% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@INPROCEEDINGS{Robledo:1005513,
      author       = {Robledo, Jose Ignacio and Cantargi, Florencia and
                      Dawidowski, Javier},
      title        = {{A}utomated grouping of spatially distributed detectors in
                      neutron time-of-flight experiments based on multivariate
                      similarity},
      reportid     = {FZJ-2023-01513},
      year         = {2023},
      abstract     = {Nowadays, 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.},
      month         = {Mar},
      date          = {2023-03-19},
      organization  = {Eighth European Conference on Neutron
                       Scattering, TUM Department of
                       Mechanical Engineering and the new
                       Science Congress Center Munich
                       (Germany), 19 Mar 2023 - 23 Mar 2023},
      subtyp        = {Invited},
      cin          = {JCNS-2 / PGI-4 / JARA-FIT},
      cid          = {I:(DE-Juel1)JCNS-2-20110106 / I:(DE-Juel1)PGI-4-20110106 /
                      $I:(DE-82)080009_20140620$},
      pnm          = {632 - Materials – Quantum, Complex and Functional
                      Materials (POF4-632) / 6G4 - Jülich Centre for Neutron
                      Research (JCNS) (FZJ) (POF4-6G4)},
      pid          = {G:(DE-HGF)POF4-632 / G:(DE-HGF)POF4-6G4},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/1005513},
}