Artificial Primary Vertexing Data
| Main Authors: | Das, Souvik, Wildridge, Andrew, Vaidya, Sachin B., Jung, Andreas |
|---|---|
| Format: | info dataset eJournal |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/3786899 |
Daftar Isi:
- This data set contains the positions of artificial vertex positions and the associated particle tracks within the Compact Muon Solenoid (CMS) particle detector located at the Large Hadron Collider (LHC). A Gaussian with a width of 35 mm is used to approximate the vertex position distribution. The z0 parameter of the artificial particle tracks is also sampled from a Gaussian centered around the sampled vertex position with a width determined from track resolutions reported by the CMS Collaboration in "Description and performance of track and primary-vertex reconstruction with the CMS tracker" (2014). The widths of the z0 Gaussian distribution are dependent on the momentum of the particle tracks, which are also sampled from the reported distribution in the aforementioned paper. The zipped data set contains 100 samples for a given number of primary vertices and particle tracks. Seven different configurations for a given number of primary vertices and particle tracks are included, giving a total number of 700 samples to analyze. Each sample is a JSON file containing the primary vertex location and the associated tracks with their positions and uncertainties. Below is an example code in Python to load the data set: inputFile = open(filename) d_vertextracks = json.load(inputFile) zT_i = [] zT_unc_i = [] for vertexTracks in d_vertextracks: primary_vertex = vertexTracks[0] tracks = vertexTracks[1] for i in tracks: zT_i.append(i[0]) zT_unc_i.append(i[1]) print(str(i[0])+" "+str(i[1]))