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About this paper
Kensuke Muto, Hirotaka Sakamoto, Kenji Nagata, Taka-hisa Arima, Masato Okada
An automatic termination strategy for inelastic neutron-scattering experiments is developed, employing Bayesian optimization for optimal bin-width selection in multidimensional histograms. This approach improves experimental efficiency by dynamically assessing data resolution and preventing redundant data acquisition, with numerical experiments demonstrating substantial reductions in necessary measurement time.
Key insights
- Optimal bin widths in inelastic neutron scattering data consistently decrease as the accumulated event count increases, reflecting improved resolution with more data.
- Even with 1/5 of the total data, optimal bin widths could approach or exceed the equipment's intrinsic resolution, indicating that real-world experiments often collect redundant data.
- Bayesian optimization reduces the search cost for optimal bin widths by approximately 90% compared to an exhaustive search, making real-time, online termination decisions feasible on standard workstations.
Summary by alphaXiv.
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