Recent years have seen the rapid growth and development of the field of smart photonics,
where machine-learning algorithms are being matched to optical systems to add new …

Electronically excited states of molecules are at the heart of photochemistry, photophysics,
as well as photobiology and also play a role in material science. Their theoretical description …

We provide a review of machine learning (ML) tools for material discovery and sophisticated
applications of different ML strategies. Although there have been a few published reviews on …

The time–energy information of ultrashort X-ray free-electron laser pulses generated by the
Linac Coherent Light Source is measured with attosecond resolution via angular streaking …

In the field of beam physics, two frontier topics have taken center stage due to their potential
to enable new approaches to discovery in a wide swath of science. These areas are …

Neutron and x-ray scattering represent two classes of state-of-the-art materials
characterization techniques that measure materials structural and dynamical properties with …

The development of high-brilliance third-and fourth-generation light sources such as
synchrotrons and X-ray free-electron lasers (XFELs), the emergence of laboratory-based X …

Artificial intelligence (AI) has received widespread attention over the last few decades due to
its potential to increase automation and accelerate productivity. In recent years, a large …

Self-tuning optical systems are of growing importance in technological applications such as
mode-locked fiber lasers. Such self-tuning paradigms require intelligent algorithms capable …

We report on the application of machine learning (ML) methods for predicting the
longitudinal phase space (LPS) distribution of particle accelerators. Our approach consists …