Muon Shield Optimization for the SHiP experiment (2024 and onward)

Warning: The repository is still in very initial phases of development and can change really quickly.

Envrionment

For non-GUI access (such as on servers), download simcontainer2.sif from the following location:

Containers

If you are using physik cluster, run the singularity container via the following commands:

cd /disk/lhcb_data/sqasim/images
. /disk/lhcb/scripts/lhcb_setup.sh
export SINGULARITY_TMPDIR=/disk/users/`whoami`/temp
export TMPDIR=/disk/users/`whoami`/tmp
singularity shell --nv -B /cvmfs -B /disk/users/`whoami` -B /run/user/`id -u` -B /home/hep/`whoami` simcontainer2.sif

For other clusters, modify the commands accordingly. You should include every directory you need access to from within the container with -B option.

Running on the MacBook is also easy, the default binary release from Geant4 works fine. And the rest of the packages can be installed simply via pip3.

Then, clone the repository (SSH / HTTPS):

git clone [email protected]:shahrukhqasim/MuonsAndMatter.git

or

git clone https://github.com/shahrukhqasim/MuonsAndMatter.git

cd MuonsAndMatter
git submodule update --init --remote --recursive
source env.sh

The following python script will give you the cmake command that you can use:

python3 chore/find_cmake_command.py

If you are running on a MacBook with a custom Geant4 installation:

python3 chore/find_cmake_command.py -g /path/to/Geant4-XX.X.X

For me, it gave:

Using python: /usr/bin/python3
pybind11 found in: /home/hep/sqasim/.local/lib/python3.10/site-packages/pybind11/share/cmake/pybind11
The following cmake command can be used:
cmake -Dpybind11_DIR=/home/hep/sqasim/.local/lib/python3.10/site-packages/pybind11/share/cmake/pybind11 -DPython_EXECUTABLE=/usr/bin/python3 the/path

Take node of the cmake command and run the following commands as per your username:

cd cpp/
mkdir build
cd build
cmake -Dpybind11_DIR=/home/hep/sqasim/.local/lib/python3.10/site-packages/pybind11/share/cmake/pybind11 -DPython_EXECUTABLE=/usr/bin/python3 ..
make -j
cd ../..

Data

To start with, a collection of enriched data consisting of ~0.5M samples can be downloaded from the following location:

Data

You should create a folder called data and put the pickle file there to be able to run the following two commands.

Running visually

python3 python/bin/run_full_detector_visually.py

Running multi-core

python3 python/bin/run_full_detector_multi_core_2.py --cores 45