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39 results for “Pair Production”
S66 | EAWAGTPS | Parent-Transformation Product Pairs from Eawag
<p>This is the collection associated with list S66 EAWAGTPS - Parent-Transformation Product Pairs from Eawag on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>Parent-Transformation Product Pairs of various micropollutants from Eawag: Swiss Federal Institute for Aquatic Science and Technology (<a href="https://www.eawag.ch/en/">https://www.eawag.ch/en/</a>), described in Schollee et al 2017 DOI:<a href="http://doi.org/10.1007/s13361-017-1797-6">10.1007/s13361-017-1797-6</a> . Dataset DOI: 10.5281/zenodo.3754448</p> <p>Update 23/04/2020: fixed names, added synonym columns and classification information.<br>Update 15/05/2020: adjusted classification information following feedback from Juliane.<br>Update 13/01/2023: adjusted <a href="https://gitlab.lcsb.uni.lu/eci/pubchem/-/commit/447d9a7eabe3660732a80ad261cf80b7491cc027" target="_blank" rel="noopener">selected BT entries</a> based on feedback from Emma Palm.<br>Update 07/02/2023: adjusted <a href="https://gitlab.lcsb.uni.lu/eci/pubchem/-/commit/6b56bd345b1598081062607d458927dd99bd64d2" target="_blank" rel="noopener">selected BT entries</a> to fix 4-Me-BT issues. </p>
Top quark pair production at the LHC, with all hadronic resolved decays for solving event combinatorics
<p><strong>R&D Datasets for solving event combinatorics in all hadronic top quark pair events at the LHC.</strong></p> <p>Used in the development of Topographs: Topological Reconstruction of Particle Physics Processes using Graph Neural Networks</p> <p> </p> <p>The datasets contain 5.8M ttbar events in the all hadronic decay channel, with jets matched to the truth partons in the top quark decays.</p> <p> </p> <p><strong>Event generation</strong></p> <ul> <li>Centre of Mass energy: 13 TeV</li> <li>MC Generator: MadGraph5_aMC@NLO v3.1.0, with MadSpin modelling the decays of the top quarks and W bosons.</li> <li>Parton Shower: Pythia v .243</li> <li>Detector response: Delphes v3.4.2 using ATLAS-like geometry</li> <li>Jets reconstructed with anti-kt algorithm, R=0.4, using FastJet</li> <li>b-Tagging corresponds to inclusive 70% b-jet efficiency</li> </ul> <p><strong>Event selection and truth matching</strong></p> <ul> <li>All events are required to have at least six reconstructed jets and exactly zero leptons (electrons or muons)</li> <li>Partons are matched to jets using <span class="math-tex">\(\Delta R\)</span> matching, with <span class="math-tex">\(\Delta R < 0.4\)</span></li> <li>Events with partons matched to multiple jets or jets to multiple partons are discarded</li> <li>Up to 16 jets are stored per event</li> </ul> <p>In the training dataset 1,340,000 events have all partons from the ttbar decays matched to jets.</p> <p>In the validation dataset, 71,000 events have all partons from the ttbar decays matched to jets.</p> <p>In the testing dataset 76,000 events have all partons from the ttbar decays matched to jets.</p> <p><strong>Dataset format</strong></p> <p>The dataset is in h5 format and the key 'delphes' has the following numpy arrays:</p> <pre><code>jets (16), jets_indices (16), matchability, nbjets, njets, partons (10) </code></pre> <p>Jets structured numpy array per event:</p> <ul> <li> <pre><code>(pt, eta, phi, energy, is_tagged)</code></pre> </li> </ul> <p>Jets_indices:</p> <ul> <li>Integer corresponding to the parton the jet is matched to</li> <li>From 0 to 5: b1 W1j1 W1j2 b2 W2j1 W2j2 (1= from top, 2=from antitop)</li> <li>-1 indicates not matched to a parton</li> <li>Properties of matched partons can be obtained from the partons array</li> </ul> <p>matchability:</p> <ul> <li>Which partons are matched to jets in event</li> <li>Binary representation with bits corresponding to each parton (length 6) 0b111111</li> <li>From left to right: b1 W1j1 W1j2 b2 W2j1 W2j2</li> <li>0b111000 (56) is one top fully matched, 0b000111 (7) is the other top fully matched, 0b111111 (63) is both tops fully matched</li> </ul> <p>njets, nbjets:</p> <ul> <li>How many jets/bjets in event</li> </ul> <p>partons:</p> <ul> <li>List of truth particles from ttbar decay: tops, Ws, quarks, ordered by top quark and its decays followed by anti-top and its decays</li> <li> <pre><code>PDGID, pt, eta, phi, mass</code></pre> </li> </ul> <p> </p> <p> </p> <p> </p>
MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: Version 2 (Greenland Sample Products)
<p>We provide 21 sample products of MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: Version 2 in three test regions of Greenland Ice Sheet. The full archive of version 2 ITS_LIVE products (including image pair maps, data cubes and mosaics) from Sentinel-1 as well as other optical sensors (Landsat-4/5/6/7/8 and Sentinel-2) can be found at the ITS_LIVE project website: <a href="https://its-live.jpl.nasa.gov/">https://its-live.jpl.nasa.gov</a>.</p> <p><strong>Sensor</strong>: Sentinel-1A/B</p> <p><strong>Processor</strong>: <a href="https://github.com/isce-framework/isce2">ISCE</a>v2.4.1 (topsApp -> <a href="https://github.com/leiyangleon/Geogrid">Geogrid</a>v1.4.0 -> <a href="https://github.com/nasa-jpl/autoRIFT">autoRIFT</a>v1.4.0)</p> <p><strong>Project</strong>: NASA MEaSUREs project <a href="https://its-live.jpl.nasa.gov">ITS_LIVE</a></p> <p><strong>Region 1</strong> (69.13N, 50.88W; Jakobshavn Isbræ Glacier): 7 ascending image pairs</p> <p><strong>Region 2</strong> (77.61N, 42.79W; central north of interior Greenland): 3 ascending image pairs</p> <p><strong>Region 3</strong> (72.48N, 35.87W; central south of interior Greenland): 10 descending image pairs and 1 ascending image pair</p> <p>This serves as a supplementary dataset for the companion journal article submitted to Earth System Science Data (to appear).</p> <p> </p> <p><strong>Acknowledgement</strong>: This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project (<a href="https://its-live.jpl.nasa.gov/">https://its-live.jpl.nasa.gov/</a>) and through Alex Gardner’s participation in the NASA NISAR Science Team.</p>
Top quark pair production at the LHC
<p><strong>R&D Datasets containing all-hadronic, semi-leptonic and di-leptonic top quark pair events at the LHC.</strong></p> <p>Used in the development of PIPPIN: Particles Into Particles with Permutation Invariant Network</p> <p> </p> <p>The datasets contain a total of 40M ttbar events in the all-hadronic, semi-leptonic and di-leptonic decay channels, with jets matched to the truth partons in the top quark decays.</p> <p> </p> <p><strong>Event generation</strong></p> <ul> <li>Centre of Mass energy: 13 TeV</li> <li>MC Generator: PYTHIA v8.307</li> <li>Parton Shower and Hadronisation: PYTHIA v8.307</li> <li>Detector response: Delphes v3.4.2 using ATLAS-like geometry</li> <li>Jets reconstructed with anti-kt algorithm, R = 0.4, using FastJet</li> </ul> <p><strong>Event selection and truth matching</strong></p> <ul> <li>All events are required to have between 2 and 16 reconstructed jets</li> <li>Jets are required to fall within |η| < 2.5 and to have a minimum pT > 25 GeV</li> <li>Leptons are required to fall within |η|<2.5 and to have a minimum pT > 15 GeV</li> <li>Partons are matched to jets using <span><span><span><span><span>Δ</span><span>R</span></span></span></span></span> matching, with <span><span><span><span><span>Δ</span><span>R </span><span>< </span><span>0.4</span></span></span></span></span></li> <li>Events with partons matched to multiple jets or jets to multiple partons are discarded</li> </ul> <p>The training dataset contains 37M events.<br>The validation dataset contains 0.8M events.<br>The testing dataset contains 2.4M events.</p> <p> </p> <p><strong>Dataset format</strong></p> <p>The dataset is in HDF5 format and the key 'delphes' contains the following numpy arrays:</p> <p>Truth information (parton-level):</p> <ul> <li><code>truth_leptons</code>, <code>truth_neutrinos</code>, <code>truth_quarks</code>: Truth level information of the final state partons <ul> <li><em>keys:</em> <code>PDGID</code>, <code>pt</code>, <code>eta</code>, <code>phi</code>, <code>mass</code></li> </ul> </li> <li><code>truth_particles</code>: Truth level information of the final state partons and the intermediate particles <ul> <li><em>keys:</em> <code>PDGID</code>, <code>pt</code>, <code>eta</code>, <code>phi</code>, <code>mass</code></li> </ul> </li> </ul> <p>Reconstructed information (detector-level):</p> <ul> <li><code>leptons</code>: The zero padded reconstructed leptons (0 to 2), ordered by decay channel <ul> <li><em>keys:</em> <code>pt</code>, <code>eta</code>, <code>phi</code>, <code>energy</code>, <code>charge</code>, <code>type</code></li> </ul> </li> <li><code>MET</code>: The missing transverse energy <ul> <li><em>keys:</em> <code>MET</code>, <code>phi</code></li> </ul> </li> <li><code>jets</code>: The zero padded reconstructed jets (2 to 16), ordered by pT <ul> <li><em>keys:</em> <code>pt</code>, <code>eta</code>, <code>phi</code>, <code>energy</code>, <code>is_tagged</code>, <code>is_tau</code></li> </ul> </li> </ul> <p>Miscellaneous information:</p> <ul> <li><code>decay_channel</code>: The decay channel of the event <ul> <li>0b00 for all-hadronic, 0b01 for semi-leptonic (from Top), 0b10 for semi-leptonic (from Anti-Top), 0b11 for di-leptonic</li> </ul> </li> <li><code>matchability</code>: Which partons are matched to a reconstructed object <ul> <li>Binary representation with bits corresponding to each parton (length 6) 0b111111</li> <li>From left to right: b1, q1<sub>W1</sub>, q2<sub>W1</sub>, b2, q1<sub>W2</sub>, q2<sub>W2 </sub>(b1/W1 = from Top, b2/W2 = from Anti-Top)</li> <li>0b111000 means Top fully matched, 0b000111 means Anti-Top fully matched, 0b111111 means both Tops fully matched, etc.</li> </ul> </li> <li><code>jet_indices</code>: Integer corresponding to the parton a jet is matched to <ul> <li>From 0 to 5: b1, q1<sub>W1</sub>, q2<sub>W1</sub>, b2, q1<sub>W2</sub>, q2<sub>W2 </sub>(b1/W1 = from Top, b2/W2 = from Anti-Top)</li> <li>-1 indicates not matched to a parton</li> </ul> </li> <li><code>nleptons</code>, <code>njets</code>, <code>nbjets</code>: How many leptons, jets, b-jets in the event</li> </ul>
Profiling results for top pair plus jets production with Pepper
<h2>Profiling results for top pair plus jets production with Pepper v1.1.1</h2> <h3>Contents</h3> <p>This includes data/output for the following GPU accelerated unweighted event generation runs:</p> <ul> <li>A run over a few seconds to produce pepper-internal timing results (`*timers.csv` files)</li> <li>The same run, but with `nvprof` (`*.nvprof` files)</li> <li>A run with a single event batch, with `ncu --import-source on --set full` (`*.ncu-rep` files)</li> </ul> <p>The simulated process is top pair production with n jets, with n = 0...4, at 13 TeV. The configuration files (`pepper.ini`) are included. Also the `pepper_cache` directories are included.</p> <p>All results are for the "main" pepper variant (which uses Kokkos to utilise the GPU) and for the "native" pepper variant (which uses CUDA directly).</p> <h3>Software stack and CPU/GPU hardware details</h3> <p>The software/hardware used for the profiling are as follows:</p> <ul> <li>GPU Driver: NVIDIA-SMI: 550.100, Driver Version: 550.100, CUDA Version: 12.4</li> <li>GPU: Tesla V100S-PCIE-32GB</li> <li>Cuda compilation tools: release 11.6, V11.6.124</li> <li>Kokkos 4.3.01</li> <li>gcc (GCC) 11.4.1 20231218 (Red Hat 11.4.1-3)</li> <li>Intel(R) Xeon(R) Silver 4214R CPU @ 2.40GHz</li> </ul> <p>Note that the event generation includes write-out of event files. The LHEH5 files are written to local SSD storage. The event files are not included in this dataset.</p> <h3>Additional run parameters</h3> <table> <tbody> <tr> <td>TTBar</td> <td>number of batches</td> <td>batch size</td> <td>rate (main variant)</td> <td>rate (native variant)</td> </tr> <tr> <td>+0j</td> <td>20</td> <td>1,179,648</td> <td>1.4e10</td> <td>2.0e10</td> </tr> <tr> <td>+1j</td> <td>20</td> <td>1,179,648</td> <td>1.5e10</td> <td>2.4e10</td> </tr> <tr> <td>+2j</td> <td>20</td> <td>1,179,648 * 2</td> <td>1.3e10</td> <td>2.7e10</td> </tr> <tr> <td>+3j</td> <td>20</td> <td>1,179,648 / 2</td> <td>6.4e9</td> <td>1.4e10</td> </tr> <tr> <td>+4j</td> <td>20</td> <td>1,179,648</td> <td>2.2e9</td> <td>2.2e9</td> </tr> </tbody> </table> <p>The number of batches has been chosen such that the most important sub processes are samples and such that the overall runtime is at least a few seconds. The batch size has been chosen by scanning over factors of two and picking the best-performing batch size with the native variant. The event rate is the number given in the Pepper output. It does not include the closing time of the generated HDF5 file, which can be significant for the two lowest multiplicities. This can be checked by inspecting the corresponding relative and absolute timing results in the `*timing.csv` files included in the dataset.</p>
Sample version 2.0 ITS_LIVE Sentinel-1 image pair product of ice velocity in Greenland
<p>21 samples of version 2.0 ITS_LIVE Sentinel-1 image pair product of ice velocity in three test regions of Greenland Ice Sheet</p> <p>Sensor: Sentinel-1A/B</p> <p>Processor: <a href="https://github.com/isce-framework/isce2">ISCE</a> v2.4.1 (topsApp -> <a href="https://github.com/leiyangleon/Geogrid">Geogrid</a> v1.4.0 -> <a href="https://github.com/nasa-jpl/autoRIFT">autoRIFT</a> v1.4.0)</p> <p>Project: NASA MEaSUREs project <a href="https://its-live.jpl.nasa.gov">ITS_LIVE</a></p> <p>Region 1 (69.13N, 50.88W; Jakobshavn Isbræ Glacier): 7 ascending image pairs</p> <p>Region 2 (77.61N, 42.79W; central north of interior Greenland): 3 ascending image pairs</p> <p>Region 3 (72.48N, 35.87W; central south of interior Greenland): 10 descending image pairs and 1 ascending image pair</p> <p>This serves as a supplementary dataset for the companion journal article submitted to Earth System Science Data (to appear soon).</p> <p> </p> <p>Acknowledgement:</p> <p>This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project (<a href="https://its-live.jpl.nasa.gov/">https://its-live.jpl.nasa.gov/</a>) and through Alex Gardner’s participation in the NASA NISAR Science Team</p>
New Physics Mining at the Large Hadron Collider: top pair production
<p><span class="math-tex">\(t \bar t\)</span> background events reconstructed by inclusive single-muon selection.</p> <p>Events are represented as an array of physics-motivated high-level features.</p> <p>Details are given in https://arxiv.org/abs/1811.10276</p>
Novel production pathways for the 64Cu / 67Cu theranostic pair through natZn(n, x) reactions
<p>This repository contains all raw gamma-ray spectra analyzed for the present manuscript, as well as calibration spectra. Further details and analysis code are available on reasonable request. </p> <p> </p> <p>The nuclear decay properties of the 64,67Cu radionuclides are favorable for clinical applications, with 64Cu currently being employed for PET imaging. The combined use of 64Cu with 67Cu as a theranostic pair may enable highly personalized therapeutic treatment, with real-time monitoring of dose delivery. In this study, the natZn(n,x) reactions have been investigated as novel production pathways for the 64,67Cu isotopes. The experiment was performed at the Lawrence Berkeley National Laboratory’s 88-Inch Cyclotron, producing fast neutrons through the deuteron breakup process using deuteron beams of 16 MeV and 33 MeV. This study reports spectrum-averaged cross sections for the 64,67Cu isotopes, as well as for 20 additional reaction products from neutron irradiation of natural zinc, zirconium, indium, yttrium and aluminum, more than half of which are measured for the first time. The well-characterized monitor reactions of 89Y(n,2n)88Y, 27Al(n,x)24Na, and natZr(n,x)89Zr were employed to determine the neutron fluence, using the recommendations from the IRDFF-II dosimetry library, and all activities were measured through γ-ray spectroscopy using a high-purity germanium detector. The results are compared to previous experiments from the EXFOR and TENDL-2019 databases, and calculations using ALICE-2017, CoH-3.5.3, EMPIRE-3.2.3, and TALYS-1.9. This work shows that natZn(n,x)64,67Cu is a viable pathway for producing these isotopes, and offers a potential ”tunable” ratio of 64Cu:67Cu for various applications.</p>
Fig. 8. Ochrathinols A in Ochrathinols A and B, two pairs of sulfur-containing racemates from an Antarctic fungus Aspergillus ochraceopetaliformis SCSIO 05702 inhibit LPS-induced pro-inflammatory cytokines and NO production
Fig. 8. Ochrathinols A (±)-1 compensated the NAD+/NADH ratio induced by LPS. Cells were exposed to 0.1 μg/mL LPS and co-treated with compounds of (±)-1 (10 μM) for 24 h. Intracellular NAD+/NADH ratios were determined by NAD+/NADH assay kit. Data are shown as mean ± SD (n = 3). *P <0.05, ****P <0.001 vs. LPS group, n = 3. P value was assessed by two-tailed Student's t-test.
Fig. 7 in Ochrathinols A and B, two pairs of sulfur-containing racemates from an Antarctic fungus Aspergillus ochraceopetaliformis SCSIO 05702 inhibit LPS-induced pro-inflammatory cytokines and NO production
Fig. 7. Anti-inflammation activity of ochrathinols A and B ((±)-1, (±)-2). Cells were exposed to 0.1 μg/mL LPS and co-treated with compounds of (+)-1, ()-1, (±)-1, (+)-2, ()-2, (±)-2 (10 μM) for 24 h, respectively. (A) (±)-1 reduced the release of LPS-induced IL-6, TNF-α, and MCP-1 in culture medium, n = 3. (B) qPCR analysis of pro-inflammatory cytokines genes (IL-1β, IL-6, TNF-α, and MCP-1) normalized by β-actin, n = 3. All data are presented as the mean ± SD of three independent experiments. ns, P> 0.05, *P <0.05, **P <0.01, ***P <0.005, ****P <0.001 vs. LPS group; #P <0.05, ##P <0.01, ###P <0.005, ####P <0.001 vs. control group, n = 3. P value was assessed by two-tailed Student's t-test.
Scheme 1 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Scheme 1 Proposal of the reaction pathway between valsartan and BPB with formation Valsartan-Bromphenol blue complex.
Figure 7 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 7 Absolute values ∆ A of the difference in the absorption of valsartan with MR in different solvents with the absorption of MR in different solvents.
Scheme 2 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Scheme 2 Proposal of the reaction pathway between valsartan and MR with formation Valsartan-Methyl red ion pair associates.
Figure 5 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 5 Absolute values ∆ A of the difference in the absorption of valsartan with BPB in different solvents with the absorption of BPB in different solvents.
Figure 15 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 15 Graph of the dependence of the adsorption of the reaction product of valsartan with MR on time.
Figure 14 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 14 Graph of the dependence of the adsorption of the reaction product of valsartan with BPB on time.
Figure 13 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 13 Absorption spectra of MR and valsartan with MR under conditions of studying the amount of added MR.
Figure 12 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 12 Absorption spectra of BPB and valsartan with BPB under conditions of studying the amount of added BPB.
Figure 9 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 9 Plot of Job's method for determination of molar ratio of the formed Valsartan-MR ion pair complex.
Figure 8 from: Peleshok K, Bondar B, Kryskiw L, Kucher T, Poliak O, Logoyda L (2021) Non-extractive spectrophotometric determination of valsartan in pure form and in pharmaceutical products by ion-pair complex formation with bromophenol blue and methyl red. Pharmacia 68(4): 851-858. https://doi.org/10.3897/pharmacia.68.e73559
Figure 8 Plot of Job's method for determination of molar ratio of the formed Valsartan-BPB ion pair complex.
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