Weak signal extraction enabled by deep neural network denoising of diffraction data.

The removal or cancellation of noise has wide-spread applications in imaging and acoustics. In applications in everyday life, such as image restoration, denoising may even include generative aspects, which are unfaithful to the ground truth. For scientific use, however, denoising must reproduce the ground truth accurately. Denoising scientific data is further challenged by unknown noise profiles. In fact, such data will often include noise from multiple distinct sources, which substantially reduces the applicability of simulation-based approaches. Here we show how scientific data can be denoised by using a deep convolutional neural network such that weak signals appear with quantitative accuracy. In particular, we study X-ray diffraction and resonant X-ray scattering data recorded on crystalline materials. We demonstrate that weak signals stemming from charge ordering, insignificant in the noisy data, become visible and accurate in the denoised data. This success is enabled by supervised training of a deep neural network with pairs of measured low- and high-noise data. We additionally show that using artificial noise does not yield such quantitatively accurate results. Our approach thus illustrates a practical strategy for noise filtering that can be applied to challenging acquisition problems.

Prototype of the novel CAMEA concept-A backend for neutron spectrometers.

The continuous angle multiple energy analysis concept is a backend for both time-of-flight and analyzer-based neutron spectrometers optimized for neutron spectroscopy with highly efficient mapping in the horizontal scattering plane. The design employs a series of several upward scattering analyzer arcs placed behind each other, which are set to different final energies allowing a wide angular coverage with multiple energies recorded simultaneously. For validation of the concept and the model calculations, a prototype was installed at the Swiss neutron source SINQ, Paul Scherrer Institut. The design of the prototype, alignment and calibration procedures, experimental results of background measurements, and proof-of-concept inelastic measurements on LiHoF4 and h-YMnO3 are presented here.