Docs: update

docs/CPU_DATA_ANALYSIS.md

@@ -1,6 +1,6 @@
 # CPU-side crystallographic data analysis (Jungfraujoch)
 
-This document describes the crystallographic algorithms implemented in Jungfraujoch for **CPU**- and **GPU**-side real‑time and near‑real‑time data analysis. It is written for crystallographers and follows established concepts from **XDS** and **CrystFEL**. Implementation details (GPU kernels, data structures, threading) are intentionally minimized in favour of the underlying crystallographic models and numerical procedures.
+This document describes the crystallographic algorithms implemented in Jungfraujoch for **CPU**- and **GPU**-side real‑time and near‑real‑time data analysis.
 
 **Scope.** The pipeline covered here comprises:
 
@@ -15,17 +15,16 @@ This document describes the crystallographic algorithms implemented in Jungfrauj
 9. scaling and merging,
 10. auxiliary statistics (Wilson plot, ⟨I/σ(I)⟩, French–Wilson).
 
-## References (to be cited)
+## References
 
-The methods are closely aligned with:
+The methods are inspired by solutions implemented in:
 
 - W. Kabsch, “XDS”, *Acta Cryst.* **D66** (2010), 125–132 and related XDS papers (rotation geometry, partiality, scaling concepts).
 - W. Kabsch, “Integration, scaling, space-group assignment and post-refinement”, *Acta Cryst.* **D66** (2010), 133–144 (mosaicity/partiality likelihood treatment; notation such as ζ and rotation factors).
-- T. A. White *et al.*, CrystFEL method papers (spot finding, three‑ring integration, serial/still diffraction processing concepts).
-
-(Exact bibliographic details and DOIs should be inserted in the Sphinx bibliography; the above is the intended citation set.)
-
----
+- T. A. White et al., CrystFEL method papers (spot finding, three‑ring integration, serial/still diffraction processing concepts).
+- J. Kieffer & J. P. Wright, "PyFAI: a Python library for high performance azimuthal integration on GPU", *Powder Diffraction* **28** (2013), S339-S350 (detector geometry definition, azimuthal integration)
+- H. Powell, "The Rossmann Fourier autoindexing algorithm in MOSFLM", *Acta Cryst.* **D55** (1999), 1690-1695 (FFT indexing)
+(list is not exhaustive)
 
 ## 1. Geometry, reciprocal-space mapping, and basic quantities
 
@@ -616,11 +615,3 @@ Numerical quadrature over a scaled intensity variable is used to compute posteri
 - **Rotation vs still modes** differ substantially in prediction and scaling because partiality is angle-driven in rotation data and excitation-error-driven in still data.
 
 ---
-
-## 14. Suggested citation wording (Acta Cryst. D style)
-
-When describing the methods in manuscripts, we recommend phrasing along the lines of:
-
-> “Real-time data reduction in Jungfraujoch follows established strategies from XDS (Kabsch, 2010a,b) and CrystFEL (White et al.), including strong-pixel spot finding, lattice determination by FFT-based periodicity detection, non-linear refinement of experimental geometry and crystal parameters, and summation integration using a three‑ring background estimator. For rotation datasets, predictions and scaling employ XDS-like quantities such as \(\zeta\) and error-function partiality.”
-
-(Replace with exact reference list entries as appropriate.)