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10
datasets available to search
ShareScore release 0.9.0
Dataset results
10 results for “collider physics”
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>
New Physics Mining at the Large Hadron Collider: W -> l nu
<p><span class="math-tex">\(W \to \ell \nu\)</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>
New Physics Mining at the Large Hadron Collider: QCD multijet production
<p>QCD multijet 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>
Supplementary Data: Simple, but not simplified: A new approach for optimising beyond-Standard Model physics searches at the Large Hadron Collider
<p><strong>Supplementary Data</strong></p> <p><em>Simple, but not simplified: A new approach for optimising beyond-Standard Model physics searches at the Large Hadron Collider</em></p> <p>This record contains the full dataset generated for the study "<em>Simple, but not simplified: A new approach for optimising beyond-Standard Model physics searches at the Large Hadron Collider</em>". It contains the following files:</p> <ul> <li>data_cross_sections_full_exact.csv - a CSV file with the soft breaking parameters M1, M2, mu and tanb, the neutralino/chargino masses, the cross sections for neutralino-neutralino, chargino-neutralino and chargino-chargino production at the LHC operating at a CM energy of 13 TeV, and the branching ratios of the unstable charginos/neutralinos. </li> <li>benchmark_points.zip - this zip file contains the SLHA files for the four benchmark points as shown in the paper, together with the prospino output for the cross section. </li> </ul> <p> </p>
New Physics Mining at the Large Hadron Collider: LQ -> b tau
<p><span class="math-tex">\(LQ \to b \tau\)</span> signal 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>
New Physics Mining at the Large Hadron Collider: A -> 4 leptons
<p><span class="math-tex">\(A \to 4\ell\)</span> signal 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>
New Physics Mining at the Large Hadron Collider: h^0 -> tau tau
<p><span class="math-tex">\(h^0 \to \tau^+ \tau^-\)</span> signal 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>
New Physics Mining at the Large Hadron Collider: Z -> l l
<p><span class="math-tex">\(Z \to \ell \ell\)</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>
New Physics Mining at the Large Hadron Collider: h+ -> tau nu
<p><span class="math-tex">\(h^\pm \to \tau^\pm \nu\)</span> signal 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>
PYTHIA6 Dataset: Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics
<p>Dataset corresponding to: https://inspirehep.net/literature/2164495</p> <p>The data set contains PYTHIA6 jets in ep collisions, with separate files for LO DIS and photoproduction samples. For further details about the data set, see https://inspirehep.net/literature/2164495. Examples of how to analyze the data set can be found at: https://github.com/jdmulligan/ml-eic-flavor.</p> <p>Please contact james.mulligan@berkeley.edu with any questions.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research 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.
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.
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.
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.
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.