:Author: Jérôme Kieffer
:Date: 19/11/2024
:Keywords: List of publications


Publications about pyFAI
========================

* *PyFAI, a versatile library for azimuthal regrouping*;
  J Kieffer and D Karkoulis;
  **Journal of Physics: Conference Series** (2013) 425 (20), pp202012
  Initial publication where the usage of GPU is envisaged to overcome
  the speed limitation of azimuthal integration.

* *PyFAI: a Python library for high performance azimuthal integration on GPU*;
  J Kieffer and J.P. Wright;
  **Powder Diffraction** (2013) 28 (S2), pp339-350;
  Introduces the concept of look-up table to register the pixel distribution.

* *PyFAI: a Python library for high performance azimuthal integration on GPU*;
   Jérôme Kieffer and Giannis Ashiotis;
   **PROC. OF THE 7th EUR. CONF. ON PYTHON IN SCIENCE** (EUROSCIPY 2014);
   Presents the usage of sparse matrices to store the look-up table.

* *The fast azimuthal integration Python library: pyFAI*;
  G. Ashiotis, A. Deschildre, Z. Nawaz, J. P. Wright, D. Karkoulis, F. E. Picca and J. Kieffer;
  **Journal of Applied Crystallography** (2015) 48 (2), 510-519;
  This publication provides a nice overview of the features introduced in version 0.11 and further developed in v0.12, v0.13 & v0.14.

* *New tools for calibrating diffraction setups*;
  J. Kieffer, V. Valls, N. Blanc and C. Hennig;
  **Journal of Synchrotron Radiation** (2020) 27 (2), 558-566;
  Describes the new integration scheme, the new user interface and the calibration of goniometers.

* *Application of signal separation to diffraction image compression and serial crystallography*;
  Jérôme Kieffer, Julien Orlans, Nicolas Coquelle, Samuel Debionne, Shibom Basu, Alejandro Homs, Gianluca Santonia and Daniele De Sanctis;
  **Journal of Applied Crystallography** (2025) 58, https://doi.org/10.1107/S1600576724011038.
  In depth explainaion of sigma-clipping background assessment and error models.

The latest paper should be the cited in publications using pyFAI.
There are already 1400 publications referring to pyFAI, some of them in the most
prestigious scientific journals (Nature, PNAS, ...) and
40 other `applications <https://github.com/silx-kit/pyFAI/network/dependents?dependent_type=PACKAGE>`_
using pyFAI as a library.
