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65 results for “redshift”
Data for 'Cosmology with Binary Neutron Stars: Does Mass-Redshift Correlation Matter?'
<p>The code is available at the following GitHub link: https://github.com/SoumendraRoy/RedevolBNS</p> <p>To generate the plots in the paper, see: https://github.com/SoumendraRoy/RedevolBNS/tree/main/Make_Plots</p> <p>A frozen version of the Make_Plots is included here.</p> <p>Description of the files:</p> <ol> <li><a href="https://zenodo.org/api/records/14704635/draft/files/Cosmo_Plots.ipynb/content" target="_blank" rel="noopener noreferrer">Cosmo_Plots.ipynb</a>, <a href="https://zenodo.org/api/records/14704635/draft/files/Pop_Plots.ipynb/content" target="_blank" rel="noopener noreferrer">Pop_Plots.ipynb</a> : Jupyter notebooks containing all plots in the main text.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/Appendix_Plots.ipynb/content" target="_blank" rel="noopener noreferrer">Appendix_Plots.ipynb</a>, <a href="https://zenodo.org/api/records/14704635/draft/files/All_Contours.ipynb/content" target="_blank" rel="noopener noreferrer">All_Contours.ipynb</a> : Jupyter notebooks containing all plots in Appendix.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/inference_marginal_fiducial.h5/content" target="_blank" rel="noopener noreferrer">inference_marginal_fiducial.h5</a>, <a href="https://zenodo.org/api/records/14704635/draft/files/inference_full_fiducial.h5/content" target="_blank" rel="noopener noreferrer">inference_full_fiducial.h5</a> : The samples of the Hubble constant and dark matter density for the fiducial injected population, with uncorrelated and correlated mass-redshift populations, respectively.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/inference_marginal_MM.h5/content" target="_blank" rel="noopener noreferrer">inference_marginal_MM.h5</a>, <a href="https://zenodo.org/api/records/14704635/draft/files/inference_full_MM.h5/content" target="_blank" rel="noopener noreferrer">inference_full_MM.h5</a> : The samples of the Hubble constant and dark matter density for the Mandel-Müller injected population, with uncorrelated and correlated mass-redshift populations, respectively.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/inference_full_result_Uncorrelated.h5/content" target="_blank" rel="noopener noreferrer">inference_full_result_Uncorrelated.h5</a>, <a href="https://zenodo.org/api/records/14704635/draft/files/inference_full_result_Injected.h5/content" target="_blank" rel="noopener noreferrer">inference_full_result_Injected.h5</a> : The samples of the Hubble constant and dark matter density for the fiducial injected population, with uncorrelated and correlated mass-redshift populations, respectively for varying number of detections.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/simulation.h5/content" target="_blank" rel="noopener noreferrer">simulation.h5</a> : The injected mass, redshift samples for different population synthesis variations.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/compare_pop.h5/content" target="_blank" rel="noopener noreferrer">compare_pop.h5</a>, <a href="https://zenodo.org/api/records/14704635/draft/files/variant_pop.h5/content" target="_blank" rel="noopener noreferrer">variant_pop.h5</a> : Comparison of different population synthesis variations.</li> <li><a href="https://zenodo.org/api/records/14704635/draft/files/gmm.h5/content" target="_blank" rel="noopener noreferrer">gmm.h5</a> : Gaussian mixture model fit of the fiducial and Mandel-Müller injected population.</li> </ol>
Photometric redshifts for quasars from WISE-PS1-STRM
<p>Photometric redshift estimations for quasars</p> <p>In this repository we publish our photometric redshift catalogue of quasar candidates found in the cross-matched catalogue of the WISE All-Sky and PS1 3π DR2 sky surveys. Altogether there are 4,849,634 quasars in the catalog from which 2,879,298 are covered by our training set. When using this data please cite our work<br> https://doi.org/10.48550/arXiv.2206.01440. Below you can find the description of each column:</p> <ul> <li><strong>objID_PS1</strong>: object id in the PannSTARRS DR2 catalogue</li> <li><strong>raMean</strong>: rectascension of the object</li> <li><strong>decMean</strong>: declination of the object</li> <li><strong>w1mpro</strong>: PSF profile-fitting magnitude measured in WISE W1 filter</li> <li><strong>w1sigmpro</strong>: error estimation of w1mpro</li> <li><strong>w1mag</strong>: aperture magnitude related to 8.25" radius circular apertures measured in WISE W1 filter</li> <li><strong>w1sigm</strong>: error estimation of w1mag</li> <li><strong>w2mpro</strong>: PSF profile-fitting magnitude measured in WISE W2 filter</li> <li><strong>w2sigmpro</strong>: error estimation of w2mpro</li> <li><strong>w2mag</strong>: aperture magnitude related to 8.25" radius circular apertures measured in WISE W2 filter</li> <li><strong>w2sigm</strong>: error estimation of w2mag</li> <li><strong>gFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 g filter</li> <li><strong>gFPSFMagErr</strong>: error estimation of gFPSFMag</li> <li><strong>rFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 r filter</li> <li><strong>rFPSFMagErr</strong>: error estimation of rFPSFMag</li> <li><strong>iFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 i filter</li> <li><strong>iFPSFMagErr</strong>: error estimation of iFPSFMag</li> <li><strong>zFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 z filter</li> <li><strong>zFPSFMagErr</strong>: error estimation of zFPSFMag</li> <li><strong>yFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 y filter</li> <li><strong>yFPSFMagErr</strong>: error estimation of yFPSFMag</li> <li><strong>gFKronMag</strong>: Kron magnitude measured in PS1 g filter</li> <li><strong>gFKronMagErr</strong>: error estimation of gFKronMag</li> <li><strong>rFKronMag</strong>: Kron magnitude measured in PS1 r filter</li> <li><strong>rFKronMagErr</strong>: error estimation of rFKronMag</li> <li><strong>iFKronMag</strong>: Kron magnitude measured in PS1 i filter</li> <li><strong>iFKronMagErr</strong>: error estimation of iFKronMag</li> <li><strong>zFKronMag</strong>: Kron magnitude measured in PS1 z filter</li> <li><strong>zFKronMagErr</strong>: error estimation of zFKronMag</li> <li><strong>yFKronMag</strong>: Kron magnitude measured in PS1 y filter</li> <li><strong>yFKronMagErr</strong>: error estimation of yFKronMag</li> <li><strong>EBV_PS1</strong>: E(B-V) dust extinction values</li> <li><strong>EXT</strong>: flag denoting an object being extrapolated or not. It is 1 if the object is extraplolated and 0 if not.</li> <li><strong>z_pred_mean</strong>: photometric redshift estimation</li> <li><strong>z_pred_std</strong>: uncertainty of z_pred_mean</li> <li><strong>spectroz</strong>: spectroscopic redshift of the object if available and -999 otherwise</li> </ul>
Additional Data for "Shock cooling of a red-supergiant supernova at redshift 3 in lensed images"
<p><strong>The dataset includes additional data for the journal paper “Shock cooling of a red-supergiant supernova at redshift 3 in lensed images” by W. Chen et al., 2022. As described in the paper, these data include the MMT spectroscopic data, the HST coaddition and image differencing data, the GALFIT scripts and resulting models, the HST photometry of the SN host galaxy, the lens model, the SN light curve fitting script and resulting MCMC data, and plots of distributions of the model parameters and the best-fit light curves.</strong></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>
Photometric redshifts for quasars from WISE-PS1-STRM
<p>Photometric redshift estimations for quasars</p> <p>In this repository we publish our photometric redshift catalogue of quasar candidates found in the cross-matched catalogue of the WISE All-Sky and PS1 3π DR2 sky surveys. Altogether there are 4,849,607 quasars in the catalog from which 2,879,273 are covered by our training set. When using this data please cite our work<br> https://doi.org/10.48550/arXiv.2206.01440. Below you can find the description of each column:</p> <ul> <li><strong>objID_PS1</strong>: object id in the PanSTARRS DR2 catalogue</li> <li><strong>raMean</strong>: rectascension of the object</li> <li><strong>decMean</strong>: declination of the object</li> <li><strong>w1mpro</strong>: PSF profile-fitting magnitude measured in WISE W1 filter</li> <li><strong>w1sigmpro</strong>: error estimation of w1mpro</li> <li><strong>w1mag</strong>: aperture magnitude related to 8.25" radius circular apertures measured in WISE W1 filter</li> <li><strong>w1sigm</strong>: error estimation of w1mag</li> <li><strong>w2mpro</strong>: PSF profile-fitting magnitude measured in WISE W2 filter</li> <li><strong>w2sigmpro</strong>: error estimation of w2mpro</li> <li><strong>w2mag</strong>: aperture magnitude related to 8.25" radius circular apertures measured in WISE W2 filter</li> <li><strong>w2sigm</strong>: error estimation of w2mag</li> <li><strong>gFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 g filter</li> <li><strong>gFPSFMagErr</strong>: error estimation of gFPSFMag</li> <li><strong>rFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 r filter</li> <li><strong>rFPSFMagErr</strong>: error estimation of rFPSFMag</li> <li><strong>iFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 i filter</li> <li><strong>iFPSFMagErr</strong>: error estimation of iFPSFMag</li> <li><strong>zFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 z filter</li> <li><strong>zFPSFMagErr</strong>: error estimation of zFPSFMag</li> <li><strong>yFPSFMag</strong>: PSF profile-fitting magnitude measured in PS1 y filter</li> <li><strong>yFPSFMagErr</strong>: error estimation of yFPSFMag</li> <li><strong>gFKronMag</strong>: Kron magnitude measured in PS1 g filter</li> <li><strong>gFKronMagErr</strong>: error estimation of gFKronMag</li> <li><strong>rFKronMag</strong>: Kron magnitude measured in PS1 r filter</li> <li><strong>rFKronMagErr</strong>: error estimation of rFKronMag</li> <li><strong>iFKronMag</strong>: Kron magnitude measured in PS1 i filter</li> <li><strong>iFKronMagErr</strong>: error estimation of iFKronMag</li> <li><strong>zFKronMag</strong>: Kron magnitude measured in PS1 z filter</li> <li><strong>zFKronMagErr</strong>: error estimation of zFKronMag</li> <li><strong>yFKronMag</strong>: Kron magnitude measured in PS1 y filter</li> <li><strong>yFKronMagErr</strong>: error estimation of yFKronMag</li> <li><strong>EBV_PS1</strong>: E(B-V) dust extinction values</li> <li><strong>EXT</strong>: flag denoting an object being extrapolated or not in the 12-dimensional color index space. It is 1 if the object is extrapolated and 0 if not.</li> <li><strong>DIST</strong>: average distance measured between the inference data points and their spectroscopic neighbors in the 12-dimensional color index space.</li> <li><strong>z_pred</strong>: photometric redshift estimation (predicted from color indices)</li> <li><strong>z_pred_std</strong>: uncertainty of z_pred</li> <li><strong>spectroz</strong>: spectroscopic redshift of the object if available and -999 otherwise</li> <li><strong>EXT2</strong>: flag denoting an object being extrapolated or not in the 13-dimensional color index+magnitude space. It is 1 if the object is extrapolated and 0 if not.</li> <li><strong>DIST2</strong>: average distance measured between the inference data points and their spectroscopic neighbors in the 13-dimensional color index+magnitude space.</li> <li><strong>z_pred2</strong>: photometric redshift estimation (predicted from color indices+magnitude)</li> <li><strong>z_pred_std2</strong>: uncertainty of z_pred2</li> </ul>
Archetype-Based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey
<p>Supplementary material to DESI's publication "Archetype-Based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey" by Anand et al. 2024 to comply with the data management plan. The material includes all the data shown in the figures of the results of the paper.</p>
Data for: Redshift Prediction with Images for Cosmology using a Bayesian Convolutional Neural Network with Conformal Predictions
<p>These files contain the predictions from the CNN and BCNN model from the paper titled: "Redshift Prediction with Images for Cosmology using a Bayesian Convolutional Neural Network with Conformal Predictions" (Jones et al. 2024). These files will allow reproduction of the performance metrics described in the paper.</p> <p> </p> <p>full_prediction_set_CNN.csv - predictions for the redshift using the CNN model of the entire dataset<br>cnn_evaluation.csv - predictions from just the evaluation dataset that was not used in training</p> <p>Columns are:</p> <p>photoz - predicted photoz from the model<br>specz - spectroscopic redshift<br>objectid - object ID from HSC PDR2 data release (Aihara et al. 2019)</p> <p><br>full_prediction_set_BCNN.csv - predictions for the redshift using the BCNN model of the entire dataset<br>bcnn_evaluation.csv - predictions from just the evaluation dataset that was not used in training</p> <p>Columns are:</p> <p>photoz - predicted photoz from the model<br>specz - spectroscopic redshift<br>objectid - object ID from HSC PDR2 data release (Aihara et al. 2019)<br>photoz_uncertainty - uncertainty in the predicted photoz</p>
Hubble Frontier Field Clusters and their Parallel Fields: Photometric and Photometric Redshift Catalogs
<p>Source catalogs of the Hubble Frontier Field clusters and parallel fields. If used, please cite https://ui.adsabs.harvard.edu/abs/2021arXiv210301952P/abstract</p>
Halo power spectrum computed in real and redshift space
<p>Halo power spectrum computed from the halo catalogs in-<br> terpolated on a 4003 mesh, in real (P(k)) and redshift space, the lat-<br> ter represented through the monopole P0(k), the quadrupole P2(k)<br> and the hexadecapole P4(k). The main panels show the mean from<br> 80 SLICS realizations (green dashed line) and the mean from the<br> same number of BAM mocks (solid gray lines). The bottom panels<br> show the ratio between the mean spectra from the BAM mocks to<br> the mean from the SLICS. The gray area in the ratios show the 1σ<br> region computed from the means and their respective errors.</p>
Data for "The DESI One-Percent Survey: Evidence for Assembly Bias from Low-Redshift Counts-in-Cylinders Measurements"
<p>Summary statistics, covariance matrices, and MCMC results for each of our HOD samples. For links to the original data catalogs and instructions to reproduce the analysis, see the README at: <a href="https://github.com/AlanPearl/galtab/tree/main/galtab/paper2/">https://github.com/AlanPearl/galtab/tree/main/galtab/paper2/</a></p> <p>In brief, the desi_observations/desi_obs_*.npz files contain information about each threshold/redshift sample. Data is loaded via `obs_data = np.load(filename, allow_pickle=True)`, and all available fields can be shown via `obs_data.keys()`. Most importantly, our target data and its corresponding covariance matrix can be accessed with the "mean" and "cov" keys, respectively. These arrays can be sliced into our three observables using the slice objects accessed with the "slice_n", "slice_wp", and "slice_cic" keys.<br><br>The emcee MCMC chains for each sample can be found under desi_results/results_*/emcee_backend.h5. To access the chain data (i.e., to construct corner plots of our HOD parameters), you can either follow our paper plot notebooks linked in the README above, or see the <a href="https://emcee.readthedocs.io/en/stable/">emcee documentation</a>.</p>
Mapping the Redshift Evolution of Hα Equivalent Width Distributions & RST Grism Surveys
<p>The Hα Equivalent Width (EW) is an observational proxy for the specific star formation rate (sSFR) and can give us valuable insight in regards to bursty star formation histories. Studies find Hα EW anti-correlates with stellar mass and increases in redshift similar to the `main sequence’ and sSFR redshift evolution. However, selection effects may bias the underlying results, such that measurements of the intrinsic correlations are needed. In this talk, I will be presenting a new methodology of constraining EW distributions by simulating emission line galaxies assuming an intrinsic EW distribution and applying selection criteria to match observations drawn from Hα narrowband surveys between z ~ 0.4 and 2. This nicely overlaps with the expected redshift coverage of RST planned surveys. We find EW intrinsically correlates with Hα luminosity and stellar mass, while ignoring selection effect corrections causes a steeper correlation. We also observe an increasing redshift evolution between EW and stellar mass. The correlation between EW and stellar mass is found to reproduce the EW distribution, LF, and SMF at all redshifts probed, which suggests it is shaped by physical processes associated with star formation. I will finish by discussing the implication of our results for RST survey planning by taking into account the effective EW threshold in slitless grism surveys set by the limiting resolving power using the redshift evolution of the EW — stellar mass correlation.</p>
Dark Sky Simulations ds14_a redshift=0 Mass Power Spectrum
<p>Dark Sky Simulations ds14_a redshift=0 Mass Power Spectrum</p>
ErikVini/specz_compilation: Southern Hemisphere Spectrocopic Redshift Compilation
<p>A new version of the catalogue was published. The catalogue was created on 2025-03-27 (YYYY-MM-DD).</p> <p>The new data and changelog can be found in the Zenodo page: <a href="https://zenodo.org/records/15114194">link</a></p> <p><strong>This version only contains a copy of the GitHub repository. To download the data, please follow the link above (for version v4)</strong></p>
Temperature of the neutral CGM around high-redshift galaxies
<p>Gas in galaxy halos is the result of an interplay between the AGN/stellar outflows and the inflows from intergalactic medium. Observational constraints on the CGM properties provide a clue for the cosmological simulations and shed a light on the feedback mechanisms, which are responsible for the baryonic cycle and determine the CGM energy distribution. Due to the complex nature of CGM, understanding of the feedback processes requires a comprehensive study of the halo gas in hot ionized as well as warm and cold neutral phases. Unfortunately, in contrast with a cold and ionized gas, estimation of the temperature of warm phase is a difficult task. This can be overcome using the analysis of the absorption lines imprinted onto quasar spectra (Noterdaeme et al. 2021). We present such measurements of the warm CGM temperature, based on a sample of Damped Lyman-alpha systems in high-resolution high-redshift (z~2) VLT/UVES spectra. We show that warm neutral circum-galactic gas demonstrates a huge variety of estimated temperatures, which in some cases exceed the canonical Galactic value of ~10 000 K generally assumed in thermal balance models.</p> <p>Noterdaeme et al., A&A 651, A78 (2021)</p>
Triplet Sensitization Enables Bidirectional Isomerization of Diazocine with 130 nm Redshift in Excitation Wavelengths
<p>Dataset for the accepted manuscript</p>
Estimating the redshift error in supernova data analysis_Code supplement
<p>Supplement for 'Estimating the redshift error in supernova data analysis'</p>
The first identification of Lyman $\alpha$ Changing-look Quasars at high-redshift in DESI
Open the record for dataset details and reuse information.
XMM2ATHENA: Catalogue of photometric redshifts for 4XMM-DR11/DES/VHS
<p>We provide photometric redshift estimations for 4XMM sources having optical DES counterparts, identified as AGN in the classification catalogue and outside the galactic plane.</p> <p>For more details, visit the <a href="http://xmm-ssc.irap.omp.eu/xmm2athena/catalogues/">XMM2ATHENA project site</a>.</p>
X-ray properties of high-redshift Radio Loud and Radio Quiet Quasars observed by Chandra
<p><a href="http://arxiv.org/abs/2301.02866">X-ray properties of high-redshift Radio Loud and Radio Quiet Quasars observed by Chandra</a></p> <p>The following data set presents the data used in our research paper "X-ray properties of high-redshift Radio Loud and Radio Quiet Quasars observed by Chandra " <a href="http://http://arxiv.org/abs/2301.02866">http://arxiv.org/abs/2301.02866</a>. These tables contain the X-rays parameters of our selected sample of quasars. The file name acronames are (RLQ: Radio Loud Quasars), (RQQ: Radio Quiet Quasars), and (RIQ: Radio Intermediate Quasars). The number in the files name indicates the number of quasars in this file. Each parameter has its corresponding data type, physical description, and unit.</p>
Posterior samples of high-redshift binary black holes
<p>Catalog of the posterior samples of the simulations reported in the paper "<a href="https://doi.org/10.3847/2041-8213/ac6bea">On the Single-event-based Identification of Primordial Black Hole Mergers at Cosmological Distances</a>" (arXiv:2108.07276).</p>
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