

Welcome to the ALP Automated Computed Algorithm (ALPaca)!
ALPaca is an open-source Python library for the phenomenology of Axion-Like Particles (ALPs) with masses in the ranges of
ALPaca integrates the full analysis with an easy-to-use syntax:
- Matching of selected UV-complete models (DFSZ-like, KSVZ-like, flaxions, etc.) to the ALP-EFT.
- Numerical running and matching of the ALP-EFT coefficients down to the physical relevant scales, including ALP-$\chi!$ PT.
- Calulation of decay rates for processes involving ALPs:
- ALP production in rare meson decays
$M_1\to M_2 a$ , quarkonia decays$V\to \gamma a$ and non-resonant production$e^+e^- \to \gamma a$ , - ALP decays into photons, leptons and mesons,
- Processes mediated by on-shell ALPs in the Narrow Width Approximation,
- Leptonic and radiative meson decays, and meson mixing, with off-shell ALPs.
- ALP production in rare meson decays
- Calculation of ALP decay lengths and probability of decaying outside the detector, with a displaced vertex or in the prompt region.
-
$\chi^2$ statistical analysis, with fine-grained control of the observables and experimental measurements included. - Generation of publication-grade exclusion plots.
- Automatic management of the bibliographical references used in the analysis.
- Jorge Alda: Università degli Studi di Padova & INFN Sezione di Padova & CAPA Zaragoza.
- Marta Fuentes Zamoro: Universidad Autónoma de Madrid & IFT Madrid.
- Luca Merlo: Universidad Autónoma de Madrid & IFT Madrid.
- Xavier Ponce Díaz: University of Basel.
- Stefano Rigolin: Università degli Studi di Padova & INFN Sezione di Padova.
In this repositoy you can find examples, tutorials and applications of ALPaca.
ALPaca has been used in the following publications:
- J. Alda, M. Fuentes Zamoro, L. Merlo, X. Ponce Díaz, S. Rigolin: Comprehensive ALP searches in Meson Decays. arXiv:2507.19578
If you have used ALPaca in your publication and want to be featured in this list, please contact us.
ALPaca can be installed with pip
:
pip3 install alpaca-ALPs
It is strongly recommended to install ALPaca inside a virtual environment (venv), in order to avoid clashes with conflicting versions of the dependencies. In order to create a venv, execute the following command
python3 -m venv pathToVenv
where pathToVenv
is the location where the files of the venv will be stored. In order to activate the venv, for Linux or MacOS using bash
or zsh
source pathToVenv/bin/activate
For Windows using cmd.exe
C:\> pathToVenv\Scripts\Activate.bat
And for Windows using PowerShell
PS C:\> path_to_venv\Scripts\Activate.ps1
Once the venv is activated, ALPaca can be normally installed and used.
If you use ALPaca, please cite
@article{Alda:2025nsz,
author = "Alda, Jorge and Fuentes Zamoro, Marta and Merlo, Luca and Ponce D{\'\i}az, Xavier and Rigolin, Stefano",
title = "{ALPaca: The ALP Automatic Computing Algorithm}",
eprint = "2508.08354",
archivePrefix = "arXiv",
primaryClass = "hep-ph",
reportNumber = "IFT-UAM/CSIC-25-82",
month = "8",
year = "2025"
}
@software{alda_2025_16447036,
author = {Alda, Jorge and
Fuentes Zamoro, Marta and
Merlo, Luca and
Rigolin, Stefano and
Ponce Díaz, Xavier},
title = {ALPaca v1.0},
month = jul,
year = 2025,
publisher = {Zenodo},
version = {v1.0.0},
doi = {10.5281/zenodo.16447036},
url = {https://doi.org/10.5281/zenodo.16447036},
}
The ALPaca manual is available on arXiv.
You can also check the automatically-generated documentation.
If you encounter bugs or want to propose a new feature, you can contact us using Gihub issues.

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