Dear participants,
 
We are writing to you in particular about the dark showers tutorial scheduled to take place at the LLP workshop, tomorrow, on the 27th May. The tutorial has been planned as a hands on session and in particular we hope that you will be able to generate some distributions and receive the joy of 'seeing' simulated dark showers at the LHC in this tutorial.
 
The detailed agenda is now posted at [1].
 
As the planned material comes with a few prerequisites, we have made a docker container so that we minimise the installation load. We will however still need jupyter notebook, scripy and numpy installed on your end as explained below.
 
In order to proceed smoothly during the tutorial, we therefore ask you to
 
0) Make sure that you have about 10GB of space on your machine. The docker has become rather heavy and thus we need some space for the tutorial to be successful.
1) install the docker facility/application on your machine from [2]
2) familiarise yourself with the usage of docker and in particular how to copy files in and out of docker containers to your local machine. This is needed as we will need to use a graphical interface e.g. to see the plotted histograms but we don't have a x11 forwarding installed on docker.
2a) You can follow a docker tutorial from here [3] for elementary docker usage and [4] shows how to copy files. Please note for macbooks local docker runs, the docker utility provides a very easy command line interface.
3) You can then obtain the docker image for the tutorial via
 
docker pull mgenest/dark-shower-tutorial
 
You can start an interactive shell inside docker via 
 
docker run -it mgenest/darkshower-tutorial sh
 
and check e.g. if Pythia examples work inside the docker.
 
To exit docker, type exit.
4) Please also have jupyter notebook along with scripy and numpy installed on your machine, this is particularly needed for understanding pythia card creation and SUEP setups.
5) We recommend not to use your own setups to avoid problems with correct setup of dependencies. In case you would still want to do that you would need pythia8 compiled with python containing matplotlib, pythia should also be linked against hepmc, boost libraries, and you would need a jupyter notebook installation irrespective of docker based or your own setup. If you use your own setup, we may not be able to provide live assistance.
 
Please let us know if you have any questions.
 
Best,
Suchita and Marie-Helene together with LLP workshop organisers.
 
[1] https://indico.cern.ch/e/LLP_May_2021
[2] https://docs.docker.com/get-docker/
[3] https://docker-curriculum.com/#hello-world
 
[4] https://docs.docker.com/engine/reference/commandline/cp/