# Documentation for the density mode of MadGraph
Work In Progress

= Density mode
== Authors
V. Durupt
== Short description
Automatic computation of density matrices and quantum information observables. 
This page contains the technical description of the Python library Density_functions.py used for analysis.

== How to compute density matrices
This module of MadGraph5 allows to compute density matrices automatically in a user-friendly way. After having generated your process
{{{
generate YOUR_PROCESS
output
launch
}}}

you will be able to chose the type of run. To compute density matrices one must chose
{{{
reweight = density
}}}

The user is then asked to edit the different cards needed for the run. The information for the density matrices computation is given in the reweight_card. Examples for different benchmark processes are given in https://arxiv.org/abs/2510.17730. At the end of the run, the density matrix for each event is written in the Les Houches Event (LHE) file.

==How to read the density matrices in the LHE file
The LHE file can be read with the parser lhe_parser.py available in MadGraph. An example of code that would parse the density matrix value for each event is:

{{{
import sys
sys.path.append('PATH TO MADGRAPH')
import madgraph.various.Density_functions as dens
import madgraph.various.lhe_parser as lhe_parser

lhe_path = os.path.join('PATH TO MADGRAPH', Data_Path)
for event in lhe_parser.EventFile(lhe_path):
    density = event.density
    square_density = dens.square_matrix(density)

}}}

With this code, for each event of the file, you read the value `density` which contains the independent coefficients of the density matrix. The utility function `square_matrix` allows to write it in the usual matrix form needed for further analysis.