Abstract Plasma-based particle accelerators, realized by driving plasma waves with either an intense laser pulse or particle beam, offer accelerating fields orders of magnitude higher than conventional accelerators. This enables sources of highly relativistic electron beams with significantly reduced spatial and economic footprints. However, optimizing beam quality and brightness remains the key challenge for demanding applications such as free-electron lasers. The plasma photocathode is a method for generating high-quality beams directly within plasma waves - but hitherto was exclusively realizable using the high-current drive beams from the kilometer-scale conventional accelerator at SLAC. Here we show implementation of a plasma photocathode in a millimeter-scale, purely plasma-based hybrid wakefield accelerator, powered by a 150 TW laser system. Its operation at high plasma densities enables exploitation of micrometer-scale source sizes and rapid acceleration through high-field gradients, which increases the potential output beam quality substantially. This high-density plasma photocathode can be implemented at state-of-the-art laser-plasma accelerators worldwide, and opens the door for high-quality beam production.

Laser ion acceleration experiments with increasing repetition rates have become more common in recent years. This allows for the study of the stability of proton beam parameters and the search for correlations with laser, target, and positioning system parameters. We conducted a trial experiment with 971 shots and determined key parameters using a variety of optical and proton detectors that are common in many experimental setups. Our findings can be helpful for planning future campaigns and assessing the relevance of certain diagnostics in the effort to monitor performance and improve the stability of future high-repetition-rate systems.

The control of light’s various degrees of freedom underpins modern physics and technology, from quantum optics to telecommunications. Ultraintense lasers represent the pinnacle of this control, concentrating light to extreme intensities at which electrons oscillate at relativistic velocities within a single optical cycle. These extraordinary conditions offer unique opportunities to probe the fundamental aspects of light–matter interactions and develop transformative applications. However, the precise characterization of intense, ultrashort lasers has lagged behind our ability to generate them, creating a bottleneck in advancing laser science and its applications. Here we present the first single-shot vector field measurement technique for intense, ultrashort laser pulses that provides an unprecedented insight into their complete spatiotemporal and polarization structure, including quantified uncertainties. Our method efficiently encodes the full vector field onto a two-dimensional detector by leveraging the inherent properties of these laser pulses, allowing for real-time characterization. We demonstrate its capabilities on systems ranging from high-repetition-rate oscillators to petawatt-class lasers, revealing subtle spatiotemporal couplings and polarization effects. This advancement bridges the gap between theory and experiment in laser physics, providing crucial data for simulations and accelerating the development of novel applications in high-field physics, laser–matter interactions, future energy solutions and beyond.

In the pursuit of efficient optimization of expensive-to-evaluate systems, this paper investigates a novel approach to Bayesian multi-objective and multi-fidelity (MOMF) optimization. Traditional optimization methods, while effective, often encounter prohibitively high costs in multi-dimensional optimizations of one or more objectives. Multi-fidelity approaches offer potential remedies by utilizing multiple, less costly information sources, such as low-resolution approximations in numerical simulations. However, integrating these two strategies presents a significant challenge. We propose the innovative use of a trust metric to facilitate the joint optimization of multiple objectives and data sources. Our methodology introduces a modified multi-objective (MO) optimization policy incorporating the trust gain per evaluation cost as one of the objectives of a Pareto optimization problem. This modification enables simultaneous MOMF optimization, which proves effective in establishing the Pareto set and front at a fraction of the cost. Two specific methods of MOMF optimization are presented and compared: a holistic approach selecting both the input parameters and the fidelity parameter jointly, and a sequential approach for benchmarking. Through benchmarks on synthetic test functions, our novel approach is shown to yield significant cost reductions-up to an order of magnitude compared to pure MO optimization. Furthermore, we find that joint optimization of the trust and objective domains outperforms sequentially addressing them. We validate our findings with the specific use case of optimizing particle-in-cell simulations of laser-plasma acceleration, highlighting the practical potential of our method in the Pareto optimization of highly expensive black-box functions. Implementation of the methods in existing Bayesian optimization frameworks is straightforward, with immediate extensions e.g. to batch optimization possible. Given their ability to handle various continuous or discrete fidelity dimensions, these techniques have wide-ranging applicability in tackling simulation challenges across various scientific computing fields such as plasma physics and fluid dynamics.

Optimization of accelerator performance parameters is limited by numerous trade-offs, and finding the appropriate balance between optimization goals for an unknown system is challenging to achieve. Here, we show that multiobjective Bayesian optimization can map the solution space of a laser wakefield accelerator (LWFA) in a very sample-efficient way. We observe that there exists a wide range of Pareto-optimal solutions that trade beam energy versus charge at similar laser-to-beam efficiency. Moreover, many applications such as light sources require particle beams at certain target energies. We demonstrate accurate energy tuning of the LWFA from 150 to 400 MeV via the simultaneous adjustment of eight parameters. To further advance this use case, we propose an inverse model that allows a user to specify desired beam parameters. Trained on the forward Gaussian process model, the inverse model generates input parameter value ranges within which the desired setting is likely to be reached. The method reveals different strategies for accelerator tuning and is expected to drastically facilitate the operation of LWFAs in the near future. Published by the American Physical Society 2024

Beam parameter optimization in accelerators involves multiple, sometimes competing objectives. Condensing these individual objectives into a single figure of merit unavoidably results in a bias towards particular outcomes, in absence of prior knowledge often in a non-desired way. Finding an optimal objective definition then requires operators to iterate over many possible objective weights and definitions, a process that can take many times longer than the optimization itself. A more versatile approach is multi-objective optimization, which establishes the trade-off curve or Pareto front between objectives. Here we present the first results on multi-objective Bayesian optimization of a simulated laser-plasma accelerator. We find that multi-objective optimization reaches comparable performance to its single-objective counterparts while allowing for instant evaluation of entirely new objectives. This dramatically reduces the time required to find appropriate objective definitions for new problems. Additionally, our multi-objective, multi-fidelity method reduces the time required for an optimization run by an order of magnitude. It does so by dynamically choosing simulation resolution and box size, requiring fewer slow and expensive simulations as it learns about the Pareto-optimal solutions from fast low-resolution runs. The techniques demonstrated in this paper can easily be translated into many different computational and experimental use cases beyond accelerator optimization.

Abstract 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, we find that a state-of-the-art object detection architecture can very efficiently be fine-tuned to work on a variety of object detection tasks in a high-power laser laboratory. In this paper, three exemplary applications are presented. We show that the plasma waves in a laser–plasma accelerator can be detected and located on the optical shadowgrams. The plasma wavelength and plasma density are estimated accordingly. Furthermore, we present the detection of all the peaks in an electron energy spectrum of the accelerated electron beam, and the beam charge of each peak is estimated accordingly. Lastly, we demonstrate the detection of optical damage in a high-power laser system. The reliability of the object detector is demonstrated over 1000 laser shots in each application. Our study shows that deep object detection networks are suitable to assist online and offline experimental analysis, even with small training sets. We believe that the presented methodology is adaptable yet robust, and we encourage further applications in Hz-level or kHz-level high-power laser facilities regarding the control and diagnostic tools, especially for those involving image data.

Optimization of accelerator performance parameters is limited by numerous trade-offs and finding the appropriate balance between optimization goals for an unknown system is challenging to achieve. Here we show that multi-objective Bayesian optimization can map the solution space of a laser wakefield accelerator in a very sample-efficient way. Using a Gaussian mixture model, we isolate contributions related to an electron bunch at a certain energy and we observe that there exists a wide range of Pareto-optimal solutions that trade beam energy versus charge at similar laser-to-beam efficiency. However, many applications such as light sources require particle beams at a certain target energy. Once such a constraint is introduced we observe a direct trade-off between energy spread and accelerator efficiency. We furthermore demonstrate how specific solutions can be exploited using \emph{a posteriori} scalarization of the objectives, thereby efficiently splitting the exploration and exploitation phases.

Plasma wakefield accelerators can be driven either by intense laser pulses (LWFA) or by intense particle beams (PWFA). A third approach that combines the complementary advantages of both types of plasma wakefield accelerator has been established with increasing success over the last decade and is called hybrid LWFA→PWFA. Essentially, a compact LWFA is exploited to produce an energetic, high-current electron beam as a driver for a subsequent PWFA stage, which, in turn, is exploited for phase-constant, inherently laser-synchronized, quasi-static acceleration over extended acceleration lengths. The sum is greater than its parts: the approach not only provides a compact, cost-effective alternative to linac-driven PWFA for exploitation of PWFA and its advantages for acceleration and high-brightness beam generation, but extends the parameter range accessible for PWFA and, through the added benefit of co-location of inherently synchronized laser pulses, enables high-precision pump/probing, injection, seeding and unique experimental constellations, e.g., for beam coordination and collision experiments. We report on the accelerating progress of the approach achieved in a series of collaborative experiments and discuss future prospects and potential impact.

The Centre for Advanced Laser Applications in Garching, Germany, is home to the ATLAS-3000 multi-petawatt laser, dedicated to research on laser particle acceleration and its applications. A control system based on Tango Controls is implemented for both the laser and four experimental areas. The device server approach features high modularity, which, in addition to the hardware control, enables a quick extension of the system and allows for automated data acquisition of the laser parameters and experimental data for each laser shot. In this paper we present an overview of our implementation of the control system, as well as our advances in terms of experimental operation, online supervision and data processing. We also give an outlook on advanced experimental supervision and online data evaluation - where the data can be processed in a pipeline - which is being developed on the basis of this infrastructure.

Knowledge of spatio-temporal couplings such as pulse-front tilt or curvature is important to determine the focused intensity of high-power lasers. Common techniques to diagnose these couplings are either qualitative or require hundreds of measurements. Here we present both a new algorithm for retrieving spatio-temporal couplings, as well as novel experimental implementations. Our method is based on the expression of the spatio-spectral phase in terms of a Zernike-Taylor basis, allowing us to directly quantify the coefficients for common spatio-temporal couplings. We take advantage of this method to perform quantitative measurements using a simple experimental setup, consisting of different bandpass filters in front of a Shack-Hartmann wavefront sensor. This fast acquisition of laser couplings using narrowband filters, abbreviated FALCON, is easy and cheap to implement in existing facilities. To this end, we present a measurement of spatio-temporal couplings at the ATLAS-3000 petawatt laser using our technique.

In recent years, significant progress has been made in laser wakefield acceleration (LWFA), both regarding the increase in electron energy, charge and stability as well as the reduction of bandwidth of electron bunches. Simultaneous optimization of these parameters is, however, still the subject of an ongoing effort in the community to reach sufficient beam quality for next generation's compact accelerators. In this report, we show the design of slit-shaped gas nozzles providing centimeter-long supersonic gas jets that can be used as targets for the acceleration of electrons to the GeV regime. In LWFA experiments at the Centre for Advanced Laser Applications, we show that electron bunches are accelerated to 1GeV using these nozzles. The electron bunches were injected into the laser wakefield via a laser-machined density down-ramp using hydrodynamic optical-field-ionization and subsequent plasma expansion on a ns-timescale. This injection method provides highly controllable quasi-monoenergetic electron beams with high charge around 100pC , low divergence of 0.5mrad, and a relatively small energy spread of around 10% at 1GeV . In contrast to capillaries and gas cells, the scheme allows full plasma access for injection, probing or guiding in order to further improve the energy and quality of LWFA beams.

We report on experimental investigations of plasma wave structures in a plasma wakefield acceleration (PWFA) stage which is driven by electron beams from a preceding laser plasma accelerator. Femtosecond optical probing is utilized to allow for direct visualization of the plasma dynamics inside the target. We compare two regimes in which the driver propagates either through an initially neutral gas, or a preformed plasma. In the first case, plasma waves are observed that quickly damp after a few oscillations and are located within a narrow plasma channel ionized by the driver, having about the same transverse size as the plasma wakefield cavities. In contrast, for the latter robust cavities are recorded sustained over many periods. Furthermore, here an elongation of the first cavity is measured, which becomes stronger with increasing driver beam charge. Since the cavity length is linked to the maximum accelerating field strength, this elongation implies an increased field strength. This observation is supported by 3D particle-in-cell simulations performed with PIConGPU. This work can be extended for the investigation of driver depletion by probing at different propagation distances inside the plasma, which is essential for the development of high energy efficiency PWFAs.

Plants exhibit a huge variety of biologically functional surfaces with rather unique characteristics. Analysis and mimicking of the surface leaf of the lotus plant have recently been used to develop biomimetic water repellency surfaces. A functional ceramic coating with the "lotus leaf effect" is also an interesting option in aggressive environments to mitigate corrosion by natural silicate melts. Here, inspired by natural superhydrophobic surfaces, and through the application of femtosecond laser pulses, a ceramic surface is fabricated with a hierarchical nano/microstructure. This ceramic surface exhibits the combined effects of super "silicate" phobicity at high temperature and superhydrophobicity at room temperature. The capability of the laser-irradiated TBC is attributed to resist wetting by both silicate melt and water to its lotus-leaf-like dual-scale microstructure, emulating in particular the existence of nanoparticles. These findings may be an important step toward next-generation jet engines with greatly reduced vulnerability to environmental siliceous debris and mitigate lunar or Mars regolith dust sticking to the landing vehicle in the rocket engine exhaust plume and anti-slagging in coal-fired power plants or further industries.

We present experimental results on a plasma wakefield accelerator (PWFA) driven by high-current electron beams from a laser wakefield accelerator (LWFA). In this staged setup stable and high-quality (low-divergence and low energy spread) electron beams are generated at an optically generated hydro-dynamic shock in the PWFA. The energy stability of the beams produced by that arrangement in the PWFA stage is comparable to both single-stage laser accelerators and plasma wakefield accelerators driven by conventional accelerators. Simulations support that the intrinsic insensitivity of PWFAs to driver energy fluctuations can be exploited to overcome stability limitations of state-of-the-art laser wakefield accelerators when adding a PWFA stage. Furthermore, we demonstrate the generation of electron bunches with energy spread and divergence superior to single-stage LWFAs, resulting in bunches with dense phase space and an angular-spectral charge density beyond the initial drive beam parameters. These results unambiguously show that staged LWFA-PWFA can help to tailor the electron-beam quality for certain applications and to reduce the influence of fluctuating laser drivers on the electron-beam stability. This encourages further development of this new class of staged wakefield acceleration as a viable scheme toward compact, high-quality electron beam sources.

Figure 20.1 was not correct in the published article. The original article has been corrected. The published apologizes for the inconvenience.

We spectrally broaden 1.3 ps pulses and show compressibility to 37 fs for energies >100 mJ at a repetition rate of 5 kHz by using a first order Laguerre-Gaussian mode in an argon-filled multipass cell.

The first-order helical Laguerre-Gaussian mode (also called donut mode) is used to improve the energy throughput of nonlinear spectral broadening in gas-filled multipass cells. The method proposed in this Letter enables, for the first time to the best of our knowledge, the nonlinear spectral broadening of pulses with energies beyond 100 mJ and is suitable for an average power of more than 500 W while conserving an excellent spatio-spectral homogeneity of ∼98% and a Gaussian-like focus profile. Additionally compressibility from 1.3 ps to 37 fs is demonstrated.

The interaction of light with the quantum-vacuum is predicted to give rise to some of the most fundamental and exotic processes in modern physics, which remain untested in the laboratory to date. Electron–positron pair production from a pure vacuum target, which has yet to be observed experimentally, is possibly the most iconic. The advent of ultra-intense lasers and laser accelerated GeV electron beams provide an ideal platform for the experimental realisation. Collisions of high energy γ-ray photons derived from the GeV electrons and intense laser fields result in detectable pair production rates at field strengths that approach and exceed the Schwinger limit in the centre-of-momentum frame. A detailed experiment has been designed to be implemented at the ATLAS laser at the centre of advanced laser applications. We show full calculations of the expected backgrounds and beam parameters which suggest that single pair events can be reliably generated and detected.

Plasma wakefield accelerators are capable of sustaining gigavolt-per-centimeter accelerating fields, surpassing the electric breakdown threshold in state-of-the-art accelerator modules by 3-4 orders of magnitude. Beam-driven wakefields offer particularly attractive conditions for the generation and acceleration of high-quality beams. However, this scheme relies on kilometer-scale accelerators. Here, we report on the demonstration of a millimeter-scale plasma accelerator powered by laser-accelerated electron beams. We showcase the acceleration of electron beams to 128 MeV, consistent with simulations exhibiting accelerating gradients exceeding 100 GV m −1 . This miniaturized accelerator is further explored by employing a controlled pair of drive and witness electron bunches, where a fraction of the driver energy is transferred to the accelerated witness through the plasma. Such a hybrid approach allows fundamental studies of beam-driven plasma accelerator concepts at widely accessible high-power laser facilities. It is anticipated to provide compact sources of energetic high-brightness electron beams for quality-demanding applications such as free-electron lasers.