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001005513 037__ $$aFZJ-2023-01513
001005513 1001_ $$0P:(DE-Juel1)195622$$aRobledo, Jose Ignacio$$b0$$ufzj
001005513 1112_ $$aEighth European Conference on Neutron Scattering$$cTUM Department of Mechanical Engineering and the new Science Congress Center Munich$$d2023-03-19 - 2023-03-23$$gECNS 2023$$wGermany
001005513 245__ $$aAutomated grouping of spatially distributed detectors in neutron time-of-flight experiments based on multivariate similarity
001005513 260__ $$c2023
001005513 3367_ $$033$$2EndNote$$aConference Paper
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001005513 520__ $$aNowadays, in neutron time of flight measurements, there are experimental setups in which many detectors record data during a single experiment. It is usually desirable to be able to sum several spectra in order to increase counting statistics, and therefore decrease uncertainties, for further analysis. A problem arises in time-of-flight experiments when the available spectra are acquired with a set of spatially distributed detectors, each forming a different source-sample-detector angle and at different sample-detector distances. Since these spectra record the neutron’s time of flight after scattering, and the neutron scattering depends on the Q vector, then these spectra are not arbitrarily summable. In this work, we propose an automated methodology for wisely adding spectra based on their multivariate similarity by means of machine learning techniques, such as k nearest neighbors combined with T-distributed Stochastic Neighbor Embedding (t-SNE). We exemplify it in the effective temperature determination of hydrogen in ethane and triphenylmethane samples by means of Deep Inelastic Neutron Scattering, measured at the VESUVIO spectrometer (ISIS facility, UK). The proposed methodology can be applied in other time-of-flight experiments, in which detectors located at different angles record complete spectra, and with this method their degree of compatibility can be determined.
001005513 536__ $$0G:(DE-HGF)POF4-632$$a632 - Materials – Quantum, Complex and Functional Materials (POF4-632)$$cPOF4-632$$fPOF IV$$x0
001005513 536__ $$0G:(DE-HGF)POF4-6G4$$a6G4 - Jülich Centre for Neutron Research (JCNS) (FZJ) (POF4-6G4)$$cPOF4-6G4$$fPOF IV$$x1
001005513 7001_ $$0P:(DE-HGF)0$$aCantargi, Florencia$$b1
001005513 7001_ $$0P:(DE-HGF)0$$aDawidowski, Javier$$b2
001005513 909CO $$ooai:juser.fz-juelich.de:1005513$$pVDB
001005513 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)195622$$aForschungszentrum Jülich$$b0$$kFZJ
001005513 9131_ $$0G:(DE-HGF)POF4-632$$1G:(DE-HGF)POF4-630$$2G:(DE-HGF)POF4-600$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bForschungsbereich Materie$$lVon Materie zu Materialien und Leben$$vMaterials – Quantum, Complex and Functional Materials$$x0
001005513 9131_ $$0G:(DE-HGF)POF4-6G4$$1G:(DE-HGF)POF4-6G0$$2G:(DE-HGF)POF4-600$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bForschungsbereich Materie$$lGroßgeräte: Materie$$vJülich Centre for Neutron Research (JCNS) (FZJ)$$x1
001005513 9141_ $$y2023
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