Jupyter At US ATLAS AFs

One of the services available at the US ATLAS analysis facilities is the Jupyter Lab enviroment. Some of the Jupyter kernels available there includes:

1. python2 with pyroot and uproot, some allows users to load an ATLAS analysis releases in order to access xAODs.
2. python3 with pyroot and uproot.
3. python3 with ML packages such as Tensorflow and Keras, with support of Nvidia GPUs.
4. Terminal console for simple interactive use, e.g. file managements.

Use the following links to access the Jupyter environment at the AFs, or access site specific documents on Jupyter.

• BNL JupyterLab and documents.
• SLAC JupyterLab and documents.
  • SLAC is migrating to a new computing facility SDF. As a result, we recently made some change to the SLAC JupyterLab portal. If you haven’t read and prepare yourself for “SLAC ID”, please refer to “SDF: New SLAC …” to estiblish your “SLAC ID”, then ssh sdf-login01.slac.stanford.edu for the first time.
  • The SLAC JupyterLab link above will change in the near future as the migration continue. When that happens, we will update the above link.
  • When asked to choose an identity provider, please choose “SLAC National Accelerator Laboratory” and then use your “SLAC ID” to login.

Examples of using Jupyter to analyze xAODs

• How to get information about an xAOD in python
• Read xAODs using PyROOT
• Info about uproot and xAOD