Laser-plasma physics has developed rapidly over the past few decades as lasers have
become both more powerful and more widely available. Early experimental and numerical …

Developments in machine learning promise to ameliorate some of the challenges of
modeling complex physical systems through neural-network-based surrogate models. High …

The recent advent of deep artificial neural networks has resulted in a dramatic increase in
performance for object classification and detection. While pre-trained with everyday objects …

High power laser-driven ion acceleration produces bright beams of energetic ions that have
the potential to be applied in a wide range of sectors. The routine generation of optimised …

Plasma supports collective modes and particle–wave interactions that lead to complex
behaviour in, for example, inertial fusion energy applications. While plasma can sometimes …

Computer models of intense, laser-driven ion acceleration require expensive particle-in-cell
simulations that may struggle to capture all the multi-scale, multi-dimensional physics …

The optimum parameters for the generation of synchrotron radiation in ultraintense laser
pulse interactions with planar foils are investigated with the application of Bayesian …

With the advent of multi-petawatt lasers, the relativistic transparency regime of laser-plasma
interactions becomes readily accessible for near-solid density targets. Initially opaque …

We explore the applications of a variety of machine learning techniques in relativistic laser-
plasma experiments beyond optimization purposes. With the trained supervised learning …

In this work, we have looked into the amplitude modulation and formation of enveloping
soliton in a dense plasma with thermal degeneracy pressure expressions as a strong laser …