ANDiE is the Autonomous Neutron Diffraction Explorer which enables the autonomous control of neutron diffraction experiments. The goal of ANDiE is to autonomously discover the magnetic order parameter and transition dynamics of a material while minimizing the number of diffraction measurements needed to do so. 

ANDiE consists of two nested Bayesian inference loops to control an autonomous experiment followed by a hypothesis testing step. ANDiE first infers the parameters of a model to describe the isothermal diffraction pattern, then predicts the temperature dependence of the magnetic component of diffraction intensity. ANDiE then increases the experiment temperature to where the model uncertainty exceeds a threshold relative to the expected Poissonian-like uncertainty in the predicted intensity. Finally, ANDiE uses a Bayes factor test to infer the best model to describe the temperature dependence of the magnetic component of the diffraction intensity. The relevant governing physics has been encoded into ANDiE to ensure that the predictions are physically realistic. 

This notebook will run a simulated autonomous neutron diffraction experiment. The last cell launches a second notebook to perform the hypothesis testing on data from a prior simulated autonomous experiment.  

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Austin McDannald^1,*, Matthias Frontzek², Andrei T. Savici², Mathieu Doucet², Efrain E. Rodriguez^3,4, Kate Meuse⁵, Jessica Opsahl-Ong⁶, Daniel Samarov⁷, Ichiro Takeuchi^4,8, William Ratcliff^8,9,*, A. Gilad Kusne^1,8

¹ Materials Measurement Laboratory, NIST, Gaithersburg, MD, 20899, USA

² Neutron Sciences Directorate, ORNL, Oak Ridge, TN, 37831, USA

³ Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, 20742 USA

⁴ Maryland Quantum Materials Center, College Park, MD, 20742, USA

⁵ Department of Computer Science, Cornell University, Ithaca, NY, USA

⁶ Department of Computer Science, Rice University, Houston, TN, USA

⁷ Information Technology Laboratory, NIST, Gaithersburg, MD, 20899, USA,

⁸ Department of Materials Science and Engineering, University of Maryland, College Park, MD, 20742 USA

⁹ NIST Center for Neutron Research, NIST, Gaithersburg, MD, 20899, USA

*Contact Author. Email: austin.mcdannald@nist.gov (A.M), william.ratcliff@nist.gov (W.R.)

https://arxiv.org/abs/2108.08918

Researchers should cite this work as follows:

• Austin McDannald (2021), "Autonomous Neutron Diffraction Explorer," https://nanohub.org/resources/andie. (DOI: 10.21981/PAFW-5G64).

  BibTex | EndNote

1. ANDiE
2. Autonomous Experiment
3. Bayesian statistics
4. Jupyter notebooks
5. machine learning
6. materials science
7. NCN Group - Machine Learning Hands-on
8. Neutron Diffraction