# Acknowledgements

Citation: F. Leonarski, M. Bruckner, C. Lopez-Cuenca, A. Mozzanica, H.-C. Stadler, Z. Matej, A. Castellane, B. Mesnet, J. Wojdyla, B. Schmitt and M. Wang "Jungfraujoch: hardware-accelerated data-acquisition system for kilohertz pixel-array X-ray detectors" (2023), J. Synchrotron Rad., 30, 227-234 [doi:10.1107/S1600577522010268](https://doi.org/10.1107/S1600577522010268).

The project is supported by :
* Innosuisse via Innovation Project "NextGenDCU high data rate acquisition system for X-ray detectors in structural biology applications" (101.535.1 IP-ENG; Apr 2023 - Sep 2025).
* ETH Domain via Open Research Data Contribute project (Jan - Dec 2023)
* AMD University Program with donation of licenses of Ethernet IP cores and Vivado software

Decoding bitshuffle+LZ4 images on the GPU, rather than decompressing them on the host and uploading
the result, follows Jon Wright (ESRF): "Experiences with GPU decompression for bitshuffle + LZ4
data", HDF5 User Group meeting (2021), and [bslz4decoders](https://github.com/jonwright/bslz4decoders).
The CUDA kernels in Jungfraujoch are its own, but the approach is his.

Spot extraction groups strong pixels into spots with the sparse connected-component labelling of the
ACTS traccc project: P. Gessinger, H. M. Gray, A. Krasznahorkay, C. Leggett, J. Niermann,
A. Salzburger, S. N. Swatman and B. Yeo, "traccc: GPU track reconstruction library for HEP
experiments" (2025), [arXiv:2505.22822](https://arxiv.org/abs/2505.22822);
[traccc](https://github.com/acts-project/traccc). The CPU spot extractor adapts its SparseCCL source,
and the CUDA spot extractor follows the design of its GPU counterpart - a backward-neighbour graph
over a sorted hit list, resolved by a parallel union-find. traccc is MPL-2.0; see
[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md).

This software uses Viridis, Magma and Inferno colormaps from Matplotlib under its BSD-compatible license

## Crystallographic methods adopted from other packages

The analysis pipeline reimplements methods first published, and in most cases first implemented, by
other crystallographic software. The code below is Jungfraujoch's own; the methods are theirs, and
are acknowledged here. Where a package's source was consulted this is said explicitly. None of these
packages is linked or vendored, with the single exception of GEMMI (see
[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md)).

**[XDS](https://xds.mr.mpg.de/)** — rotation geometry and notation, the reciprocal Lorentz and
partiality treatment, the maximum-likelihood mosaicity estimate, the `MINPK` criterion for rejecting
a reflection whose predicted profile is not cleanly its own, the intensity-based test for a
centred lattice, and the scaling correction surfaces indexed by image number and detector region. W. Kabsch, "XDS" (2010), Acta Cryst. D66, 125-132
[doi:10.1107/S0907444909047337](https://doi.org/10.1107/S0907444909047337); W. Kabsch, "Integration,
scaling, space-group assignment and post-refinement" (2010), Acta Cryst. D66, 133-144
[doi:10.1107/S0907444909047374](https://doi.org/10.1107/S0907444909047374).

**Profile fitting** with reweighted, de-biased variances is the Kabsch/Otwinowski iteration, from the
second XDS paper above and from Z. Otwinowski and W. Minor, "Processing of X-ray diffraction data
collected in oscillation mode" (1997), Methods Enzymol. 276, 307-326
[doi:10.1016/S0076-6879(97)76066-X](https://doi.org/10.1016/S0076-6879%2897%2976066-X).

**[DIALS](https://dials.github.io/)** — the resolution cutoff from the CC1/2 fall-off, per-observation
outlier rejection at merge, the scaling error model, and the treatment of a reflection whose
background is contaminated. Its published behaviour, and in places its source, settled several
choices here. G. Winter, D. G. Waterman, J. M. Parkhurst et al., "DIALS: implementation and
evaluation of a new integration package" (2018), Acta Cryst. D74, 85-97
[doi:10.1107/S2059798317017235](https://doi.org/10.1107/S2059798317017235); D. G. Waterman,
G. Winter, R. J. Gildea et al., "Diffraction-geometry refinement in the DIALS framework" (2016),
Acta Cryst. D72, 558-575 [doi:10.1107/S2059798316002187](https://doi.org/10.1107/S2059798316002187);
J. Beilsten-Edmands, G. Winter, R. Gildea et al., "Scaling diffraction data in the DIALS software
package: algorithms and new approaches for multi-crystal scaling" (2020), Acta Cryst. D76, 385-399
[doi:10.1107/S2059798320003198](https://doi.org/10.1107/S2059798320003198); J. M. Parkhurst,
G. Winter, D. G. Waterman et al., "Robust background modelling in DIALS" (2016), J. Appl. Cryst. 49,
1912-1921 [doi:10.1107/S1600576716013595](https://doi.org/10.1107/S1600576716013595).

**[POINTLESS](https://www.ccp4.ac.uk/)** (CCP4) — the space-group search. Stage A scores each
candidate rotation operator by the correlation of I(h) with I(Rh) on **resolution-normalised**
intensities (E²), as POINTLESS does — both arms of a symmetry pair sit at the same |s|, so on raw
intensities the resolution fall-off is variance shared between them and lifts a false operator's
correlation as much as a true one's; the screw-axis test scores a
predicted-absent class against the rest of its own axial row rather than against a global mean or a
fixed cut, and lets confidence fall away with the number of axial reflections instead of refusing
below a count. P. Evans, "Scaling and assessment of data quality" (2006), Acta Cryst. D62, 72-82
[doi:10.1107/S0907444905036693](https://doi.org/10.1107/S0907444905036693); P. R. Evans, "An
introduction to data reduction: space-group determination, scaling and intensity statistics" (2011),
Acta Cryst. D67, 282-292 [doi:10.1107/S090744491003982X](https://doi.org/10.1107/S090744491003982X);
P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061);
J. Agirre, M. Atanasova, H. Bagdonas et al., "The CCP4 suite: integrative software for macromolecular
crystallography" (2023), Acta Cryst. D79, 449-461
[doi:10.1107/S2059798323003595](https://doi.org/10.1107/S2059798323003595).

**[MOSFLM](https://www.mrc-lmb.cam.ac.uk/mosflm/)** — the Rossmann FFT autoindexing algorithm and
post-refinement practice, including which parameters are safe to refine per image and which must be
refined over a wedge. A. G. W. Leslie and H. R. Powell, "Processing diffraction data with MOSFLM"
(2007), in *Evolving Methods for Macromolecular Crystallography*, NATO Science Series II, vol. 245,
41-51 [doi:10.1007/978-1-4020-6316-9_4](https://doi.org/10.1007/978-1-4020-6316-9_4);
T. G. G. Battye, L. Kontogiannis, O. Johnson, H. R. Powell and A. G. W. Leslie, "iMOSFLM: a new
graphical interface for diffraction-image processing with MOSFLM" (2011), Acta Cryst. D67, 271-281
[doi:10.1107/S0907444910048675](https://doi.org/10.1107/S0907444910048675); H. R. Powell,
T. G. G. Battye, L. Kontogiannis, O. Johnson and A. G. W. Leslie, "Integrating macromolecular X-ray
diffraction data with the graphical user interface iMosflm" (2017), Nat. Protoc. 12, 1310-1325
[doi:10.1038/nprot.2017.037](https://doi.org/10.1038/nprot.2017.037).

**[CrystFEL](https://www.desy.de/~twhite/crystfel/)** — spot finding, the three-ring integration
region, the serial/stills processing model, and the per-frame indexing acceptance test
(`indexing_peak_check()` in `peaks.c`). T. A. White, R. A. Kirian, A. V. Martin, A. Aquila, K. Nass,
A. Barty and H. N. Chapman, "CrystFEL: a software suite for snapshot serial crystallography" (2012),
J. Appl. Cryst. 45, 335-341 [doi:10.1107/S0021889812002312](https://doi.org/10.1107/S0021889812002312).

**[GEMMI](https://github.com/project-gemmi/gemmi)** — symmetry operations, unit-cell and
structure-factor machinery, and MTZ / XDS_ASCII I/O. Vendored in `gemmi_gph/`, so it also carries a
licence obligation. M. Wojdyr, "GEMMI: A library for structural biology" (2022), J. Open Source
Softw. 7, 4200 [doi:10.21105/joss.04200](https://doi.org/10.21105/joss.04200).

**Hexagonal-ice ring positions** — the eleven measured ring $d$ spacings the ice-ring score, the
ice-ring flagging and the ice calibrant are all built on are taken from the measurements of, not
enumerated from a cell. D. W. Moreau, H. Atakisi and R. E. Thorne, "Ice in biomolecular
cryocrystallography" (2021), Acta Cryst. D77, 540-554
[doi:10.1107/S2059798321001170](https://doi.org/10.1107/S2059798321001170).

**Diffraction anisotropy** — the description of the overall fall-off by a single anisotropic
displacement tensor, its symmetry constraints, and the fact that only its deviatoric part is
determined (the isotropic part being degenerate with the overall scale) are Sheriff and Hendrickson's.
The estimator fits that tensor to the observed intensity distribution, taking sigma(I) into account,
in the sense of Popov and Bourenkov. The directional diffraction limits - <I/sigma(I)> in a cone about
each principal direction, and the reporting of the anisotropic deltaB as the range of the principal
components - follow AIMLESS. rugnux reports these; it corrects no intensity and removes no reflection
on a directional criterion. S. Sheriff and W. A. Hendrickson, "Description of overall anisotropy in
diffraction from macromolecular crystals" (1987), Acta Cryst. A43, 118-121
[doi:10.1107/S010876738709977X](https://doi.org/10.1107/S010876738709977X); A. N. Popov and
G. P. Bourenkov, "Choice of data-collection parameters based on statistic modelling" (2003), Acta
Cryst. D59, 1145-1153 [doi:10.1107/S0907444903008163](https://doi.org/10.1107/S0907444903008163);
P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061).

**Data-quality statistics** follow the established conventions rather than any one program: R_meas
and R_pim, CC1/2 and CC\*, and the reporting of I/sigma(I). K. Diederichs and P. A. Karplus, "Improved
R-factors for diffraction data analysis in macromolecular crystallography" (1997), Nat. Struct. Biol.
4, 269-275 [doi:10.1038/nsb0497-269](https://doi.org/10.1038/nsb0497-269); P. A. Karplus and
K. Diederichs, "Linking crystallographic model and data quality" (2012), Science 336, 1030-1033
[doi:10.1126/science.1218231](https://doi.org/10.1126/science.1218231); K. Diederichs and
P. A. Karplus, "Better models by discarding data?" (2013), Acta Cryst. D69, 1215-1222
[doi:10.1107/S0907444913001121](https://doi.org/10.1107/S0907444913001121).

**Uncertainty conventions** follow the IUCr Commission on Crystallographic Nomenclature:
D. Schwarzenbach, S. C. Abrahams, H. D. Flack et al., "Statistical descriptors in crystallography:
Report of the IUCr Subcommittee on Statistical Descriptors" (1989), Acta Cryst. A45, 63-75
[doi:10.1107/S0108767388009596](https://doi.org/10.1107/S0108767388009596); D. Schwarzenbach,
S. C. Abrahams, H. D. Flack, E. Prince and A. J. C. Wilson, "Statistical descriptors in
crystallography. II. Report of a Working Group on Expression of Uncertainty in Measurement" (1995),
Acta Cryst. A51, 565-569 [doi:10.1107/S0108767395002340](https://doi.org/10.1107/S0108767395002340).