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13 results for “GAMBIT”
Supplementary Data: Axion global fits with Peccei-Quinn symmetry breaking before inflation using GAMBIT
<p><strong>Description of Supplementary Data</strong></p> <p>This record contains the samples used to create the figures (excluding validation and prior dependence plots) and to derive most of the results in Hoof et al., <em>“Axion global fits with Peccei-Quinn symmetry breaking before inflation using GAMBIT”</em> (available on the <a href="https://arxiv.org/abs/1810.07192">arXiv</a>). Please contact the authors if you are interested in other samples, YAML files or plotting scripts.<br> <br> This record consists of</p> <ul> <li>21 <code>YAML</code> files (6 for <code>T-Walk</code>, 15 for <code>Diver</code>). Running <code>./gambit -f path/to/YAML/file.yaml</code> in the GAMBIT directory will start the scan. However, most users might want to adjust the output file name and directory as well as the settings for the samplers to their systems.</li> <li>21 <code>hdf5</code> files (6 for <code>T-Walk</code>, 15 for <code>Diver</code>). These files contain the actual samples and were compressed using the <code>tar</code> format.</li> <li>Two example <code>pip</code> files (<code>2_QCDAxion_10M1.pip</code> for <code>Diver</code> samples, <code>2_QCDAxion_3041.pip</code> for <code>T-Walk</code> samples) for producing plots from the corresponding <code>hdf5</code> files, using <a href="https://github.com/patscott/pippi"><code>pippi</code></a> and <code>functions.py</code>.</li> </ul> <p>The files follow the naming scheme <code>V_ModelName_[S][C][I][R][E]</code> plus one of the extensions <code>.yaml</code>, <code>.hdf5.tar.gz</code>, or <code>.pip</code>.</p> <ul> <li><code>V</code>: This internal version number can be ignored, but should be quoted when asking for help with the plotting scripts</li> <li><code>ModelName</code>: Corresponds to the axion models in the paper (<em>GeneralALP</em>, <em>QCDAxion</em>, <em>DFSZAxion_I</em>, <em>DFSZAxion_II</em>, <em>KSVZAxion</em>)</li> <li><code>S</code>: Scanner (<code>S=1</code>: <code>Diver</code>, <code>S=3</code>: <code>T-Walk</code>)</li> <li><code>C</code>: Switch to include (<code>C=1</code>) or exclude (<code>C=0</code>) the White Dwarf cooling hints</li> <li><code>I</code>: Setting for the initial misalignment angle <em>θ<sub>i</sub></em> (<code>I=4</code>: flat prior on <em>θ<sub>i</sub></em> with values in [-3.1415, 3.1415]). <code>I=M</code> is used to indicate that the file includes merged samples from other scans in addition to the corresponding <code>I=4</code> scan.</li> <li><code>R</code>: Setting for the DM relic density likelihood (<code>R=1</code>: upper limit, <code>R=2</code>: matching the DM density)</li> <li><code>E</code>: Extra digit for the anomaly ratio <em>E/N</em>; only for <em>KSVZAxion</em> models (<code>E=1</code>: 0, <code>E=2</code>, 2/3, <code>E=3</code>: 5/3, <code>E=4</code>: 8/3), <em>DFSZAxion-I</em> models (<code>E=1</code>: 8/3), <em>DFSZAxion-II</em> models (<code>E=2</code>: 2/3), or some <em>GeneralALP</em> files (<code>E=a</code>: “QCD-like setting” with <em>β</em> = 7.94, <em>T<sub>crit</sub></em> = 147 MeV; <code>E=b</code>: “Simple ALP-like setting” with <em>β</em> = 0, <em>T<sub>crit</sub></em> irrelevant)</li> </ul> <p>For convenience, we provide a mapping between the figures in the paper and the <code>hdf5</code> files:</p> <ul> <li>Fig. 1: none</li> <li>Figs 2 - 11: Validation plots</li> <li>Figs 12 + 13: 2_GeneralALP_10M2</li> <li>Fig. 14: 2_GeneralALP_10M2a, 2_GeneralALP_10M2b</li> <li>Fig. 15: 2_QCDAxion_10M1, 2_QCDAxion_10M2</li> <li>Fig. 16: 2_QCDAxion_3041, 2_QCDAxion_3042</li> <li>Figs 17 + 18: 2_QCDAxion_10M1, 2_QCDAxion_10M2, 2_QCDAxion_30M1, 2_QCDAxion_30M2</li> <li>Fig. 19: 3_KSVZAxion_10M11, 3_KSVZAxion_10M12, 3_KSVZAxion_10M13, 3_KSVZAxion_10M14, 3_DFSZAxion_I_10M11, 3_DFSZAxion_II_10M12</li> <li>Fig. 20: 2_QCDAxion_10M1, 3_KSVZAxion_10M11, 3_KSVZAxion_10M12, 3_KSVZAxion_10M13, 3_KSVZAxion_10M14, 3_DFSZAxion_I_10M11, 3_DFSZAxion_II_10M12</li> <li>Fig. 21: 2_QCDAxion_11M1, 2_QCDAxion_11M2</li> <li>Fig. 22: 2_QCDAxion_3141, 2_QCDAxion_3142</li> <li>Figs 23 + 24: 2_QCDAxion_3041, 2_QCDAxion_3042, 2_QCDAxion_3141, 2_QCDAxion_3142</li> <li>Fig. 25: 2_QCDAxion_3141, 2_QCDAxion_3142</li> <li>Fig. 26: 2_QCDAxion_11M1, 3_DFSZAxion_I_11M11, 3_DFSZAxion_II_11M12</li> <li>Fig. 27: 2_QCDAxion_3141, 3_DFSZAxion_I_31411, 3_DFSZAxion_II_31412</li> <li>Fig. 28: Validation plot</li> <li>Fig. 29: Prior dependence plot</li> </ul> <p>A few caveats to keep in mind:</p> <ul> <li>The YAML files are designed to work with <code>GAMBIT 1.3.1</code>, and the pip files are tested with <code>pippi 2.1</code>, commit 1a08644. They may or may not work with later versions of either software (these working versions/commits can always be obtained via the <code>git</code> history).</li> <li>The <code>pip</code> files will produce an approximately complete, but very basic version of plots in the paper. Re-creating all the plots in the paper requires various manual, undocumented interventions such as additions, deletions and combination of the plotting scripts created by <code>pippi</code>. Users wishing to reproduce the more advanced plots in the paper should contact the authors for tips, scripts, or experiment for themselves.</li> </ul>
Supplementary Data: A global fit of the MSSM with GAMBIT (arXiv:1705.07917)
<p><strong>Supplementary Data</strong></p> <p><em>A global fit of the MSSM with GAMBIT </em><br> <em>arXiv:1705.07917 </em></p> <p>The files in this record contain data for the MSSM7 model considered in the GAMBIT “Round 1” weak-scale SUSY paper.</p> <p>The files consist of</p> <ul> <li>A number of YAML files corresponding to different sets of sampling parameters and/or priors</li> <li>MSSM7.yaml, a YAML file used for postprocessing</li> <li>StandardModel_SLHA2_scan.yaml, a universal YAML fragment included from other YAML files</li> <li>StandardModel_SLHA2_postprocessing.yaml, a YAML fragment included from MSSM7.yaml</li> <li>A final hdf5 file, containing the combined results of all sampling runs</li> <li>An example pip file, for producing plots from the hdf5 file using pippi</li> <li>gambit_preamble.py, a collection of python functions used for in-line data processing in the pip file</li> <li>SLHA1 and SLHA2 files for the best-fit point in each subregion of the fit. These can found inside the tarball best_fits_SLHA.tar.gz.</li> </ul> <p>The different YAML files corresponding to different samplers and/or priors follow the naming scheme MSSM7_[scanner]_[prior]_[slice]_[special].yaml , where</p> <ul> <li>scanner = Diver, MN</li> <li>prior = log, flat</li> <li>slice = nM2, pM2, Afunnel, hZfunnel, sqcoann, slcoann (positive or negative M2, A/H funnel, h/Z funnel, squark co-annihilation, slepton co-annihilation)</li> <li>special = jDE, [blank] (used pure jDE, or used the default lambdajDE)</li> </ul> <p>A few caveats to keep in mind:</p> <ol> <li> <p>The final hdf5 results file included here was generated in the following way:</p> <ul> <li>carry out initial runs using YAML files following the naming scheme above</li> <li>combine the resulting hdf5 output files into a single file, using<br> gambit/Printers/scripts/combine_hdf5.py</li> <li>postprocess the samples to remove all points more than 5 sigma from the current best fit, using MSSM7_strip.yaml</li> <li>postprocess the samples to include a new likelihood term for LHC Run II searches, and to recompute the FlavBit likelihoods (these were buggy in a pre-release version of GAMBIT), using MSSM7.yaml .</li> </ul> </li> <li> <p>It is not necessary to repeat the steps listed in point 1 when running new scans; the LHC Run II likelihoods can be included in the original YAML file, so that no postprocessing step is required.</p> </li> <li> <p>The YAML files that we give here are updated compared to the ones that we used when generating the hdf5 file, in order to match the set of available options in the release version of GAMBIT 1.0.0. The included physics and numerics are however identical.</p> </li> <li> <p>The YAML files are designed to work with the tagged release of GAMBIT 1.0.0, and the pip file is tested with pippi 2.0, commit 2ab061a8. They may or may not work with later versions of either software (but you can of course always obtain the version that they do work with via the git history).</p> </li> <li> <p>The pip file is an example only. Users wishing to reproduce the more advanced plots in any of the GAMBIT papers should contact us for tips or scripts, or experiment for themselves. Many of these scripts are in multiple parts and require undocumented manual interventions and steps in order to implement various plot-specific customisations, so please don’t expect the same level of polish as for files provided here or in the GAMBIT repo.</p> </li> </ol>
Supplementary Data: Global fits of GUT-scale SUSY models with GAMBIT (arXiv:1705.07935)
<p>Supplementary Data</p> <p><em>Global fits of GUT-scale SUSY models with GAMBIT</em><br> <em>arXiv:1705.07935</em></p> <p>The files in this record contain data for the CMSSM, NUHM1 and NUHM2 models considered in the GAMBIT "Round 1" GUT-scale SUSY paper.</p> <p>For each model, there are</p> <ul> <li>A number of YAML files, each corresponding to a different set of sampling parameters and/or priors</li> <li>A set of YAML files used for postprocessing: CMSSM_intermediate.yaml, CMSSM.yaml, NUHM1.yaml and NUHM2.yaml</li> <li>A final hdf5 file, containing the combined results of all sampling runs</li> <li>An example pip file, for producing plots from the hdf5 file using pippi</li> <li>SLHA1 and SLHA2 files for the best-fit point in each subregion of the fit. These can be found inside the tarball best_fits_SLHA.tar.gz.</li> </ul> <p>The record also contains</p> <ul> <li>StandardModel_SLHA2_scan.yaml and StandardModel_SLHA2_postprocessing.yaml, two universal YAML fragments included from other yaml files</li> <li>gambit_preamble.py, a collection of python functions used for in-line data processing in the pip files</li> </ul> <p>The different YAML files corresponding to different samplers and/or priors follow the naming scheme [model]_[scanner]_[prior]_[slice]_[special].yaml, where</p> <ul> <li>model = CMSSM, NUHM1, NUHM2</li> <li>scanner = Diver, MN</li> <li>prior = log, flat</li> <li>slice = pmu, nmu (positive or negative mu)</li> <li>special = sqcoann, slcoann, [blank] (squark co-annihilation, slepton co-annihilation, or bulk)</li> </ul> <p>A few caveats to keep in mind:</p> <ol> <li> <p>For each model, the final hdf5 results file included here was generated in the following way:</p> <ul> <li>carry out initial runs using YAML files following the naming scheme above</li> <li>combine the resulting hdf5 output files into a single file, using gambit/Printers/scripts/combine_hdf5.py</li> <li>postprocess the samples to remove all points more than 5 sigma from the current best fit, using [model]_strip.yaml</li> <li>postprocess the samples to include a new likelihood term for LHC Run II searches, and to recompute the FlavBit likelihoods (these were buggy in a pre-release version of GAMBIT). For the CMSSM, this happened in two steps, due to persistent flavour bugs, using CMSSM_intermediate.yaml and CMSSM.yaml. For the NUHM1 and NUHM2, this was done in a single step each, using NUHM1.yaml and NUHM2.yaml.</li> </ul> </li> <li> <p>It is not necessary to repeat the steps listed in point 1 when running new scans; the LHC Run II likelihoods can be included in the original YAML file, so that no postprocessing step is required.</p> </li> <li> <p>The YAML files that we give here are updated compared to the ones that we used when generating the hdf5 file, in order to match the set of available options in the release version of GAMBIT 1.0.0. The included physics and numerics are however identical.</p> </li> <li> <p>The YAML files are designed to work with the tagged release of GAMBIT 1.0.0, and the pip files are tested with pippi 2.0, commit 2ab061a8. They may or may not work with later versions of either software (but you can of course always obtain the version that they do work with via the git history).</p> </li> <li> <p>The pip file for each model is an example only. Users wishing to reproduce the more advanced plots in any of the GAMBIT papers should contact us for tips or scripts, or experiment for themselves. Many of these scripts are in multiple parts and require undocumented manual interventions and steps in order to implement various plot-specific customisations, so please don't expect the same level of polish as for files provided here or in the GAMBIT repo.</p> </li> </ol>
Supplementary Data: Global fits if simplified models for dark matter with GAMBIT II. Vector dark matter with an s-channel vector mediator
<p>This record contains the YAML files, data files, and some of the plotting scripts for: "Global fits of simplified models for dark matter with GAMBIT II. Vector dark matter with an s-channel vector mediator".</p> <p>Samples have been created using GAMBIT and figures can be reproduced with pippi. Plotting scripts (*.pip) are designed to work with either the original version of pippi 2.1 or the forked unreleased version. The provided scripts do not reproduce all the figures in the paper exactly.</p> <p>To save storage space, all samples have been compressed using <code>tar</code>. To inflate each dataset after downloading run <code>tar -zxvf <samples>.hdf5.gz</code>.</p> <p>To facilitate uploading to Zenodo, several of the data files have been thinned to only include enough points to reproduce plots.</p>
Supplementary Data: A Frequentist Analysis of Three Right-Handed Neutrinos with GAMBIT
<p><strong>Supplementary Data</strong><br> <em> A Frequentist Analysis of 3 Right-Handed Neutrinos with GAMBIT.</em></p> <p>The files in this record contain data for the frequentist global fit of a model with three right-handed neutrinos using the <a href="http://gambit.hepforge.org">GAMBIT</a> tool.</p>
Supplementary Data: Global analyses of Higgs portal singlet dark matter models using GAMBIT
<p>The files in this record contain data for the effective Higgs portal dark matter models considered in the <a href="http://gambit.hepforge.org/">GAMBIT</a> "Higgs portal" paper.</p>
Supplementary Data: Global fits of vector-mediated s-channel simplified models for scalar and fermionic dark matter with GAMBIT
<p>This record contains the YAML files, data files, and some of the plotting scripts for: "Global fits of vector-mediated s-channel simplified models for scalar and fermionic dark matter with GAMBIT". The paper can be found at https://arxiv.org/abs/2209.13266.</p> <p>Samples have been created using GAMBIT and figures can be reproduced with pippi.</p>
Supplementary Data: CosmoBit: A GAMBIT module for computing cosmological observables and likelihoods (arXiv:2009.03286)
<p><strong>Supplementary Data</strong><br> <em>CosmoBit: A GAMBIT module for computing cosmological observables and likelihoods</em></p> <p>This record contains the samples and plotting routines used to create the figures and to derive most of the results in J.J. Renk et al., “CosmoBit: A GAMBIT module for computing cosmological observables and likelihoods” (available on the <a href="http://arxiv.org/abs/2009.03286">arXiv</a>)</p>
Supplementary Data: A model-independent analysis of b→sμ+μ− transitions with GAMBIT's FlavBit
<p>Supplementary Data</p> <p> A model-independent analysis of b→sμ+μ− transitions with GAMBIT's FlavBit</p> <p>The files in this record contain supplementary data including the samples and plotting scripts used for the results in Bhom. J et al. " A model-independent analysis of b→sμ+μ− transitions with GAMBIT's FlavBit." Samples have been created using <a href="http://gambit.hepforge.org/">GAMBIT</a> and figures can be reproduced with <a href="http://github.com/patscott/pippi">pippi</a>.</p> <p>This record contains:</p> <ul> <li>2 hdf5 files containing the samples produced for this article.</li> <li>2 pip files to create the figures from the samples, using pippi.</li> </ul> <p> </p>
GAMBIT Trial: Cisplatin Plus Irinotecan in the Treatment of Gallbladder or Biliary Tract Cancer
ClinicalTrials.gov study NCT01859728. IPD Sharing: Not stated. Countries: 1. Publications: 0.
GAMBIT Task With PTSD and Healthy Control Participants
ClinicalTrials.gov study NCT05313334. IPD Sharing: YES. Countries: 1. Publications: 0.
Combined dataset from GAMBIT MSSM9 scans on MareNostrum - PART B
<p>Samples collected on MareNostrum in the period November 2017 to February 2018.</p> <p>Note, this dataset exceeds the 50GB standard limit of Zenodo, so it has been split into two pieces using the linux command 'split':</p> <pre><code class="language-bash">split -b 49G MSSM9_all_trimmed.hdf5 Split_MSSM9_all_trimmed_</code></pre> <p>To recover this dataset, download "Split_MSSM9_all_trimmed_ab" from this deposit, as well as "Split_MSSM9_all_trimmed_aa" from the <a href="https://zenodo.org/deposit/1206173">PART A</a> deposit, place them in the same directory, and then run</p> <pre><code class="language-bash">cat Split_MSSM9_all_trimmed_* > Remerged_MSSM9.hdf5</code></pre> <p>You can verify the integrity of the recombined file using this checksum:</p> <pre><code>64284069a066756c83cca77a75db62d9</code></pre> <p>produced with md5sum:</p> <pre><code>md5sum Remerged_MSSM9.hdf5 64284069a066756c83cca77a75db62d9 Remerged_MSSM9.hdf5</code></pre> <p> </p>
Combined dataset from GAMBIT MSSM9 scans on MareNostrum - PART A
<p>Samples collected on MareNostrum in the period November 2017 to February 2018.</p> <p>Note, this dataset exceeds the 50GB standard limit of Zenodo, so it has been split into two pieces using the linux command 'split':</p> <pre><code class="language-bash">split -b 49G MSSM9_all_trimmed.hdf5 Split_MSSM9_all_trimmed_</code></pre> <p>To recover this dataset, download "Split_MSSM9_all_trimmed_aa" from this deposit, as well as "Split_MSSM9_all_trimmed_ab" from the <a href="https://zenodo.org/deposit/1206162">PART B</a> deposit, place them in the same directory, and then run</p> <pre><code class="language-bash">cat Split_MSSM9_all_trimmed_* > Remerged_MSSM9.hdf5</code></pre> <p>You can verify the integrity of the recombined file using this checksum:</p> <pre><code>64284069a066756c83cca77a75db62d9</code></pre> <p>produced with md5sum:</p> <pre><code>md5sum Remerged_MSSM9.hdf5 64284069a066756c83cca77a75db62d9 Remerged_MSSM9.hdf5</code></pre>
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