leonarski_fandClaude Opus 5
6081b6bc43
Six methods the pages name or describe carried no citation: Padilla & Yeates (the L test), Steller, Bolotovsky & Rossmann (the projection/FFT autoindexing MOSFLM implements), TORO (what ffbidx implements), Krivy & Gruber and the ITA lattice-character table (the reduction and Bravais assignment), Cheetah's peakfinder8 (the per-ring background statistics of the adaptive finder) and Hennequin et al.'s SparseCCL (already credited to traccc, now also to its authors). Each gets its ACKNOWLEDGEMENT.md paragraph, a References entry in CPU_DATA_ANALYSIS.md, and a one-line credit at the algorithm. The Sheriff & Hendrickson / Popov & Bourenkov entry is re-scoped so each claim sits on the paper that supports it - P&B 2003 is titled, and credited for the sigma-aware anisotropy estimation its statistic modelling contains, not for the tensor and its constraints. All DOIs verified against the publishers; the SparseCCL DOI resolves to IEEE document 9049184 (IEEE blocks content scraping, so verified by the resolved document id plus two independent sources). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N
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# Acknowledgements
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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).
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The project is supported by :
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* 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).
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* ETH Domain via Open Research Data Contribute project (Jan - Dec 2023)
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* AMD University Program with donation of licenses of Ethernet IP cores and Vivado software
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Decoding bitshuffle+LZ4 images on the GPU, rather than decompressing them on the host and uploading
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the result, follows Jon Wright (ESRF): "Experiences with GPU decompression for bitshuffle + LZ4
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data", HDF5 User Group meeting (2021), and [bslz4decoders](https://github.com/jonwright/bslz4decoders).
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The CUDA kernels in Jungfraujoch are its own, but the approach is his.
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Spot extraction groups strong pixels into spots with the sparse connected-component labelling of the
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ACTS traccc project: P. Gessinger, H. M. Gray, A. Krasznahorkay, C. Leggett, J. Niermann,
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A. Salzburger, S. N. Swatman and B. Yeo, "traccc: GPU track reconstruction library for HEP
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experiments" (2025), [arXiv:2505.22822](https://arxiv.org/abs/2505.22822);
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[traccc](https://github.com/acts-project/traccc). The CPU spot extractor adapts its SparseCCL source,
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and the CUDA spot extractor follows the design of its GPU counterpart - a backward-neighbour graph
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over a sorted hit list, resolved by a parallel union-find. traccc is MPL-2.0; see
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[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md). The SparseCCL algorithm itself is A. Hennequin,
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B. Couturier, V. V. Gligorov and L. Lacassagne, "SparseCCL: Connected Components Labeling and
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Analysis for sparse images" (2019), DASIP 2019, 65-70
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[doi:10.1109/DASIP48288.2019.9049184](https://doi.org/10.1109/DASIP48288.2019.9049184).
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This software uses Viridis, Magma and Inferno colormaps from Matplotlib under its BSD-compatible license
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## Public diffraction data used for testing
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In addition to in-house datasets collected at SLS 2.0, Jungfraujoch is tested against public
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diffraction data collected on other people's beamlines, on detectors and in file formats we do not
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produce ourselves - most of it at other facilities, a few sets at the Swiss Light Source but not by
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this system. That data was collected and published by other people. Every dataset used, the DOI to
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cite for it, and the deposition it belongs to are listed in
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[EXTERNAL_TEST_DATA](EXTERNAL_TEST_DATA.md); we thank the depositors, and the repositories that make
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the data findable and citable.
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**[IRRMC](https://proteindiffraction.org/)**, the Integrated Resource for Reproducibility in
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Macromolecular Crystallography (Minor lab, University of Virginia), is the source of most of them.
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IRRMC releases its data under CC0 and asks that the DOI of the dataset be cited; those DOIs are in
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the table. M. Grabowski, K. M. Langner, M. Cymborowski, P. J. Porebski, P. Sroka, H. Zheng,
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D. R. Cooper, M. D. Zimmerman, M.-A. Elsliger, S. K. Burley and W. Minor, "A public database of
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macromolecular diffraction experiments" (2016), Acta Cryst. D72, 1181-1193
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[doi:10.1107/S2059798316014716](https://doi.org/10.1107/S2059798316014716); M. Grabowski,
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M. Cymborowski, P. J. Porebski, T. Osinski, I. G. Shabalin, D. R. Cooper and W. Minor, "The
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Integrated Resource for Reproducibility in Macromolecular Crystallography: Experiences of the first
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four years" (2019), Struct. Dyn. 6, 064301
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[doi:10.1063/1.5128672](https://doi.org/10.1063/1.5128672).
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**[SBGrid Data Bank](https://data.sbgrid.org/)** supplied nine of the datasets. P. A. Meyer,
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S. Socias, J. Key, E. Ransey, E. C. Tjon, A. Buschiazzo et al., "Data publication with the
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structural biology data grid supports live analysis" (2016), Nat. Commun. 7, 10882
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[doi:10.1038/ncomms10882](https://doi.org/10.1038/ncomms10882).
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**[Zenodo](https://zenodo.org/)** hosts eleven, deposited there directly by the groups that
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collected them. European Organization for Nuclear Research and OpenAIRE, "Zenodo" (2013), CERN
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[doi:10.25495/7GXK-RD71](https://doi.org/10.25495/7GXK-RD71). Three of those datasets were
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published as IUCrData Raw Data Letters; the letters are cited on the
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[EXTERNAL_TEST_DATA](EXTERNAL_TEST_DATA.md) page, beside the datasets they describe.
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The beamline, resolution, space group and unit cell quoted for each dataset are the values
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deposited with the corresponding PDB entry, read from the RCSB PDB data API. H. M. Berman,
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J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov and P. E. Bourne,
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"The Protein Data Bank" (2000), Nucleic Acids Res. 28, 235-242
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[doi:10.1093/nar/28.1.235](https://doi.org/10.1093/nar/28.1.235).
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## File formats read from a published specification
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**CBF / imgCIF** - the native miniCBF reader implements the `x-CBF_BYTE_OFFSET` compression scheme
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and reads the imgCIF `_axis` table (the laboratory directions of the image's fast and slow pixel
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directions, of the goniometer axes and of a 2theta arm) from the specification alone; no CBFlib or
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other CBF code is used, so there is no licence obligation, only this credit.
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H. J. Bernstein and A. P. Hammersley, "Specification of the Crystallographic Binary File
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(CBF/imgCIF)" (2006), International Tables for Crystallography Vol. G, 37-43
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[doi:10.1107/97809553602060000729](https://doi.org/10.1107/97809553602060000729);
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A. P. Hammersley, H. J. Bernstein and J. D. Westbrook, "Image dictionary (imgCIF)" (2006),
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International Tables for Crystallography Vol. G, 444-458
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[doi:10.1107/97809553602060000746](https://doi.org/10.1107/97809553602060000746).
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## Crystallographic methods adopted from other packages
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The analysis pipeline reimplements methods first published, and in most cases first implemented, by
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other crystallographic software. The code below is Jungfraujoch's own; the methods are theirs, and
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are acknowledged here. Where a package's source was consulted this is said explicitly. None of these
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packages is linked or vendored, with the single exception of GEMMI (see
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[THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md)).
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**[XDS](https://xds.mr.mpg.de/)** — rotation geometry and notation, the reciprocal Lorentz and
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partiality treatment, the maximum-likelihood mosaicity estimate, the `MINPK` criterion for rejecting
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a reflection whose predicted profile is not cleanly its own, the intensity-based test for a
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centred lattice, and the scaling correction surfaces indexed by image number and detector region. W. Kabsch, "XDS" (2010), Acta Cryst. D66, 125-132
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[doi:10.1107/S0907444909047337](https://doi.org/10.1107/S0907444909047337); W. Kabsch, "Integration,
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scaling, space-group assignment and post-refinement" (2010), Acta Cryst. D66, 133-144
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[doi:10.1107/S0907444909047374](https://doi.org/10.1107/S0907444909047374).
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**Profile fitting** with reweighted, de-biased variances is the Kabsch/Otwinowski iteration, from the
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second XDS paper above and from Z. Otwinowski and W. Minor, "Processing of X-ray diffraction data
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collected in oscillation mode" (1997), Methods Enzymol. 276, 307-326
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[doi:10.1016/S0076-6879(97)76066-X](https://doi.org/10.1016/S0076-6879%2897%2976066-X).
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**[DIALS](https://dials.github.io/)** — the resolution cutoff from the CC1/2 fall-off, per-observation
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outlier rejection at merge, the scaling error model, and the treatment of a reflection whose
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background is contaminated. Its published behaviour, and in places its source, settled several
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choices here. G. Winter, D. G. Waterman, J. M. Parkhurst et al., "DIALS: implementation and
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evaluation of a new integration package" (2018), Acta Cryst. D74, 85-97
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[doi:10.1107/S2059798317017235](https://doi.org/10.1107/S2059798317017235); D. G. Waterman,
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G. Winter, R. J. Gildea et al., "Diffraction-geometry refinement in the DIALS framework" (2016),
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Acta Cryst. D72, 558-575 [doi:10.1107/S2059798316002187](https://doi.org/10.1107/S2059798316002187);
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J. Beilsten-Edmands, G. Winter, R. Gildea et al., "Scaling diffraction data in the DIALS software
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package: algorithms and new approaches for multi-crystal scaling" (2020), Acta Cryst. D76, 385-399
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[doi:10.1107/S2059798320003198](https://doi.org/10.1107/S2059798320003198); J. M. Parkhurst,
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G. Winter, D. G. Waterman et al., "Robust background modelling in DIALS" (2016), J. Appl. Cryst. 49,
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1912-1921 [doi:10.1107/S1600576716013595](https://doi.org/10.1107/S1600576716013595).
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**[POINTLESS](https://www.ccp4.ac.uk/)** (CCP4) — the space-group search. Stage A scores each
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candidate rotation operator by the correlation of I(h) with I(Rh) on **resolution-normalised**
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intensities (E²), as POINTLESS does — both arms of a symmetry pair sit at the same |s|, so on raw
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intensities the resolution fall-off is variance shared between them and lifts a false operator's
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correlation as much as a true one's; the screw-axis test scores a
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predicted-absent class against the rest of its own axial row rather than against a global mean or a
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fixed cut, and lets confidence fall away with the number of axial reflections instead of refusing
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below a count. P. Evans, "Scaling and assessment of data quality" (2006), Acta Cryst. D62, 72-82
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[doi:10.1107/S0907444905036693](https://doi.org/10.1107/S0907444905036693); P. R. Evans, "An
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introduction to data reduction: space-group determination, scaling and intensity statistics" (2011),
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Acta Cryst. D67, 282-292 [doi:10.1107/S090744491003982X](https://doi.org/10.1107/S090744491003982X);
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P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
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Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061);
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J. Agirre, M. Atanasova, H. Bagdonas et al., "The CCP4 suite: integrative software for macromolecular
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crystallography" (2023), Acta Cryst. D79, 449-461
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[doi:10.1107/S2059798323003595](https://doi.org/10.1107/S2059798323003595).
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**[MOSFLM](https://www.mrc-lmb.cam.ac.uk/mosflm/)** — the Rossmann FFT autoindexing algorithm and
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post-refinement practice, including which parameters are safe to refine per image and which must be
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refined over a wedge. The autoindexing algorithm itself — projecting the reciprocal-space points
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onto many directions and Fourier-transforming the 1D projection histograms — is I. Steller,
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R. Bolotovsky and M. G. Rossmann, "An algorithm for automatic indexing of oscillation images using
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Fourier analysis" (1997), J. Appl. Cryst. 30, 1036-1040
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[doi:10.1107/S0021889897008777](https://doi.org/10.1107/S0021889897008777); MOSFLM is the
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implementation whose practice is followed. A. G. W. Leslie and H. R. Powell, "Processing diffraction data with MOSFLM"
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(2007), in *Evolving Methods for Macromolecular Crystallography*, NATO Science Series II, vol. 245,
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41-51 [doi:10.1007/978-1-4020-6316-9_4](https://doi.org/10.1007/978-1-4020-6316-9_4);
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T. G. G. Battye, L. Kontogiannis, O. Johnson, H. R. Powell and A. G. W. Leslie, "iMOSFLM: a new
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graphical interface for diffraction-image processing with MOSFLM" (2011), Acta Cryst. D67, 271-281
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[doi:10.1107/S0907444910048675](https://doi.org/10.1107/S0907444910048675); H. R. Powell,
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T. G. G. Battye, L. Kontogiannis, O. Johnson and A. G. W. Leslie, "Integrating macromolecular X-ray
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diffraction data with the graphical user interface iMosflm" (2017), Nat. Protoc. 12, 1310-1325
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[doi:10.1038/nprot.2017.037](https://doi.org/10.1038/nprot.2017.037).
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**[CrystFEL](https://www.desy.de/~twhite/crystfel/)** — spot finding, the three-ring integration
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region, the serial/stills processing model, and the per-frame indexing acceptance test
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(`indexing_peak_check()` in `peaks.c`). T. A. White, R. A. Kirian, A. V. Martin, A. Aquila, K. Nass,
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A. Barty and H. N. Chapman, "CrystFEL: a software suite for snapshot serial crystallography" (2012),
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J. Appl. Cryst. 45, 335-341 [doi:10.1107/S0021889812002312](https://doi.org/10.1107/S0021889812002312).
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The self-calibrating spot finder's per-resolution-ring background statistics, with the Bragg peaks
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excluded by iterated clipping, follow Cheetah's peakfinder8: A. Barty, R. A. Kirian,
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F. R. N. C. Maia, M. Hantke, C. H. Yoon, T. A. White and H. N. Chapman, "Cheetah: software for
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high-throughput reduction and analysis of serial femtosecond X-ray diffraction data" (2014),
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J. Appl. Cryst. 47, 1118-1131
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[doi:10.1107/S1600576714007626](https://doi.org/10.1107/S1600576714007626).
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**[fast-feedback-indexer](https://github.com/paulscherrerinstitute/fast-feedback-indexer)** — the
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known-cell indexer for serial stills (`-X ffbidx`) is PSI's fast-feedback-indexer library, linked at
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build time (BSD-3-Clause; see [THIRD_PARTY_NOTICES.md](THIRD_PARTY_NOTICES.md)), which implements
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the TORO algorithm: P. Gasparotto, L. Barba, H.-C. Stadler, G. Assmann, H. Mendonça, A. W. Ashton,
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M. Janousch, F. Leonarski and B. Béjar, "TORO Indexer: a PyTorch-based indexing algorithm for
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kilohertz serial crystallography" (2024), J. Appl. Cryst. 57, 931-944
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[doi:10.1107/S1600576724003182](https://doi.org/10.1107/S1600576724003182).
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**[GEMMI](https://github.com/project-gemmi/gemmi)** — symmetry operations, unit-cell and
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structure-factor machinery, and MTZ / XDS_ASCII I/O. Vendored in `gemmi_gph/`, so it also carries a
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licence obligation. M. Wojdyr, "GEMMI: A library for structural biology" (2022), J. Open Source
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Softw. 7, 4200 [doi:10.21105/joss.04200](https://doi.org/10.21105/joss.04200).
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**Křivý & Gruber's Niggli reduction, and the lattice-character table** — the reduction that puts
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every candidate cell in a comparable form is I. Křivý and B. Gruber, "A unified algorithm for
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determining the reduced (Niggli) cell" (1976), Acta Cryst. A32, 297-298
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[doi:10.1107/S0567739476000636](https://doi.org/10.1107/S0567739476000636), used through GEMMI's
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implementation; the table of lattice characters that maps a reduced cell to Bravais lattices and
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centrings follows International Tables for Crystallography Vol. A, Table 9.2.5.1.
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**Grosse-Kunstleve, Sauter & Adams's numerically stable cell reduction** - the magnitude-scaled
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tolerance that decides the sign of a structurally-zero scalar product, and with it the Niggli type a
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reduced cell is presented in. R. W. Grosse-Kunstleve, N. K. Sauter and P. D. Adams, "Numerically
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stable algorithms for the computation of reduced unit cells" (2004), Acta Cryst. A60, 1-6
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[doi:10.1107/S010876730302186X](https://doi.org/10.1107/S010876730302186X).
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**Le Page's metric-symmetry search** - the obliquity of each of the 81 candidate two-folds of a
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reduced cell, which is what tells a run that its lattice metric hosts more rotational symmetry than
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the group its intensities supported. Used through GEMMI's implementation of it. Y. Le Page, "The
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derivation of the axes of the conventional unit cell from the dimensions of the Buerger-reduced
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cell" (1982), J. Appl. Cryst. 15, 255-259
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[doi:10.1107/S0021889882011959](https://doi.org/10.1107/S0021889882011959).
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**Hexagonal-ice ring positions** — the eleven ring $d$ spacings from 3.895 to 1.522 Å that the
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ice-ring score, the ice-ring flagging and the ice calibrant are all built on are taken from the
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measurements of, not enumerated from a cell. D. W. Moreau, H. Atakisi and R. E. Thorne, "Ice in
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biomolecular cryocrystallography" (2021), Acta Cryst. D77, 540-554
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[doi:10.1107/S2059798321001170](https://doi.org/10.1107/S2059798321001170).
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That list ends at 1.522 Å by its own scope, so the eight bands below it are calculated here rather
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than taken from anyone: ice Ih structure factors on the oxygen sublattice, kept where they reach 3% of
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the strongest line, which reproduces the eleven measured positions exactly. The lattice constants are
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Röttger and co-workers'. K. Röttger, A. Endriss, J. Ihringer, S. Doyle and W. F. Kuhs, "Lattice
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constants and thermal expansion of H2O and D2O ice Ih between 10 and 265 K" (1994), Acta Cryst. B50,
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644-648 [doi:10.1107/S0108768194004933](https://doi.org/10.1107/S0108768194004933).
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**The twinning L test** is Padilla and Yeates's: pairing each acentric reflection with a
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symmetry-independent neighbour and reading the first and second moments of
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L = (I1−I2)/(I1+I2) against their untwinned and perfect-twin values. J. E. Padilla and
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T. O. Yeates, "A statistic for local intensity differences: robustness to anisotropy and
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pseudo-centering and utility for detecting twinning" (2003), Acta Cryst. D59, 1124-1130
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[doi:10.1107/S0907444903007947](https://doi.org/10.1107/S0907444903007947).
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**Diffraction anisotropy** — the description of the overall fall-off by a single anisotropic
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displacement tensor, its symmetry constraints, and the fact that only its deviatoric part is
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determined (the isotropic part being degenerate with the overall scale) are Sheriff and Hendrickson's.
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The estimator fits that tensor to the observed intensity distribution, taking sigma(I) into account,
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in the sense of Popov and Bourenkov. The directional diffraction limits - <I/sigma(I)> in a cone about
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each principal direction, and the reporting of the anisotropic deltaB as the range of the principal
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components - follow AIMLESS. rugnux reports these; it corrects no intensity and removes no reflection
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on a directional criterion. S. Sheriff and W. A. Hendrickson, "Description of overall anisotropy in
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diffraction from macromolecular crystals" (1987), Acta Cryst. A43, 118-121
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[doi:10.1107/S010876738709977X](https://doi.org/10.1107/S010876738709977X); A. N. Popov and
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G. P. Bourenkov, "Choice of data-collection parameters based on statistic modelling" (2003), Acta
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Cryst. D59, 1145-1153 [doi:10.1107/S0907444903008163](https://doi.org/10.1107/S0907444903008163);
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P. R. Evans and G. N. Murshudov, "How good are my data and what is the resolution?" (2013), Acta
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Cryst. D69, 1204-1214 [doi:10.1107/S0907444913000061](https://doi.org/10.1107/S0907444913000061).
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**[ANODE](https://doi.org/10.1107/S0021889811041768)** — reading the anomalous difference map at the
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atoms of a supplied model and reporting the strongest sites by name, instead of searching the map for
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blobs. The map itself is the textbook anomalous difference Fourier; what is taken from ANODE is that
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reading: A. Thorn and G. M. Sheldrick, "ANODE: anomalous and heavy-atom density calculation" (2011),
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J. Appl. Cryst. 44, 1285-1287
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[doi:10.1107/S0021889811041768](https://doi.org/10.1107/S0021889811041768).
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**Data-quality statistics** follow the established conventions rather than any one program: R_meas
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and R_pim, CC1/2 and CC\*, and the reporting of I/sigma(I). K. Diederichs and P. A. Karplus, "Improved
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R-factors for diffraction data analysis in macromolecular crystallography" (1997), Nat. Struct. Biol.
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4, 269-275 [doi:10.1038/nsb0497-269](https://doi.org/10.1038/nsb0497-269); P. A. Karplus and
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K. Diederichs, "Linking crystallographic model and data quality" (2012), Science 336, 1030-1033
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[doi:10.1126/science.1218231](https://doi.org/10.1126/science.1218231); K. Diederichs and
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P. A. Karplus, "Better models by discarding data?" (2013), Acta Cryst. D69, 1215-1222
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[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
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[doi:10.1107/S0108767388009596](https://doi.org/10.1107/S0108767388009596); D. Schwarzenbach,
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||
S. C. Abrahams, H. D. Flack, E. Prince and A. J. C. Wilson, "Statistical descriptors in
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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).
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