Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/alphal00p/alphaloop

https://github.com/alphal00p/alphaloop

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: alphal00p
  • Language: Python
  • Default Branch: global_dampening
  • Size: 25.4 MB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 3 years ago · Last pushed 12 months ago
Metadata Files
Readme

README.md

alphaLoop

Accurate perturbative computation of cross-sections with Numerical Loop-Tree Duality.

1. Installation and requirements

Install MadGraph and alphaLoop:

sh wget https://launchpad.net/mg5amcnlo/2.0/2.7.x/+download/MG5aMC_3.0.2.beta.py3.tgz cd <MG_ROOT_PATH>/PLUGIN && git clone git@bitbucket.org:vahirschi/alphaloop.git

As many of our example generations use an internal model to alphaLoop, it is best to soft-link it in the models directory of MadGraph:

cd models ln -s ../PLUGIN/alphaloop/models/aL_sm .

Then

sh cd alphaloop sh deploy.sh

to install all dependencies.

Then

sh cd LTD python3 ltd_commons.py to create a default hyperparameters file.

Then sh cd .. cd rust_backend cargo build to compile the Rust backend. Optionally, build --release, for a slightly faster version.

To use the Python API of the Rust backend, compile with the Python API support using the following script: sh make_lib

Make sure to install the python dependencies pip install scipy progressbar2 networkx python-igraph wheel where pip needs to refer to the pip of at least Python 3.7. On clusters you may have to run

python3.7 -m pip install <PACKAGES>

2. Usage

You can run one of the example cards:

sh python3.7 ./bin/mg5_aMC --debug --mode=alphaloop PLUGIN/alphaloop/examples/epem_a_ddxg.aL

and integrate from the rust_backend folder with:

sh cargo run -- --cross_section_set ../../MG5_aMC_v2_7_2_py3/TEST_epem_a_ddxg/FORM/Rust_inputs/all_MG_supergraphs.yaml --debug 0 -c 16

You may have to include the following to your library path: sh export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:<ALPHALOOP>/libraries/fjcore:<ALPHALOOP>/libraries/ecos:<ALPHALOOP>/libraries/scs/out:<ALPHALOOP>/libraries/Cuba-4.2

3. Working plan:

  • Output a process and list all corresponding super-graphs from it.
  • Then build a library that can be linked to rust_backed in order to retrieve a fast implementation of the numerator of all contributing super graphs.
  • Run with the Rust backend

Owner

  • Name: alphaLoop
  • Login: alphal00p
  • Kind: organization
  • Email: valentin.hirschi@gmail.com
  • Location: Switzerland

Projects relating to Local Unitarity

GitHub Events

Total
  • Push event: 23
  • Create event: 2
Last Year
  • Push event: 23
  • Create event: 2