Simulated datasets for detector and particle flow reconstruction: CLIC detector, hit-based data, machine learning format

<p>Derived from https://zenodo.org/record/8260741, prepared in a machine-learning friendly TFDS format, ready to be used with https://zenodo.org/record/8397954.</p> <ul> <li>clic_edm_ttbar_hits_pf10k.tar: ee -&gt; ttbar, center of mass energy at 380 GeV, 10k events</li> <li>clic_edm_qq_hits_pf10k.tar: ee -&gt; Z* -&gt; qqbar, center of mass energy at 380 GeV, 10k events</li> </ul> <p><strong>Contents</strong></p> <p>Each .tar file contains the dataset in the <a href="https://github.com/tensorflow/datasets">tensorflow-datasets</a> (minimum version v4.9.1), <a href="https://github.com/google/array_record">array_record</a> format.</p> <p><strong>Dataset semantics</strong></p> <p>Each dataset consists of events that can be iterated over using the tensorflow-datasets library in either tensorflow or pytorch. Each event has the following information available:</p> <ul> <li>X: the reconstruction input features, i.e. tracks and calorimeter hits</li> <li>ygen: the ground truth particles with the features [&quot;PDG&quot;, &quot;charge&quot;, &quot;pt&quot;, &quot;eta&quot;, &quot;sin_phi&quot;, &quot;cos_phi&quot;, &quot;energy&quot;, &quot;jet_idx&quot;], with &quot;jet_idx&quot; corresponding to the gen-jet assignment of this particle</li> <li>ycand: the baseline Pandora PF particles with the features [&quot;PDG&quot;, &quot;charge&quot;, &quot;pt&quot;, &quot;eta&quot;, &quot;sin_phi&quot;, &quot;cos_phi&quot;, &quot;energy&quot;, &quot;jet_idx&quot;], with &quot;jet_idx&quot; corresponding to the gen-jet assignment of this particle</li> </ul> <p>The full semantics, including the list of features for X, are available at https://github.com/jpata/particleflow/blob/v1.6/mlpf/heptfds/clic_pf_edm4hep_hits/utils_edm.py.</p>