Advances in utilizing event based data structures for neutron scattering experiments
Abstract
This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Finally, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.
- Authors:
-
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES)
- OSTI Identifier:
- 1486961
- Alternate Identifier(s):
- OSTI ID: 1471794
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Review of Scientific Instruments
- Additional Journal Information:
- Journal Volume: 89; Journal Issue: 9; Journal ID: ISSN 0034-6748
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 74 ATOMIC AND MOLECULAR PHYSICS; neutron scattering; Poisson statistics; clustering; machine learning; diffraction
Citation Formats
Peterson, Peter F., Olds, Daniel, Savici, Andrei T., and Zhou, Wenduo. Advances in utilizing event based data structures for neutron scattering experiments. United States: N. p., 2018.
Web. doi:10.1063/1.5034782.
Peterson, Peter F., Olds, Daniel, Savici, Andrei T., & Zhou, Wenduo. Advances in utilizing event based data structures for neutron scattering experiments. United States. https://doi.org/10.1063/1.5034782
Peterson, Peter F., Olds, Daniel, Savici, Andrei T., and Zhou, Wenduo. Fri .
"Advances in utilizing event based data structures for neutron scattering experiments". United States. https://doi.org/10.1063/1.5034782. https://www.osti.gov/servlets/purl/1486961.
@article{osti_1486961,
title = {Advances in utilizing event based data structures for neutron scattering experiments},
author = {Peterson, Peter F. and Olds, Daniel and Savici, Andrei T. and Zhou, Wenduo},
abstractNote = {This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Finally, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.},
doi = {10.1063/1.5034782},
journal = {Review of Scientific Instruments},
number = 9,
volume = 89,
place = {United States},
year = {Fri Sep 21 00:00:00 EDT 2018},
month = {Fri Sep 21 00:00:00 EDT 2018}
}
Web of Science
Figures / Tables:
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Figures / Tables found in this record: