Mattias Marklund

Laser-plasma accelerators (LPAs) enable compact, bright x-ray sources, but their practical application demands a significant reduction of beam instabilities that originate from drive laser fluctuations. Moreover, the complexity of the laser-plasma interaction makes it difficult to disentangle and quantify the impact of individual parameters on machine performance. To address this challenge, we develop a data-driven modeling strategy and apply it to an extensive dataset collected during a daylong operation of the LPA-based x-ray source LUX. By making use of an orthogonal-distance-based training objective, our approach reduces bias originating from measurement errors, which allows us to estimate the functional dependencies between laser, accelerated electrons, and generated undulator radiation. In addition, we demonstrate accurate prediction of the x-ray spectrum based on noninvasive measurements, showcasing the potential of our approach for building virtual diagnostics.

The impact of radiation reaction and Breit-Wheeler pair production on the acceleration of fully ionized carbon ions driven by an intense linearly polarized laser pulse has been investigated in the ultra-relativistic transparency regime. Against initial expectations, the radiation reaction and pair production at ultra-high laser intensities are found to enhance the energy gained by the ions. The electrons lose most of their transverse momentum, and the additionally produced pair plasma of Breit-Wheeler electrons and positrons co-streams in the forward direction as opposed to the existing electrons streaming at an angle above zero degree. We discuss how these observations could be explained by the changes in the phase velocity of the Buneman instability, which is known to aid ion acceleration in the breakout afterburner regime, by tapping the free energy in the relative electron and ion streams. We present evidence that these non-classical effects can further improve the highest carbon ion energies in this transparency regime.

The power of machine learning (ML) in feature identification can be harnessed for determining quantities in experiments that are difficult to measure directly. However, if an ML model is trained on simulated data, rather than experimental results, the differences between the two can pose an obstacle to reliable data extraction. Here we report on the development of ML-based diagnostics for experiments on high-intensity laser–matter interactions. With the intention to accentuate robust, physics-governed features, the presence of which is tolerant to such differences, we test the application of principal component analysis, data augmentation and training with data that has superimposed noise of gradually increasing amplitude. Using synthetic data of simulated experiments, we identify that the approach based on the noise of increasing amplitude yields the most accurate ML models and thus is likely to be useful in similar projects on ML-based diagnostics.

When a pulsed, few-cycle electromagnetic wave is focused by optics with f-number smaller than two, the frequency components it contains are focused to different regions of space, building up a complex electromagnetic field structure. Accurate numerical computation of this structure is essential for many applications such as the analysis, diagnostics, and control of high-intensity laser-matter interactions. However, straightforward use of finite-difference methods can impose unacceptably high demands on computational resources, owing to the necessity of resolving far-field and near-field zones at sufficiently high resolution to overcome numerical dispersion effects. Here, we present a procedure for fast computation of tight focusing by mapping a spherically curved far-field region to periodic space, where the field can be advanced by a dispersion-free spectral solver. In many cases of interest, the mapping reduces both run time and memory requirements by a factor of order 10, making it possible to carry out simulations on a desktop machine or a single node of a supercomputer. We provide an open-source C++ implementation with Python bindings and demonstrate its use for a desktop machine, where the routine provides the opportunity to use the resolution sufficient for handling the pulses with spectra spanning over several octaves. The described approach can facilitate the stability analysis of theoretical proposals, the studies based on statistical inferences, as well as the overall development and analysis of experiments with tightly-focused short laser pulses.

It is conjectured that all perturbative approaches to quantum electrodynamics (QED) break down in the collision of a high-energy electron beam with an intense laser, when the laser fields are boosted to ‘supercritical’ strengths far greater than the critical field of QED. As field strengths increase toward this regime, cascades of photon emission and electron–positron pair creation are expected, as well as the onset of substantial radiative corrections. Here we identify the important role played by the collision angle in mitigating energy losses to photon emission that would otherwise prevent the electrons reaching the supercritical regime. We show that a collision between an electron beam with energy in the tens of GeV and a laser pulse of intensity 10 24 W cm − 2 at oblique, or even normal, incidence is a viable platform for studying the breakdown of perturbative strong-field QED. Our results have implications for the design of near-term experiments as they predict that certain quantum effects are enhanced at oblique incidence.

Modern laser technology is now sufficiently advanced that collisions between high-intensity laser pulses and laser-wakefield-accelerated (LWFA) electron beams can reach the strong-field regime, so that it is possible to measure the transition between the classical and quantum regimes of light–matter interactions. However, the energy spectrum of LWFA electron beams can fluctuate significantly from shot to shot, making it difficult to clearly discern quantum effects in radiation reaction (RR), for example. Here we show how this can be accomplished in only a single laser shot. A millimetre-scale pre-collision drift allows the electron beam to expand to a size larger than the laser focal spot and develop a correlation between transverse position and angular divergence. In contrast to previous studies, this means that a measurement of the beam’s energy-divergence spectrum automatically distinguishes components of the beam that hit or miss the laser focal spot and therefore do and do not experience RR.