Bayesian Gaussian process inference for neutron spin echo measurement

C Chi-Huan Tung (Neutron Scattering Division, Oak Ridge National Laboratory 1 , Oak Ridge, Tennessee 37831,) G Guan-Rong Huang (Department of Engineering and System Science, National Tsing Hua University 2 , Hsinchu 30013,) I Ingo Hoffmann (Institut Laue-Langevin 4 , 71 Avenue des Martyrs, B.P. 156, F-38042 Grenoble Cedex 9,) P Péter Falus (Institut Laue-Langevin 4 , 71 Avenue des Martyrs, B.P. 156, F-38042 Grenoble Cedex 9,) B Bela Farago (Institut Laue-Langevin 4 , 71 Avenue des Martyrs, B.P. 156, F-38042 Grenoble Cedex 9,) L Lionel Porcar (Institut Laue-Langevin) G Georg Ehlers (Neutron Technologies Division, Oak Ridge National Laboratory 5 , Oak Ridge, Tennessee 37831,) Y Yuya Shinohara (Materials Science and Technology Division, Oak Ridge National Laboratory 6 , Oak Ridge, Tennessee 37831,) J Jan-Michael Carrillo (Center for Nanophase Materials Sciences, Oak Ridge National Laboratory 3 , Oak Ridge, Tennessee 37831,) Y Yangyang Wang (Wuya College of Innovation) S Sidney Yip (Department of Nuclear Sciences and Engineering, Massachusetts Institute of Technology 8 , Cambridge, Massachusetts 02139,) P Piotr Zolnierczuk (Neutron Scattering Division, Oak Ridge National Laboratory 1 , Oak Ridge, Tennessee 37831,) L Lijie Ding (Xi’an Jiaotong University , , , ,) C Changwoo Do (Neutron Scattering Division) W Wei-Ren Chen (Neutron Scattering Division, Oak Ridge National Laboratory 1 , Oak Ridge, Tennessee 37831,)

Abstract

Neutron spin echo (NSE) spectroscopy provides unique access to microscopic dynamics, but its application is often constrained by low neutron flux, long acquisition times, and significant noise. We present a Bayesian inference approach based on Gaussian process regression (GPR) to reconstruct high-quality spin echo signals from sparse and noisy data by exploiting correlations in reciprocal space. Benchmarks on synthetic datasets and validation with experimental NSE measurements of dendrimers show that GPR suppresses noise, interpolates missing intensity values, and accommodates irregular observations. The method improves accuracy, shortens acquisition times, and enables high-throughput and real-time studies. Beyond NSE, the framework is broadly applicable to other low signal-to-noise ratio scattering techniques, thereby extending the scope of neutron spectroscopy.

Article Details

Volume / Issue Vol. 163, Issue 23
Published December 21, 2025
ISSN 0021-9606
Publisher American Institute of Physics

Journal Info

The Journal of Chemical Physics

American Institute of Physics

ISSN: 0021-9606 Physical Sciences

Authors (15)

C

Chi-Huan Tung

Neutron Scattering Division, Oak Ridge National Laboratory 1 , Oak Ridge, Tennessee 37831,

G

Guan-Rong Huang

Department of Engineering and System Science, National Tsing Hua University 2 , Hsinchu 30013,

I

Ingo Hoffmann

Institut Laue-Langevin 4 , 71 Avenue des Martyrs, B.P. 156, F-38042 Grenoble Cedex 9,

P

Péter Falus

Institut Laue-Langevin 4 , 71 Avenue des Martyrs, B.P. 156, F-38042 Grenoble Cedex 9,

B

Bela Farago

Institut Laue-Langevin 4 , 71 Avenue des Martyrs, B.P. 156, F-38042 Grenoble Cedex 9,

L

Lionel Porcar

Institut Laue-Langevin

G

Georg Ehlers

Neutron Technologies Division, Oak Ridge National Laboratory 5 , Oak Ridge, Tennessee 37831,

Y

Yuya Shinohara

Materials Science and Technology Division, Oak Ridge National Laboratory 6 , Oak Ridge, Tennessee 37831,

J

Jan-Michael Carrillo

Center for Nanophase Materials Sciences, Oak Ridge National Laboratory 3 , Oak Ridge, Tennessee 37831,

Y

Yangyang Wang

Wuya College of Innovation

S

Sidney Yip

Department of Nuclear Sciences and Engineering, Massachusetts Institute of Technology 8 , Cambridge, Massachusetts 02139,

P

Piotr Zolnierczuk

Neutron Scattering Division, Oak Ridge National Laboratory 1 , Oak Ridge, Tennessee 37831,

L

Lijie Ding

Xi’an Jiaotong University , , , ,

C

Changwoo Do

Neutron Scattering Division

W

Wei-Ren Chen

Neutron Scattering Division, Oak Ridge National Laboratory 1 , Oak Ridge, Tennessee 37831,