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375 results for “Compaction”
Compact continuum source finding for next generation radio surveys
<p>This is a data set that accompanies the paper "Compact continuum source finding for next generation radio surveys" (2012MNRAS.422.1812H)</p> <p>The image files and source catalogues contained here were used to test the completeness and false detection rate of a number of source finding algorithms including: Aegean, Selavy, Sfind, SExtractor, and IMSAD. These data can be used to assess the performance of future source finding codes, and to verify the the performance of code during development.</p>
Maize Phosphorus Leaf Deficiency (MPLD) Database | Compact Scientific Camera (original-processed)
<p>This database presents samples of maize leaves placed on a withe background, representing three levels of phosphorus deficiency: complete absence of the nutrient (labeled -P), half dose of the required phosphorus for normal plant development (-P50), and complete supply (C).</p><p>Its composed of two folders:</p><ul><li>Original_dataset: 722 jpg images of 1280 x 1020 pixels size divided into '_C', '-P' and '-P50' folders for class labels.</li><li>Processed_dataset: 2433 png images of 224 x 224 pixels size divided into '-C', '-P' and '-P50' folders for class labels.</li></ul>
Case study of self-compacting, fiber reinforced, lightweight concrete, intended for production of precast elements
<p>This a dataset set to paper entitled: "Case study of self-compacting, fiber reinforced, lightweight concrete, intended for production of precast elements".</p> <p>Dataset is one excel file divided in various sheets containing:</p> <ol> <li>Properties of used aggregates</li> <li>Initial properties of concrete</li> <li>Composition of concrete</li> <li>Concrete with fibres</li> <li>Final concrete</li> </ol>
The population of merging compact binaries inferred using gravitational waves through GWTC-3 - Data release
<p>Data associated with Figures, Tables, and population parameter samples associated with <br><strong>The population of merging compact binaries inferred using gravitational waves through GWTC-3 , </strong><br><strong><a href="https://dcc.ligo.org/LIGO-P2100239/public">LIGO DCC</a>, <a href="https://arxiv.org/abs/2111.03634">arXiv</a>, <a href="https://journals.aps.org/prx/abstract/10.1103/PhysRevX.13.011048">PRX</a>. </strong><br>This is v3, superseding v2. Please see the README.md for more information.</p>
SCORPIO ASKAP15 compact radio source catalogue
<p>This dataset provides the compact radio source catalogue data extracted from ASKAP observations (15 antennae) of the SCORPIO field at 912 MHz, carried out in the context of ASKAP EMU Early Science phase. The reference scientific publication is S.Riggi et al., to appear on MNRAS. </p> <p>The dataset includes:</p> <p>- Source catalogue in tabular format: Two ascii/FITS table files with a series of summary parameters for each catalogued source islands and fitted components, respectively. Table format (number of data columns and column description) is detailed in the CAESAR source finder online documentation at <a href="http://caesar-doc.readthedocs.io">https://caesar-doc.readthedocs.io</a>. Additionally, we provide an added-value source component catalogue table (ascii and FITS formats) with extra-information (corrected fluxes, radio/infrared cross-match info, spectral indices, etc.). Its format is described in the reference publication;</p> <p>- Source catalogue in ROOT format: A ROOT file storing the list of catalogued sources and relative components as a CAESAR <em>Source</em> C++ object. For each source the summary parameters plus detailed information at pixel level are available. The detailed format is described in the CAESAR API documentation at <a href="http://caesar-doc.readthedocs.io">https://caesar-doc.readthedocs.io</a>.</p> <p>- Source list in region format: Two DS9 region files with the list of catalogued source islands and fitted components, respectively reported as labelled polygons or ellipses.</p> <p>- Background maps in FITS format: Two FITS files with background and noise maps obtained in the source finding process.</p>
Identification at local and global scale: a case for using the Compact URI (CURIE) for life science data
<p>Panel A) A Local Resource Identifier (LRI) is not suited to global scale identification because of inevitable collisions: “9606” corresponds to a Pubmed article, a CGNC gene, a PubChem chemical, as well as an NCBI taxon (<em>Homo sapiens</em>), a BOLD taxon (<em>Bombycilla</em> <em>cedrorum</em>), and a GRIN taxon (<em>Catha</em> <em>edulis</em>)</p> <p>Panel B) Prefixing is often used to indicate the source of an LRI, but prefixes themselves are often undocumented and collide.</p> <p>Panel C) Prefixes may exist in alternate forms. When all of the alternates are not known, collapsing equivalent identifiers is tedious and incomplete.</p> <p>Panel D) CURIE syntax addresses these issues by having a prefix whose relationship with a resolving namespace is clearly documented.</p>
GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — Data Quality Products for GW Searches
<p>This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>).</p> <p>This release contains two data-quality products that are used by search analyses to help mitigate non-Gaussian noise in the detector data. Gating removes short-duration artifacts from the data by smoothly rolling the affected data to zero. The <a href="https://doi.org/10.1088/2632-2153/abab5f">iDQ glitch likelihood</a> uses machine learning to predict the probability that a non-Gaussian transient is present using information from auxiliary channels.</p> <p><br> <strong>Gating files used in analyses of O3 LIGO data</strong></p> <p>As a pre-processing step, the <a href="https://pycbc.org/">PyCBC</a> search pipeline uses an inverted-Tukey window to mitigate the effect of loud, non-Gaussian features in the data. This is further described in <a href="https://dx.doi.org/10.1088/0264-9381/33/21/215004">Usman <em>et al.</em> 2016</a>.</p> <p>A subset of these times are the times listed in the txt files</p> <ul> <li>H1-O3_GATES_1238166018-31197600.txt</li> <li>L1-O3_GATES_1238166018-31197600.txt</li> </ul> <p>These times in these files were chosen based on auxiliary monitors of overflows in the digital-to-analog converters used to control the positions of the test masses. The gated times (i.e. the time period where the data is zeroed) are time segments where these monitors recorded an overflow were. The central time and suggested half-width of zero time were chosen to fully cover these time seconds. The final gating parameter, the suggested taper time was chosen to be 0.5 to balance the cost of impacting more data with the window function versus introducing additional artifacts into the data.</p> <p>The syntax of the files themselves is</p> <p>{central time} {suggested half-width of zero time} {suggested taper time}</p> <p>with each row containing the parameters of a single gate.</p> <p>The included notebook provides an example of how to read in and apply one of the suggested gates.</p> <p><br> <strong>Renormalized iDQ timeseries</strong></p> <p>The renormalized iDQ timeseries data-quality product is used within the GstLAL search pipeline to generate results for GWTC-3. This data product was found to be statistically helpful in improving data quality within the <a href="https://lscsoft.docs.ligo.org/gstlal/">GstLAL</a> search pipeline. This is further described in <a href="https://arxiv.org/abs/2010.15282">Godwin <em>et al</em>. 2020</a>.</p> <p>This file contains a time series for each LIGO detector related to the probability of a glitch in the strain data given the behavior in analyzed auxiliary channels monitoring the behavior of the detectors and their environment.</p> <ul> <li>H1L1-IDQ_TIMESERIES-1256655642-12905976.h5</li> </ul> <p>The HDF5-formatted file contains two groups, H1 and L1, corresponding to LIGO Hanford and LIGO Livingston, respectively. Each group contains several datasets; the data dataset corresponds to the renormalized iDQ log-likelihoods, as described in <a href="http://doi.org/10.1088/2632-2153/abab5f">Godwin <em>et al</em>. 2020</a>, and the time dataset corresponds to the times associated with the renormalized iDQ log-likelihoods in the data dataset.</p> <p> </p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5636795 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p> </p> <p>For more general background on gravitational-wave data quality, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>. </p>
GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Data Quality Products for GW Searches
<p>This material is part of several data products associated with GWTC-2.1, the deep extended catalog of compact binary coalescences observed by the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration and the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration during the first half of the third observing run. For further information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2100063/public">dcc.ligo.org/LIGO-P2100063/public</a>), the related material linked from this page, and the GWTC-2.1 data release documentation (<a href="https://www.gw-openscience.org/GWTC-2.1/">www.gw-openscience.org/GWTC-2.1/</a>).</p> <p>This release contains data quality products that are used by search analyses to help mitigate non-Gaussian noise in the detector data.</p> <p><strong>Renormalized iDQ timeseries</strong></p> <p>This release contains the renormalized iDQ timeseries data quality product used within the GstLAL search to generate results for GWTC-2.1 as described in <a href="https://arxiv.org/abs/2010.15282">Goodwin <em>et al</em>. 2020</a>. This data product was found to be statistically helpful in improving data quality within the GstLAL search. For further information about iDQ see <a href="https://iopscience.iop.org/article/10.1088/2632-2153/abab5f">Essick <em>et al</em>. 2020</a>.</p> <p>The file </p> <ul> <li>H1L1-IDQ_TIMESERIES-1238166018-15843600.h5</li> </ul> <p>contains a time series for each LIGO detector related to the probability of a glitch in the strain data given the behavior in the analyzed auxiliary channels which monitor the behavior of the detectors and their environment.</p> <p>The HDF5-formatted file contains two groups, H1 and L1, corresponding to LIGO Hanford and LIGO Livingston, respectively. Each group contains several datasets; the data dataset corresponds to the renormalized iDQ log-likelihoods, as described in Godwin <em>et al</em>. 2020, and the time dataset corresponds to the times associated with the renormalized iDQ log-likelihoods in the data dataset.</p> <p> </p> <p>For more general background on gravitational-wave data quality, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the guide to <a href="https://doi.org/10.1088/1361-6382/ab685e">LIGO-Virgo data analysis</a>.</p>
GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Parameter Estimation Data Release
<p>This material is part of several data products associated with GWTC-2.1, an update to the second Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2100063/public">https://dcc.ligo.org/LIGO-P2100063/public</a>), the related material linked from this page, and the GWTC-2.1 data release documentation (<a href="https://www.gw-openscience.org/GWTC-2.1/">https://www.gw-openscience.org/GWTC-2.1/</a>).</p> <p><strong>Parameter estimation data release</strong></p> <p>This data release contains posterior samples (*.h5) for gravitational-wave candidates through the first part of the third observing run (O3a). We provide results for the 44 candidates that have a probability of astrophysical origin of over 0.5 from O3 as well as the 10 previously-reported binary-black-hole candidates from GWTC-1 (this excludes GW170817). There are two .h5 files per event</p> <ul> <li> <p>Cosmologically reweighted (*cosmo.h5)</p> </li> <li> <p>Not cosmologically reweighted (*nocosmo.h5)</p> </li> </ul> <p>The cosmologically reweighted posteriors are reweighted to have a luminosity-distance prior that has a uniform merger rate in the source's comoving frame. Each .h5 file contains samples for multiple runs with keys C01:RUN_NAME, where RUN_NAME is the waveform used for the run (and additional prior-choice information if necessary) or Mixed, indicating an equal mixture of samples from runs with similar physics if they exist. In cases where only one waveform was used, the Mixed dataset is simply a resampling of those results . GW190425 does not have Mixed samples. See the <a href="https://dcc.ligo.org/LIGO-P2100063/public">paper</a> appendices for further information. In addition to containing the posterior samples, the .h5 files also contain metadata about the analyses including the configuration files (which specify details such as the detector data analyzed), noise power spectral densities (potentially for a superset of the detectors used in the analysis) and calibration uncertainty envelopes.</p> <p>The python notebook explains how to use the posterior samples. This data release also contains .FITS skymap files, which can be read with <a href="https://lscsoft.docs.ligo.org/ligo.skymap/#">ligo.skymap</a>, and skymap statistics in *.txt files.</p> <p>The inference of the source parameters were performed with <a href="https://lscsoft.docs.ligo.org/bilby/">Bilby</a>, <a href="https://lscsoft.docs.ligo.org/parallel_bilby/">Parallel Bilby</a> and <a href="https://git.ligo.org/richard-oshaughnessy/research-projects-RIT/tree/temp-RIT-Tides">RIFT</a>. The results are formatted using <a href="https://lscsoft.docs.ligo.org/pesummary/">PESummary</a>.</p> <p><a href="https://zenodo.org/record/5546663#.YnAAcvPMKqC">A similar release has been made to accompany GWTC-3</a> for results from the second part of the third observing run.</p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5117702 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p>For more general background on gravitational-wave parameter estimation, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.</p>
Data set from: Rates of Compact Object Coalescences
<p><strong>Data from: Rates of Compact Object Coalescence </strong></p> <p><strong>Brief overview: </strong><br> This Zenodo entry contains the data that has been used to make the figures for the living review <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210714239M/abstract">"Rates of Compact Object Coalescence" by Ilya Mandel & Floor Broekgaarden (2021)</a>. To reproduce the figures, download all the <strong>*.csv</strong> files and run the jupyter notebook created to reproduce the results in the publicly available Github directory <a href="https://github.com/FloorBroekgaarden/Rates_of_Compact_Object_Coalescence">https://github.com/FloorBroekgaarden/Rates_of_Compact_Object_Coalescence</a> (the exact jupyter notebook can be found <a href="https://github.com/FloorBroekgaarden/Rates_of_Compact_Object_Coalescence/tree/main/plottingCode/Make_figures_Mandel_and_Broekgaarden_2021_COC_rates_review.ipynb">here</a>)</p> <p>For any suggestions, questions or inquiry, please email one, or both, of the authors: </p> <ul> <li><strong>Ilya Mandel</strong>: <em>ilya.mandel@monash.edu</em> </li> <li><strong>Floor Broekgaarden</strong>: <em>floor.broekgaarden@cfa.harvard.edu</em></li> </ul> <p>We very much welcome suggestions for additional/missing literature with rate predictions or measurements. </p> <p> </p> <p><strong>Extra figures:</strong><br> Extra figures that can be used can be found here:</p> <p><strong>Vertical figures: <a href="https://docs.google.com/presentation/d/1GqJ0k2zpnxBGwIYNeQ0BfsLSU7H2942gspL-PN_iaJY/edit?usp=sharing">https://docs.google.com/presentation/d/1GqJ0k2zpnxBGwIYNeQ0BfsLSU7H2942gspL-PN_iaJY/edit?usp=sharing</a> </strong></p> <p><br> The authors are currently working on making an interactive tool for plotting the rates that will be available soon. In the mean time, feel free to send requests for plots/figures to the authors. </p> <p><strong>Reference</strong><br> If you use this data/code for publication, please cite both the paper: <a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210714239M/abstract">Mandel & Broekgaarden (2021)</a> (<a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210714239M/abstract">https://ui.adsabs.harvard.edu/abs/2021arXiv210714239M/abstract</a>) and the dataset on Zenodo through it's doi (see tabs on the right of this zenodo entry) <br> <br> <strong>Details datafiles: </strong></p> <p>The PDF <strong>COC_rates_supplementary_material.pdf</strong> attached (and in the Github repository) describes how each of the rates in the data files of this Zenodo entry are retrieved. The other 26 files are .csv files, where each csv file contains the rates from one specific double compact object type: NS-NS, NS-BH or BH-BH, and specific rate group (isolated binary evolution, gravitational wave observations etc.). The files in this entry are: </p> <p> </p> <ul> <li><strong>Data_Mandel_and_Broekgaarden_2021.zip </strong>all the files below conveniently in one zip file so that you only have to do 1 download. <br> </li> <li><strong>COC_rates_supplementary_material.pdf </strong> # PDF document describing how the rates are retrieved and quoted rom each study<br> </li> <li><strong>BH-BH_rates_CHE.csv</strong> # BH-BH rates for chemically homogeneous evolution </li> <li><strong>BH-BH_rates_flybys.csv </strong> # BH-BH rates for formation from wide isolated binaries with dynamical interactions from flybys</li> <li><strong>BH-BH_rates_globular-clusters.csv</strong> # BH-BH rates for dynamical formation in globular clusters </li> <li><strong>BH-BH_rates_isolated-binary-evolution.csv</strong> # BH-BH rates for isolated binary evolution </li> <li><strong>BH-BH_rates_nuclear-clusters.csv</strong> # BH-BH rates for (dynamical )formation in (active) nuclear star clusters</li> <li><strong>BH-BH_rates_observations-GWs.csv</strong> # BH-BH rates for observations from gravitational waves</li> <li><strong>BH-BH_rates_population-III.csv</strong> # BH-BH rates for population-III stars </li> <li><strong>BH-BH_rates_primordial.csv </strong> # BH-BH rates for primordial formation</li> <li><strong>BH-BH_rates_triples.csv</strong>. # BH-BH rates for formation in (hierarchical) triples </li> <li><strong>BH-BH_rates_young-stellar-clusters.csv</strong> # BH-BH rates for dynamical formation in young/open star clusters <br> </li> <li><strong>NS-BH_rates_CHE.csv</strong> # NS-BH rates for chemically homogeneous evolution </li> <li><strong>NS-BH_rates_flybys.csv </strong> # BH-BH rates for formation from wide isolated binaries with dynamical interactions from flybys</li> <li><strong>NS-BH_rates_globular-clusters.csv</strong> # NS-BH rates for dynamical formation in globular clusters </li> <li><strong>NS-BH_rates_isolated-binary-evolution.csv. </strong># NS-BH rates for isolated binary evolution </li> <li><strong>NS-BH_rates_nuclear-clusters.csv</strong> # NS-BH rates for (dynamical )formation in (active) nuclear star clusters</li> <li><strong>NS-BH_rates_observations-GWs.csv</strong> # NS-BH rates for observations from gravitational waves</li> <li><strong>NS-BH_rates_population-III.csv</strong> # NS-BH rates for population-III stars </li> <li><strong>NS-BH_rates_triples.csv</strong> # NS-BH rates for formation in (hierarchical) triples </li> <li><strong>NS-BH_rates_young-stellar-clusters.csv</strong> # BH-BH rates for dynamical formation in young/open star clusters<br> </li> <li><strong>NS-NS_rates_globular-clusters.csv </strong># NS-NS rates for dynamical formation in globular clusters </li> <li><strong>NS-NS_rates_isolated-binary-evolution.csv </strong> # NS-NS rates for isolated binary evolution </li> <li><strong>NS-NS_rates_nuclear-clusters.csv </strong># NS-NS rates for (dynamical )formation in (active) nuclear star clusters</li> <li><strong>NS-NS_rates_observations-GWs.csv</strong> # NS-NS rates for observations from gravitational waves</li> <li><strong>NS-NS_rates_observations-kilonovae.csv</strong> # NS-NS rates for observations from kilonovae</li> <li><strong>NS-NS_rates_observations-pulsars.csv</strong> # NS-NS rates for observations from Galactic pulsars</li> <li><strong>NS-NS_rates_observations-sGRBs.csv </strong># NS-NS rates for observations short gamma-ray bursts</li> <li><strong>NS-NS_rates_triples.csv </strong># NS-NS rates for formation in (hierarchical) triples </li> <li><strong>NS-NS_rates_young-stellar-clusters.csv</strong> # NS-NS rates for dynamical formation in young/open star clusters </li> </ul> <p> </p> <p><strong>Each csv file contains the following header: </strong><br> ADS year # year of the paper in the ADS entry<br> ADS month # month of the paper in the ADS entry <br> ADS abstract link # link to the ADS abstract <br> ArXiv link # link to the ArXiv version of the paper <br> First Author # name of the first author<br> label string # label of the study, that corresponds to the label in the figure<br> code (optional) # name of the code used in this study <br> type of limit (for plotting, see jupyter notebook for a dictionary) # integer, that is used to map to a certain limit visualization in the plot (e.g. scatter points vs upper limit). </p> <p>Each entry takes two columns in the csv files. One for the rates (quoted under the header 'rate [Gpc^-3 yr^-1]') and one for "notes" where we sometimes added notes about the rates (such as whether it is an upper or lower limit). </p> <p> </p>
theoretical and experimental study of the deposition of dielectric stacks on twin-hole silica fibers for implementation of compact all-fiber resonators
<p>This dataset includes the Matlab code to engineer theoretically a Bragg stack made of different dielectric layers. By changing the number of alternating stacks, their thickness and the refractive index of each layer it is possible to obtain the transmission curve of the Bragg stack versus the wavelength of the light in a certain range of values. The dataset includes also the experimental measurements of the resonances related to one of the fabricated compact resonators (based on the twin-hole fiber not poled) and obtained sweeping the wavelength of the input light injected through one of the two Bragg stacks and collecting the power at the exit of the other Bragg stack. </p>
Compact version: Dataset for publication "Assessing the techno-economic benefits of LEMs for different grid topologies and prosumer shares"
<p>This is the compact version of the results. They contain only the relevant files for the analysis and figure creation of the paper.</p> <p>USE CASE:<br>If you do not want to access every single file of the results or rerun the scenarios, you should use the compact version.</p> <p>TOOL:<br><a href="https://github.com/TUM-Doepfert/lemlab/tree/doepfert2024_lem">lemlab</a></p>
GWTC-2.1: Deep extended-catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Sensitivity of search pipelines to simulated signals
<p>Results of search pipelines (GSTLAL, MBTA, PYCBC, PYCBC BBH) used to identify candidates in <a href="https://dcc.ligo.org/LIGO-P2100063/public">GWTC-2.1</a> on a set of simulated signals corresponding to binary neutron star (BNS), neutron star black holes (NSBH), and binary black holes (BBH) signals. Additionally, we include a README file which provides information on how to read these files.</p>
Dataset for "A Bayesian neural network predicts the dissolution of compact planetary systems"
<p>The dataset used for training and evaluating the models in the paper "A Bayesian neural network predicts the dissolution of compact planetary systems": https://arxiv.org/abs/2101.04117. </p> <p>The code for working with this dataset, and other links, can be found at: https://github.com/MilesCranmer/bnn_chaos_model.</p>
GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — O3 search sensitivity estimates
<p>This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the papers (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a> and <a href="http://dcc.ligo.org/LIGO-P2100239/public">dcc.ligo.org/LIGO-P2100239/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>).</p> <p><strong>Observing Run 3 (O3) Search Sensitivity Estimates</strong></p> <p>This document contains HDF injection summary files for search sensitivity estimates spanning the LIGO–Virgo–KAGRA (LVK) Collaborations' third observing run (O3).</p> <p>Details of the individual files can be found in</p> <ul> <li> o3-sensitivity-estimates.md</li> </ul> <p>including descriptions of the injected distributions and the HDF file format adopted.</p> <p>Separate files are provided for the two parts of the run, O3a and O3b, specified by the GPS start times and durations in the filenames, and for the entire O3 run (filename with no times specified).</p> <p>Separate files are also provided for subpopulations that span the Binary Neutron Star (bns), Neutron Star–Black Hole (nsbh), Binary Black Hole (bbh), and Intermediate Mass Black Hole (imbh) mass ranges. The subpopulations are combined into a single file (mixture) containing a mixture model that spans the union of all subpopulation.</p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5546675 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p> </p> <p>For more general background on gravitational-wave search analyses, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.</p> <p> </p>
GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — O1+O2+O3 Search Sensitivity Estimates
<p>This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the papers (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a> and <a href="http://dcc.ligo.org/LIGO-P2100239/public">dcc.ligo.org/LIGO-P2100239/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>).</p> <p><strong>O1 + O2 + O3 Search Sensitivity Estimates</strong></p> <p>This document contains HDF injection summary files for search sensitivity estimates spanning the LIGO–Virgo–KAGRA (LVK) Collaborations' first (O1), second (O2), and third (O3) observing runs.</p> <p>Details of individual files can be found in</p> <ul> <li> o1+o2+o3-sensitivity-estimates.md</li> </ul> <p>including descriptions of the HDF file format adopted.</p> <p>Separate files are provided for individual subpopulations that span the Binary Neutron Star (bns), Neutron Star–Black Hole (nsbh), Binary Black Hole (bbh), and Intermediate Mass Black Hole (imbh) mass ranges. Additionally, a single file spanning the union of those mass ranges (mixture) is provided.</p> <p>Sensitivity estimates for O1 and O2 are available via semi-analytic methods (estimates of the optimal network signal-to-noise ratio). Sensitivity estimates for O3 are available from real search results. Analysts should specify detection thresholds separately for each type of sensitivity estimate (e.g., a signal-to-noise cut for O1+O2 and a false alarm rate cut for O3).</p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5636815 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p> </p> <p>For more general background on gravitational-wave search analyses, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.</p>
GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — Parameter estimation data release
<p>This material is part of several data products associated with GWTC-3, the third Gravitational-Wave Transient Catalog from the <a href="https://www.ligo.org/">LIGO</a> Scientific Collaboration, the <a href="https://www.virgo-gw.eu/">Virgo</a> Collaboration, and the <a href="https://gwcenter.icrr.u-tokyo.ac.jp/en/">KAGRA</a> Collaboration. For more information, see the paper (<a href="https://dcc.ligo.org/LIGO-P2000318/public">dcc.ligo.org/LIGO-P2000318/public</a>), the related material linked from this page, and the GWTC-3 data release documentation (<a href="https://www.gw-openscience.org/GWTC-3/">www.gw-openscience.org/GWTC-3/</a>).</p> <p><strong>Parameter estimation data release</strong></p> <p>This data release contains posterior samples (*.h5) for gravitational-wave candidates from the second part of the third observing run (O3b).We provide results for the 35 candidates that have a probability of astrophysical origin of over 0.5, plus <a href="https://doi.org/10.3847/2041-8213/ac082e">GW200105_162426</a>, which is a clear outlier from the noise background. There are two .h5 files per event</p> <ul> <li>Cosmologically reweighted (*cosmo.h5)</li> <li>Not cosmologically reweighted (*nocosmo.h5)</li> </ul> <p>The cosmologically reweighted posteriors are reweighted to have a luminosity-distance prior that has a uniform merger rate in the source's comoving frame. See the <a href="http://dcc.ligo.org/LIGO-P2000318/public">paper</a> appendices for further information. In addition to containing the posterior samples, the .h5 files also contain metadata about the analyses including the configuration files (which specify details such as the detector data analysed), noise power spectral densities (potentially for a superset of the detectors used in the analysis) and calibration uncertainty envelopes.</p> <p>The inference of the source parameters were performed with <a href="https://lscsoft.docs.ligo.org/bilby/">Bilby</a>, <a href="https://lscsoft.docs.ligo.org/parallel_bilby/">Parallel Bilby</a> and <a href="https://git.ligo.org/richard-oshaughnessy/research-projects-RIT/tree/temp-RIT-Tides">RIFT</a>. The results are formatted using <a href="https://lscsoft.docs.ligo.org/pesummary/">PESummary</a>.</p> <p><strong>A note about mixed samples:</strong> The samples provided here are produced using different waveform approximants. The Mixed label indicates that equal numbers of samples have been included from two different waveform approximants. For the binary black holes, these are IMRPhenomXPHM and SEOBNRv4PHM (for more details, see GWTC3p0PEDataReleaseExample.ipynb included in this data release and the paper). As different waveforms were analysed with different codes, there are sometimes differences in some parameters due to conventions in the codes. For example:</p> <ul> <li>As RIFT does not sample over time of coalescence as Bilby does, the RIFT time of coalescence results have a posterior distribution with a single spike, whereas the Bilby results have a distribution of peaks representing different sky positions for the source.</li> <li>There are different conventions for the range of the polarization angle (either 0 to π or 0 to 2 π). The parameter psi_wrapped maps all results to the range 0 to π, should consistency be important.</li> <li>The likelihood may show small differences when different sampling rates were used for Bilby and RIFT. The log-likelihood is expected to have a relative shift between the two runs of a few nats.</li> </ul> <p>Due to these differences, care must be taken when using Mixed samples, which will contain results using both codes' conventions. This should not impact the most interesting quantities, such as the masses, and so should only be rarely an issue.</p> <p>A <a href="https://doi.org/10.5281/zenodo.5117702">similar parameter-estimation release has been made to accompany GWTC-2.1</a> for results from the first part of the third observing run.</p> <p><strong>Sky localization data release</strong></p> <p>The sky localization tar file (IGWN-GWTC3p0-v2-PESkyLocalizations.tar.gz) contains candidate sky localizations corresponding to different parameter estimation configurations (.fits). Two waveforms are used for the majority of targets (IMRPhenomXPHM and SEOBNRv4PHM) and additional waveforms are used for possible neutron star--black hole mergers (see the <a href="https://dcc.ligo.org/LIGO-P2000318/public">paper</a> for further information). If you do not mind which waveform, the sky localizations labelled "Mixed" include posterior samples from both waveforms used. A machine readable list (skyLocalizationFileList.csv) of sky localization files is included within the .tar.gz file for ease of use, where the Mixed results are indicated as Default=True.</p> <p><strong>Contour data release</strong></p> <p>The contour tar file (IGWN-GWTC3p0-v2-PEContours.tar.gz) contains the contour files used to produce Figures 8 and 9 in the <a href="http://dcc.ligo.org/LIGO-P2000318/public">paper</a>. The python notebook (GWTC3p0PEPlotContourData.ipynb) explains how to reproduce these figures (and an interactive version of these plots can be accessed at <a href="https://gwtc3-contours.streamlit.app/">gwtc3-contours.streamlit.app/</a>).</p> <p><strong>Python notebook</strong></p> <p>The Python notebook (GWTC3p0PEDataReleaseExample.ipynb) explains how to read and use the posterior samples with a selection of examples.</p> <p><strong>How to download all files from this page</strong></p> <p>If you would like to download all files on this page, we recommend <a href="https://gitlab.com/dvolgyes/zenodo_get">zenodo_get</a>:</p> <pre><code class="language-bash">pip install zenodo_get zenodo-get RECORD_ID_OR_DOI </code></pre> <p>where the record ID for the most recent version of this page is 5546662 and IDs for other versions can be found in the Versions section at the side of this page.</p> <p> </p> <p>For more general background on gravitational-wave parameter estimation, try the materials from a <a href="https://www.gw-openscience.org/workshops/">GW Open Data Workshop</a> or the <a href="https://doi.org/10.1088/1361-6382/ab685e">guide to LIGO–Virgo data analysis</a>.</p>
Assessment of the Axial Resolution of a Compact Gamma Camera With Coded Aperture Collimator
<p>The dataset contains 21 images of a point-like gamma source, taken with a compact gamma camera that was equipped with a coded aperture collimator. The pixel intensity represents the accumulated energy deposited by the captured gamma photons. This dataset was acquired as part of the following paper, to which the reader is referred for an in-depth explanation.</p> <p>Note: Although the TIFF files may appear as all black or all transparent images, they will be displayed correctly when opened with an image processing tool such as ImageJ or a Python script.</p> <p><strong>Assessment of the Axial Resolution of a Compact Gamma Camera With Coded Aperture Collimator<br></strong></p> <p><strong>Purpose:</strong> Handheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization due to their high sensitivity and the possibility of 3D imaging. We evaluated the axial resolution and computational performance of two reconstruction methods.<br><strong>Methods:</strong> An experimental gamma camera was set up consisting of the pixelated semiconductor detector Timepix3 and MURA mask of rank 31 with round holes of 0.08mm in diameter in a 0.11mm thick Tungsten sheet. A set of measurements was taken where a point-like gamma source was placed centrally at 21 different positions within the range of 12 to 100mm. For each source position, the detector image was reconstructed in 0.5mm steps around the true source position, resulting in an image stack. The axial resolution was assessed by the full width at half maximum (FWHM) of the contrast-to-noise ratio (CNR) profile along the z-axis of the stack. <br>Two reconstruction methods were compared: MURA Decoding and a 3D maximum likelihood expectation maximization algorithm (3D-MLEM). <br><strong>Results: </strong>While taking 4,400 times longer in computation, 3D-MLEM yielded a smaller axial FWHM and a higher CNR. The axial resolution degraded from 5.3mm and 1.8mm at 12mm to 42.2mm and 13.5mm at 100mm for MURA Decoding and 3D-MLEM respectively. <br><strong>Conclusion:</strong> Our results show that the coded aperture enables the depth estimation of single point-like sources in the near field. Here, 3D-MLEM offered a better axial resolution but was computationally much slower than MURA Decoding, whose reconstruction time is compatible with real-time imaging.</p>
Operating diagram of the incubator, two tiered modules contain six independent incubators. Three shallow hatching are (220 × 60 × 17 cm) stacked on top of each other to create a compact assembly in which each tier functions independently. Eighteen trays covered with eggs can be placed in each tier, allowing the simultaneous incubation of seven to nine lays. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Operating diagram of the incubator, two tiered modules contain six independent incubators. Three shallow hatching are (220 × 60 × 17 cm) stacked on top of each other to create a compact assembly in which each tier functions independently. Eighteen trays covered with eggs can be placed in each tier, allowing the simultaneous incubation of seven to nine lays.
Relationship between sediment particle size, compaction and penetration resistance.
<p>Data on median grain size, compaction (measured with a vane tester) and penetration resistance (measured with a light penetrometer) of intertidal sediments. These data are the source of a mathematical function showing the relationship between them presented in a paper describing a new light penetrometer for intertidal and infralittoral sediments.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.