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Published July 24, 2022 | Version v3
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X-ray diffraction dataset for experimental noise filtering

  • 1. University of Zurich, Switzerland
  • 2. DESY, Hamburg
  • 3. Technical university of Denmark
  • 4. Hokkaido university, Japan

Description

X-ray diffraction data set for the training of noise filtering algorithms. The data set contains groups of low- and high-counting statistics pairs. The sampling times are mostly 1 (20) seconds for low (high) counting data. Three files in HDF5 format are provided, corresponding to a training, validation and test data set. Each data group contains sequences of 41 consecutive frames, corresponding to a scan along the reciprocal h-direction. Next to the raw data, sampling times and monitor values are included. The test data set additionally contains denoised low-count frames obtained from a pre-trained neural network.

The data has been recorded on a La1.88Sr0.12CuO4 single crystal at the beamline P21.1 at the PETRA III storage ring at DESY in Hamburg, Germany. The scattering intensities were recorded using Dectris Pilatus 100K CdTe detector. The diffractometer was operated with 100 keV photons and the sample was cooled to T ~ 30 K. The data contains different signals such as weak 2D charge density wave order, fundamental Bragg peaks, powder lines, spurions and dead pixels.

Notes

Additional funding: ONR (N00014-20-1-2352) European Union's Horizon 2020 research and innovation program (ERC-StG-Neupoert-757867-PARATOP) EU framework program for research and innovation Horizon 2020 CALIPSOplus (730872)

Files

Files (3.2 GB)

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md5:cd3893c9ba2c81ff22fc7aea35d857b8
1.7 GB Download
md5:5006c66c8d9aef0d45fa390be3019279
1.2 GB Download
md5:b5a7fb207fca20aad5f66116b4324250
302.3 MB Download

Additional details

Related works

Is cited by
Preprint: 10.48550/arXiv.2209.09247 (DOI)

Funding

Swiss National Science Foundation
Controlling Elementary Excitations in Correlated Systems PP00P2_176866
Swiss National Science Foundation
Interdisciplinary Approach to Unconventional Superconductivity 200021_188564