Files
Jungfraujoch/docs/ACKNOWLEDGEMENT.md
T
leonarski_fandClaude Opus 5 43627e22dc docs: a rule for licences and academic credit, and apply it
Several methods adopted recently came from other crystallographic packages - the screw-absence test
from POINTLESS, MINPK and the profile-fit reweighting from XDS/Otwinowski, the CC1/2 cutoff and merge
outlier rejection from DIALS, the per-frame indexing gate from CrystFEL - and nothing in the
repository said where such a debt is recorded. The licence side was already worked out (licences beside
the vendored code, verbatim texts in licenses/ collected by COLLECT.sh, a row in THIRD_PARTY_NOTICES.md,
all installed under share/doc/jfjoch); the credit side was ad hoc.

Write the rule into CLAUDE.md. It states the distinction that matters: vendoring or linking someone's
CODE creates a LICENCE obligation, discharged in licenses/ and THIRD_PARTY_NOTICES.md; reimplementing
an algorithm from a PAPER creates none of that but creates an obligation of academic CREDIT, discharged
in docs/ACKNOWLEDGEMENT.md and in a comment at the algorithm. Neither substitutes for the other, and
taking both source and paper incurs both. It also fixes the citation form (authors, title, year,
journal, volume, pages, verified DOI), and says in-source credit goes at the algorithm, not the file
header, in the one-line style the code already uses.

Then bring the repository into compliance for the works concerned: docs/ACKNOWLEDGEMENT.md gains a
section acknowledging XDS, DIALS, POINTLESS/CCP4, MOSFLM, CrystFEL, GEMMI, the Kabsch/Otwinowski
profile fit, the Diederichs & Karplus statistics and the IUCr nomenclature reports, each with a DOI
checked against Crossref; docs/CPU_DATA_ANALYSIS.md's reference list gains the ones it was missing;
and four algorithms gain a line naming their source where no adjacent comment carried one.

No licence change. licenses/ and THIRD_PARTY_NOTICES.md are untouched.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-11 16:34:48 +02:00

8.9 KiB

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.

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. 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; 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.

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).

XDS — 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; W. Kabsch, "Integration, scaling, space-group assignment and post-refinement" (2010), Acta Cryst. D66, 133-144 doi: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.

DIALS — 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; 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; 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; 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.

POINTLESS (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; 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; 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; 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.

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; 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; 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.

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.

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.

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; P. A. Karplus and K. Diederichs, "Linking crystallographic model and data quality" (2012), Science 336, 1030-1033 doi: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.

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; 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.