Acknowledge pyAMReX
===================

Please acknowledge the role that pyAMReX played in your research.


In Publications
***************

If a project using pyAMReX leads to a scientific publication, please consider citing it.
This helps to keep in touch with the community, shows its use and supports the project.

Huebl A, Ananthan S, Grote D P, Sandberg R T, Zoni E, Jambunathan R, Lehe R, Myers A, Zhang W.
**pyAMReX: GPU-Enabled, Zero-Copy AMReX Python Bindings including AI/ML**.
*software*, 2023. `DOI:10.5281/zenodo.8408733 <https://doi.org/10.5281/zenodo.8408733>`__
`github.com/AMReX-Codes/pyamrex <https://github.com/AMReX-Codes/pyamrex>`__

.. code-block:: bibtex

   @misc{pyAMReX,
     author       = {Huebl, Axel and
                     Ananthan, Shreyas and
                     Grote, David P. and
                     Sandberg, Ryan T. and
                     Zoni, Edoardo and
                     Jambunathan, Revathi and
                     Lehe, Remi and
                     Myers, Andrew and
                     Zhang, Weiqun},
     title        = {{pyAMReX: GPU-Enabled, Zero-Copy AMReX Python Bindings including AI/ML}},
     year         = 2023,
     publisher    = {Zenodo},
     doi          = {10.5281/zenodo.8408733},
     url          = {https://github.com/AMReX-Codes/pyamrex},
     howpublished = {https://github.com/AMReX-Codes/pyamrex}
   }

You can also add an acknowledgement, e.g.,

.. code-block:: latex

   This research used the open-source code pyAMReX~\cite{pyAMReX}.
   We acknowledge all AMReX contributors.


Further pyAMReX References
**************************

- Myers A, Zhang W, Almgren A, Antoun T, Bell J, Huebl A, Sinn A.
  **AMReX and pyAMReX: Looking Beyond ECP**.
  *submitted for review*, 2024.
  `arXiv:2403.12179 <https://arxiv.org/abs/2403.12179>`__

Works using pyAMReX:

- Sandberg R T, Lehe R, Mitchell C E, Garten M, Myers A, Qiang J, Vay J-L and Huebl A.
  **Synthesizing Particle-in-Cell Simulations Through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines**.
  Proc. of Platform for Advanced Scientific Computing (PASC'24), *in print*, 2024.
  `arXiv:2402.17248 <http://arxiv.org/abs/2402.17248>`__

- Huebl A et al.,
  **Exascale and ML Models for Accelerator Simulations**.
  presentation at the 6th European Advanced Accelerator Concepts workshop (EAAC23), Isola d'Elba, Italy, Sep 17 – 23, 2023.
  `DOI:10.5281/zenodo.8362549 <https://doi.org/10.5281/zenodo.8362549>`__

- Sandberg R T, Lehe R, Mitchell C E, Garten M, Qiang J, Vay J-L and Huebl A.
  **Hybrid Beamline Element ML-Training for Surrogates in the ImpactX Beam-Dynamics Code**.
  14th International Particle Accelerator Conference (IPAC'23), WEPA101, *in print*, 2023.
  `preprint <https://www.ipac23.org/preproc/pdf/WEPA101.pdf>`__,
  `DOI:10.18429/JACoW-IPAC-23-WEPA101 <https://doi.org/10.18429/JACoW-IPAC-23-WEPA101>`__

- Huebl A, Lehe R, Mitchell C E, Qiang J, Ryne R D, Sandberg R T, Vay JL.
  **Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale**.
  2022 North American Particle Accelerator Conference (NAPAC'22), TUYE2, pp. 302-306, 2022.
  `arXiv:2208.02382 <https://arxiv.org/abs/2208.02382>`__,
  `DOI:10.18429/JACoW-NAPAC2022-TUYE2 <https://doi.org/10.18429/JACoW-NAPAC2022-TUYE2>`__