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Limitations

Although these data are all intended for use in scientific research, they are not without limitations. It is important to keep in mind the limitations of these datasets when using them in order to avoid false-positive results or dead ends. Although some of the most important limitations are documented here, if you have any questions about whether a particular analysis is possible please feel free to contact us. In case the analysis is not possible with the available public data, you are also welcome to consider a short term association with ATLAS in order to perform the analysis like a member of the collaboration would.

Data format limitations​

The HION14 heavy ion collision data format released for research use does not contain all physics objects (like jets or electrons), and it does not contain all calorimeter objects or particle flow objects. As a result, some analyses cannot be performed:

  • Analyses requiring detailed calorimeter information (e.g. calorimeter-based energy flow analyses)
  • Analyses requiring jets in any way (e.g. studies of jet suppression or jet cross-sections)
  • Analyses examining lepton universality (e.g. Z-boson decays to electrons and muons)

The HION14 data format is constructed to support "standard" track-based analyses commonly done with minimum bias datasets. This also implies that analyses requiring non-standard configurations of specific tools may be difficult or impossible. For example:

  • Measurements and searches with non-standard physics object definitions or reconstruction (e.g. customized heavy-flavor hadron tagging, modified photon reconstruction) are not possible
  • Measurements using information from the forward detectors in ATLAS are not currently supported (e.g. some diffractive physics measurements using information from the zero-degree calorimeter)

Data sample limitations​

In all cases it is important to respect a good runs list, which removes detector data quality issues from the data. In some rare cases, careful checks might reveal additional data quality issues. The most straightforward way to look for these is to check for the distribution of the events of interest in time (or across data taking runs). Physics should generally be uniform in time; detector issues are unlikely to be.

Only one Monte Carlo simulation data set has been released, modeling basic minimum bias physics expected in the detector. This should be sufficient for most general studies that require, for example, establishing track efficiency. However, for many high-momentum or high-mass processes (e.g. jets, Z-boson or J/Psi production) bespoke samples might be required. Care should be taken when extrapolating from the provided simulation sample to unmodeled physics processes.

In principle it is possible to produce your own samples. In practice, this is extremely complicated and strongly discouraged. The collaboration has significant infrastructure in order to produce samples that, for example, match the data-taking conditions and pileup profile of the data period being modeled. Getting these sorts of things right without significant help from a collaboration member or access to internal resources generally requires major computing resources and prohibitive time investment.

In case there are specific samples that would be beneficial to your analysis, you are welcome to request their release.