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86 results for “hdf5”

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zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD1800-inf | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.CX2X.J3KW">Simulated QCD 1800-<span class="math-tex">\(\infty\)</span> Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 1400-1800 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.RC9V.B5KX">Simulated QCD 1400-1800 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 1000-1400 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.96U2.3YAH">Simulated QCD 1000-1400 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 800-1000 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.S3D5.KF2C">Simulated QCD 800-1000 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 470-600 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.BKTD.SGJX">Simulated QCD 470-600 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 300-470 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.X3XQ.USQR">Simulated QCD 300-470 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 170-300 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.WKRR.DCJP">Simulated QCD 170-300 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Open Data | Jet Primary Dataset | pT > 375 GeV | MOD HDF5 Format

<p>A dataset of 1,785,625 jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.UP77.P6PQ">Jet Primary Dataset of the CMS 2011A&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor. Particle Flow Candidates (PFCs) for each jet are provided and include information about the PFC kinematics, PDG ID, and vertex. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>There are corresponding datasets of simulated jets organized by hard parton&nbsp;<span class="math-tex">\(\hat p_T\)</span>&nbsp;also available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

CMS 2011A Simulation | Pythia 6 QCD 600-800 | pT > 375 GeV | MOD HDF5 Format

<p>Simulated QCD&nbsp;jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.EJT7.KSAY">Simulated QCD 600-800 Dataset&nbsp;of the CMS 2011&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are provided at generator (truth) level in the GEN files and after GEANT4 detector simulation in the SIM files (which also contain associated GEN jets to facilitate studies involving both types of jets).&nbsp;Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger (only relevant for SIM) and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor (again, only relevant for SIM). GEN jets contain&nbsp;truth-level particles with kinematic and PDG ID information,&nbsp;and SIM jets contain Particle Flow Candidates (PFCs) with kinematic, PDG ID, and vertex information. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and (in the case of SIM) have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>For reference, the other corresponding&nbsp;datasets of simulated jets&nbsp;available on Zenodo are:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul> <p>There is an associated&nbsp;dataset&nbsp;of jets recorded by the CMS detector available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3340205">CMS 2011A Jets,&nbsp;pT &gt; 375 GeV</a></li> </ul> <p>Changes:</p> <ul> <li>v1 - Uploaded missing file.</li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo44/100

TAASRAD19 Radar Sequences 2010-2019 HDF5

<p>TAASRAD19 (Trentino-Alto Adige/S&uuml;dtirol Radar 2019) is a high-resolution radar reflectivity dataset collected by the Civil Protection weather radar of the Trentino South Tyrol Region, in the Italian Alps.<br> The dataset includes 894,916 scans of precipitation from more than 9 years of data, offering a novel resource to develop and benchmark analog ensemble models and machine learning solutions for precipitation nowcasting. Data are expressed as 2D images, considering the maximum reflectivity on the vertical section and 5 minutes sampling rate, covering an area of 240km of diameter at 500m horizontal resolution. The TAASRAD19 distribution also includes a curated set of 1,732 sequences, for a total of 362,233 radar images, labeled with precipitation type tags assigned by expert meteorologists. We validated TAASRAD19 as a benchmark for nowcasting using deep learning model to forecast reflectivity and a procedure based on the UMAP dimensionality reduction method for interactive exploration.<br> Software methods for data pre-processing, model training and inference, and a pre-trained model are<br> publicly available at&nbsp;https://github.com/MPBA/TAASRAD19 for replication and reproducibility.</p>

opencc-by-4.0May 2020View details →
zenodo44/100

A multiple model high-resolution head-related impulse response database for aided and unaided ears (HDF5 format)

<p>The Multiple-Model High Resolution HRTF database is a collection of HRTFs measured using four different Head-and-Torso Simulators at high spatial resolution (2 degree azimuth and elevation).&nbsp; The data here is stored in HDF5 files, the SOFA files are published in a separate dataset <a href="https://zenodo.org/record/2582553">doi:10.5281/zenodo.2582553</a>.</p>

opencc-by-4.0Apr 2018View details →
zenodo44/100

Z + up to 9 jets parton level events at 14 TeV in HDF5

<p>Z + up to 9 jets at 14 TeV parton level events in HDF5 file format.</p> <p>Merging scale is at 20 GeV.</p> <p>This data was used in FERMILAB-PUB-19-192-T</p>

opencc-by-4.0May 2019View details →
zenodo44/100

Wplus + up to 9 jets parton level events at 14 TeV in HDF5

<p>Wplus + up to 9 jets partonic events at 14TeV</p> <p>Merging scale is at 20 GeV.</p> <p>This data was used in FERMILAB-PUB-19-192-T</p>

opencc-by-4.0May 2019View details →
zenodo40/100

METIS case study PSHA: openquake hdf5 output files for Conditional Spectra

<p>This dataset (V2) contains the disaggregation results, the hdf5 files for the Conditional Spectra are in V1</p>

opencc-by-4.0Feb 2024View details →
zenodo40/100

HDF5 datasets and python scripts to generate figures in "Butterfly distribution of relativistic electrons driven by parallel propagating lower band whistler chorus waves"

<p>HDF5 datasets and python scripts to generate figures in &quot;Butterfly distribution of relativistic electrons driven by parallel propagating lower band whistler chorus waves&quot;</p> <p>RBW simulation datasets in HDF5 format:</p> <ul> <li>300pT.h5&nbsp; &nbsp; The particle dataset to generate the figures.</li> </ul> <p>Python scripts to generate figures in the manuscript.</p> <p>- Environment:&nbsp;Python 3.6.7 :: Anaconda 4.4.0 (64-bit)</p> <p>- Required modules: matplotlib, numpy, h5py</p> <ul> <li>Figure1.py&nbsp; &nbsp; Generate figure 1.</li> <li>Figure2.py&nbsp; &nbsp; Generate figure 2.</li> <li>Figure3.py&nbsp; &nbsp; Generate figure 3.</li> <li>Figure4.py&nbsp; &nbsp; Generate figure 4.</li> <li>QLDe.py&nbsp; &nbsp; &nbsp; &nbsp;Calculate bounce averaged diffusion coefficients according to&nbsp;Shprits et al. (2006) (doi: https://doi.org/10.1029/ 2006JA011725).</li> </ul> <p>&nbsp;</p>

opencc-by-4.0Apr 2022View details →
zenodo40/100

HDF5 Table for Machine Learning on Difference image analysis

<p>A table with the features.</p> <p>There exists several tables within this file.</p> <p>Each table is a set of transient candidates, with the column IS_REAL stating their status of real or bogus.</p>

opencc-by-4.0May 2019View details →
zenodo40/100

Wminus + up to 9 jets parton level events at 14 TeV in HDF5

<p>Wminus + up to 9 jets parton level events at 14 TeV</p> <p>Merging scale is at 20 GeV.</p> <p>This data was used in FERMILAB-PUB-19-192-T</p>

opencc-by-4.0May 2019View details →
zenodo40/100

RDF2Vec DBpedia uniform embeddings in HDF5 file format

<p>This dataset contains the vectors from computing RDF2vec embeddings from a uniformly weighted DBpedia 2016-04 graph.</p> <p>The file has a group called &quot;Vectors&quot; which contains a dataset for each entity in the graph. The dataset name is the entity name and the dataset content&nbsp;is the embedded vector&nbsp;(length 200).</p> <p>The parameter settings for the embedding are as specified in the paper:</p> <p>Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Biased graph walks for RDF graph embeddings. In <em>Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics</em> (WIMS &#39;17). ACM, New York, NY, USA, Article 21, 12 pages. DOI: https://doi.org/10.1145/3102254.3102279</p>

opencc-by-sa-4.0Jun 2017View details →
zenodo40/100

Preprocessed MPI System Matrix Data in HDF5 Files

<p>This data repository contains preprocessed system matrix data from&nbsp;magnetic particle imaging. The example files are hdf5. The data is used in this code example:</p> <p><a href="https://github.com/Ivo-B/3dSMRnet">github.com/Ivo-B/3dSMRnet</a></p>

opencc-by-4.0Jul 2023View details →
zenodo36/100

ATLAS MC QUALIFICATION TASK HDF5

<p>This is an HDF5 dataset to be used for developing the workflow integration of HDF5 Les Houches + CKKWL merging with Pythia8<br> in ATHENA</p>

opencc-by-4.0Feb 2020View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record