CC BY 4.0. To view a copy of this license, visit <a href="https://creativecommons.org/licenses/by/4.0/" rel="nofollow">https://creativecommons.org/licenses/by/4.0/</a></p>
Data from: "Eddington envelopes: The fate of stars on parabolic orbits tidally disrupted by supermassive black holes" (Price et al. 2024)
<p>The paper by Price et al. (2024; <a href="https://arxiv.org/abs/2404.09381">arXiv:2404.09381</a>) simulates the tidal disruption of a one solar mass polytropic star by a million-solar-mass supermassive black hole, using the Phantom general relativistic smoothed particle hydrodynamics code (Price et al. 2018). The code used to perform the simulations is available at:</p> <p><a href="https://github.com/danieljprice/phantom">https://github.com/danieljprice/phantom</a></p> <p>This dataset contains:</p> <ol> <li>Scripts, intermediate data products and other small files used to create each figure in the paper</li> <li>Selected snapshots and other raw data from the four main calculations shown in the paper</li> </ol> <p>The main datasets contain parameter files and snapshots from the simulations used to create figures in the paper.small data files from the simulations and post-processing scripts used to create the scientific results and figures shown in the paper. Each simulation dataset contains:</p> <p><strong>.setup file:</strong> parameter file used by phantomsetup to create the initial conditions for the star itself<br><br><strong>.in file:</strong> parameter file used by phantom to perform the calculation<br><br><strong>tde_00000, tde_00100, tde_00200 etc:</strong> binary code snapshots containing raw data (particle positions, velocities, thermal energy, etc), these can be read/visualised/converted using the free and open source codes SPLASH (Price et al. 2007):<br><br><a href="https://github.com/danieljprice/splash">https://github.com/danieljprice/splash</a></p> <p>or Sarracen:</p> <p><a href="https://github.com/ttricco/sarracen">https://github.com/ttricco/sarracen</a></p> <p>SPLASH was used to create figures in the paper. The format and ways to read these data files are described in:</p> <p><a href="https://phantomsph.readthedocs.io/en/latest/user-guide/dumpfile.html">https://phantomsph.readthedocs.io/en/latest/user-guide/dumpfile.html</a></p> <p><strong>tde01.ev, tde02.ev etc:</strong> ascii files (see header) containing global quantities like total angular momentum, total momentum, total energy etc as a function of time. Each number corresponds to a restart of the code (i.e. resubmission of the job to the queue on the cluster).</p> <p><strong>tde01.log, tde02.log: </strong>output log from the simulations themselves, this contains some useful information like the unit scalings, typical timestep and code performance, hardware information etc.</p> <p><em><strong>.defaults, .limits, .units and .filenames:</strong> parameter files used by SPLASH to create particular figures. For example, to use the files lightcurve.defaults, lightcurve.units, lightcurve.limits and lightcurve.filenames one would plot using splash -p lightcurve</em></p> <p>The relevant raw data directories are:</p> <p><strong>beta1_hres: </strong>raw data from the adiabatic, beta=1 calculation</p> <p><strong>beta5_hres:</strong> raw data from the adiabatic, beta=5 calculation</p> <p><strong>beta1_isentropic: </strong>raw data from the isentropic, beta=1 calculation with a non-spinning black hole</p> <p><strong>beta1_isentropic_kerr_a99_i60:</strong> raw data from the isentropic, beta=1 calculation with a maximally-spinning black hole with the initial stellar orbit at an incliation of 60 degrees to the black hole spin</p> <p><strong>The procedure to recreate each figure and post-processing analysis used in the paper is explained in the README.md placed in each directory unpacked from the figureX.zip file</strong></p> <p> </p>
Intermediate-Mass & Supermassive Black Hole Feedback in Cosmological Hydrodynamical Simulations
<p>Intermediate-Mass Black Holes (IMBHs: with mass between 100 to 10^6 Msun) historically comprise of an elusive population in the Universe compared to the widely observed Stellar-Mass and Supermassive Black Holes. An increasing fraction of low-mass galaxies are observed to host IMBHs at their centers; some of which show signatures of activity in the form of low-luminosity AGN. In this context, a pertinent theory is that there are dormant IMBHs at the centers of Dwarf Galaxies, which we explore by performing small-volume Cosmological Hydrodynamical Simulations. The IMBHs are expected to be more prevalent in low-mass halos. We also perform medium-volume cosmological simulations to explore feedback from supermassive BHs. Our simulations employ a modified version of the SPH code GADGET-3, and include baryonic feedback models: radiative cooling, star formation, chemical enrichment, stellar evolution, supernova feedback, AGN accretion and AGN kinetic feedback. We investigate the growth of central IMBHs and SMBHs in galaxies employing the different volume simulations, as well as the resulting BH feedback. We quantify the impact of central massive BHs on their host galaxies; especially the effects on star formation and galaxy gas properties.</p>
Relativistic dynamics of stars near a supermassive black hole
<p>This data was first presented in `Relativistic dynamics of stars near a supermassive black hole’ (Hamers et al. 2014, MNRAS 443, 1; http://mnras.oxfordjournals.org/content/443/1/355; doi: 10.1093/mnras/stu1126). It includes the first- and second-order diffusion coefficients (DFCs) from the S-star N-body simulations (cf. Section 5.1 from the paper) as a function of the angular-momentum variable \ell = \sqrt{1-e^2}, binned with respect to the semimajor axis (cf. Section 5.4 from the paper).</p> <p>Description of the comma-separated txt files:<br /> `a_bins.txt’ - the semimajor axis bins. Semimajor axes are given in units of mpc (milliparsec). First column: the index of the bin; second column: the lower bin value; third column: the upper bin value; fourth column: the mean value.<br /> `D12_l_index_a_bin_i.txt’ - the DFCs for the different semimajor axis bins as a function of \ell (i is the bin index). First column: the value of \ell; second column: the first-order DFC, in units of 1/Myr; third column: the second-order DFC, in units of 1/Myr.</p> <p>Adrian Hamers, 22 April 2016</p>
Data for "A binary system in the S cluster close to the supermassive black hole Sagittarius A*"
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