# Autonomous microARPES

arXiv: https://arxiv.org/abs/2403.13815 · HTML: https://mlsanity.com/paper/2403.13815/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 38 references that are in the map.
- First posted on arXiv 16 Feb 2024.

## Builds on (most cited first, 4 of 4)

- [On scientific understanding with artificial intelligence](https://mlsanity.com/paper/2204.01467/) (2022)
- [Autonomous Materials Discovery Driven by Gaussian Process Regression with Inhomogeneous Measurement Noise and Anisotropic Kernels](https://mlsanity.com/paper/2006.02489/) (2020)
- [Active learning-assisted neutron spectroscopy with log-Gaussian processes](https://mlsanity.com/paper/2209.00980/) (2022)
- [Accelerating small-angle scattering experiments with simulation-based machine learning](https://mlsanity.com/paper/1908.09102/) (2019)

## Built on by (most cited first, 1 of 1)

- [A simulation-based training framework for machine-learning applications in ARPES](https://mlsanity.com/paper/2508.15983/) (2025)

## Abstract (arXiv)

Angle-resolved photoemission spectroscopy (ARPES) is a technique used to map the occupied electronic structure of solids. Recent progress in X-ray focusing optics has led to the development of ARPES into a microscopic tool, permitting the electronic structure to be spatially mapped across the surface of a sample. This comes at the expense of a time-consuming scanning process to cover not only a three-dimensional energy-momentum (E, kz, ky) space but also the two-dimensional surface area. Here, we implement a protocol to autonomously search both k- and real space in order to find positions of particular interest, either because of their high photoemission intensity or because of sharp spectral features. The search is based on the use of Gaussian process regression and can easily be expanded to include additional parameters or optimisation criteria. This autonomous experimental control is implemented on the SGM4 micro-focus beamline of the synchrotron radiation source ASTRID2.