Skip to content

General capabilities of the released 13 TeV Open Datasets

The publicly released 13 TeV Open Datasets can be used for educational purposes with different levels of task difficulty.

At a beginner level, one could visualise the content of the datasets and produce simple distributions. An intermediate-level task would consist of making histograms with collision data after some basic selection. Advanced-level tasks would allow for a deeper look into the ATLAS data, with possibilities of measuring real event properties and physical quantities.

A non-exhaustive list of possible tasks with the proposed datasets include:

  • comparisons of several distributions of event variables for simulated signal and background events;
  • finding variables that are able to separate signal from background (jet multiplicity, transverse momenta of jets and leptons, lepton isolation, b-tagging, missing transverse energy, angular distributions);
  • development and modification of cuts on these variables in order to enrich the signal-over-background separation;
  • optimisation of the signal-over-background ratio and estimation of the purity based on simulation only;
  • comparisons of the selection efficiency between data and simulation.

Advanced-level tasks might include:

  • derivation of production cross sections and masses of objects;
  • reconstruction of the objects (quarks or bosons) by assigning the detector physics objects (jets, leptons, missing energy) to the hypothetical decay trees;
  • estimation of the impact of other sources of systematic uncertainties (luminosity uncertainty, b-tagging efficiency, background modelling) by adding approximate and conservative values.
  • a test-bed for new data-analysis techniques, e.g. kinematic fitting procedures, multivariate discrimination of signal from background and other machine learning tasks.