# 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, and the intensity-based test for a
centred lattice. 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); 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).

**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).