Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions

Christian Beck; Kevin Pounot; Ilaria Mosca; Niina H jalarvo; Felix Roosen-Runge; Frank Schreiber; Tilo Seydel

doi:10.1051/epjconf/202227201004

Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions

Christian Beck, Kevin Pounot, Ilaria Mosca, Niina H jalarvo, Felix Roosen-Runge, Frank Schreiber, Tilo Seydel

Research output: Contribution to journal › Article › peer-review

Abstract

With continuously improving signal-to-noise ratios, a statistically sound analysis of quasi-elastic neutron scattering (QENS) spectra requires to fit increasingly complex models which poses several challenges. Simultaneous fits of the spectra for all recorded values of the momentum transfer become a standard approach. Spectrometers at spallation sources can have a complicated non-Gaussian resolution function which has to be described most accurately. At the same time, to speed up the fitting, an analytical convolution with this resolution function is of interest. Here, we discuss basic concepts to efficient approaches for fits of QENS spectra based on standard MATLAB and Python fit algorithms. We illustrate the fits with example data from IN16B, BASIS, and BATS.

Original language	English
Article number	01004
Number of pages	7
Journal	EPJ Web of Conferences
Volume	272
DOIs	https://doi.org/10.1051/epjconf/202227201004
Publication status	Published - 2022 Jan 1
Externally published	Yes

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title = "Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions",

abstract = "With continuously improving signal-to-noise ratios, a statistically sound analysis of quasi-elastic neutron scattering (QENS) spectra requires to fit increasingly complex models which poses several challenges. Simultaneous fits of the spectra for all recorded values of the momentum transfer become a standard approach. Spectrometers at spallation sources can have a complicated non-Gaussian resolution function which has to be described most accurately. At the same time, to speed up the fitting, an analytical convolution with this resolution function is of interest. Here, we discuss basic concepts to efficient approaches for fits of QENS spectra based on standard MATLAB and Python fit algorithms. We illustrate the fits with example data from IN16B, BASIS, and BATS.",

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AU - Beck, Christian

AU - Pounot, Kevin

AU - Mosca, Ilaria

AU - H jalarvo, Niina

AU - Roosen-Runge, Felix

AU - Schreiber, Frank

AU - Seydel, Tilo

PY - 2022/1/1

Y1 - 2022/1/1

N2 - With continuously improving signal-to-noise ratios, a statistically sound analysis of quasi-elastic neutron scattering (QENS) spectra requires to fit increasingly complex models which poses several challenges. Simultaneous fits of the spectra for all recorded values of the momentum transfer become a standard approach. Spectrometers at spallation sources can have a complicated non-Gaussian resolution function which has to be described most accurately. At the same time, to speed up the fitting, an analytical convolution with this resolution function is of interest. Here, we discuss basic concepts to efficient approaches for fits of QENS spectra based on standard MATLAB and Python fit algorithms. We illustrate the fits with example data from IN16B, BASIS, and BATS.

AB - With continuously improving signal-to-noise ratios, a statistically sound analysis of quasi-elastic neutron scattering (QENS) spectra requires to fit increasingly complex models which poses several challenges. Simultaneous fits of the spectra for all recorded values of the momentum transfer become a standard approach. Spectrometers at spallation sources can have a complicated non-Gaussian resolution function which has to be described most accurately. At the same time, to speed up the fitting, an analytical convolution with this resolution function is of interest. Here, we discuss basic concepts to efficient approaches for fits of QENS spectra based on standard MATLAB and Python fit algorithms. We illustrate the fits with example data from IN16B, BASIS, and BATS.

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DO - 10.1051/epjconf/202227201004

M3 - Article

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VL - 272

JO - EPJ Web of Conferences

JF - EPJ Web of Conferences

M1 - 01004

ER -

Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions

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