NanoMAX example dataset - ptychography on siemens stars - EH2
Description
Example (single-beam single-slice) hard X-ray ptychographic dataset recorded at the Diffraction Endstation (EH2) [1] of the NanoMAX beamline [2] at the MAX IV Laboratory [3].
The datasets were recorded on two different siemens star samples. They are kept in the folder and file structure typical to the lab and beamline. The upload contains the raw data, the script used to reconstruct the raw, the final reconstruction results and a jupyter notebook loading the reconstructions to create a figure of the reconstructed objects.
Data was recorded at a photon energy of 16 keV. A pair of KB-mirrors [4] was used to focus the probing X-ray beam. The samples were scanned in a Fermat-spiral scanning pattern [6] over a scan region of 6µm x 6µm with an average step size of 0.3µm. At each scan position a diffraction pattern was recorded with an Eiger2 X 1M detector (DECTRIS, Switzland) [7] and an exposure time of 1 second. The detector was positioned 3.635m downstream of the sample.
Reconstructions were performed using the ptypy-framework [8] using 1000 iterations of the difference-map (DM) algorithm [9], followed by 4000 iterations of the maximum likelihood (ML) algorithm [10] implemented for GPUs using cupy [11].
We acknowledge the MAX IV Laboratory for beamtime on the NanoMAX beamline under proposal 20250953. Research conducted at MAX IV, a Swedish national user facility, is supported by Vetenskapsrådet (Swedish Research Council, VR) under contract 2018-07152, Vinnova (Swedish Governmental Agency for Innovation Systems) under contract 2018-04969 and Formas under contract 2019-02496.
References:
[1] Dina Carbone et al., "Design and performance of a dedicated coherent X-ray scanning diffraction instrument at beamline NanoMAX of MAX IV", J. Synchrotron Rad. 29, 876-887 (2022). https://doi.org/10.1107/S1600577522001333
[2] Ulf Johansson et al., "NanoMAX: the hard X-ray nanoprobe beamline at the MAX IV Laboratory", J. Synchrotron Rad. 28, 1935-1947 (2023). https://doi.org/10.1107/S1600577521008213
[3] Aymeric Robert et al., "MAX IV Laboratory". Eur. Phys. J. Plus 138, 495 (2023). https://doi.org/10.1140/epjp/s13360-023-04018-w
[4] Maik Kahnt et al., "Complete alignment of a KB-mirror system guided by ptychography," Opt. Express 30, 42308-42322 (2022) https://doi.org/10.1364/OE.470591
[6] Xiaojing Huang et al., "Optimization of overlap uniformness for ptychography", Opt. Express 22, 12634-12644 (2014). https://doi.org/10.1364/OE.22.012634
[7] Tilman Donath et al., "EIGER2 hybrid-photon-counting X-ray detectors for advanced synchrotron diffraction experiments", J. Synchrotron Rad. 30, 723-738.(2023). https://doi.org/10.1107/S160057752300454X
[8] Björn Enders et al., "Computational framework for ptychographic reconstructions", Proc. R. Soc. A.47220160640 (2016). http://doi.org/10.1098/rspa.2016.0640
[9] Pierre Thibault et al., “Probe retrieval in ptychographic coherent diffractive imaging,” Ultramicroscopy 109(4), 338–343 (2009). https://doi.org/10.1016/j.ultramic.2008.12.011
[10] Pierre Thibault et al., "Maximum-likelihood refinement for coherent diffractive imaging," New J. Phys. 14 063004 (2012). https://doi.org/10.1088/1367-2630/14/6/063004
[11] Ryosuke Okuta et al. "Cupy: A numpy-compatible library for nvidia gpu calculations." Proceedings of workshop on machine learning systems (LearningSys) in the thirty-first annual conference on neural information processing systems (NIPS). Vol. 6. (2017).
Files
Figure_reconstruction_result.png
Files
(1.3 GB)
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Additional details
Software
- Programming language
- Python