Paper

Experiments using the OMEGA EP laser system were performed to study collisionless shock acceleration of ions driven by the interaction of a relativistically intense laser pulse with underdense plasma. The energy spectrum of accelerated ions in the direction transverse to laser propagation is measured to have several narrow-band peaks which are quasi-monoenergetic with a typical energy bandwidth of 3%. In deuterium plasmas, these ions generate a significant number of fast fusion neutrons. Particle-in-cell simulations confirm that these ions were accelerated by the interaction of transverse shocks and that the appearance of quasi-monoenergetic spectral features depends on the growth of an ion-electron two-stream instability during the interaction.

Strong multi-kilotesla magnetic fields have various applications in high-energy density science and laboratory astrophysics, but they are not readily available. In our previous work [Y. Shi et al., Phys. Rev. Lett. 130, 155101 (2023)], we developed a novel approach for generating such fields using multiple conventional laser beams with a twist in the pointing direction. This method is particularly well-suited for multi-kilojoule petawatt-class laser systems like SG-II UP, which are designed with multiple linearly polarized beamlets. Utilizing three-dimensional kinetic particle-in-cell simulations, we examine critical factors for a proof-of-principle experiment, such as laser polarization, relative pulse delay, phase offset, pointing stability, and target configuration, and their impact on magnetic field generation. Our general conclusion is that the approach is very robust and can be realized under a wide range of laser parameters and plasma conditions. We also provide an in-depth analysis of the axial magnetic field configuration, azimuthal electron current, and electron and ion orbital angular momentum densities. Supported by a simple model, our analysis shows that the axial magnetic field decays due to the expansion of hot electrons.

Motivated by experiments employing ps-long, kilojoule laser pulses, we examined x-ray emission in a finite length underdense plasma irradiated by such a pulse using two dimensional particle-in-cell simulations. We found that, in addition to the expected forward emission, the plasma also efficiently emits in the backward direction. Our simulations reveal that the backward emission occurs when the laser exits the plasma. The longitudinal plasma electric field generated by the laser at the density down-ramp turns around some of the laser-accelerated electrons and re-accelerates them in the backward direction. As the electrons collide with the laser, they emit hard x-rays. The energy conversion efficiency is comparable to that for the forward emission, but the effective source size is smaller. We show that the ps laser duration is required for achieving a spatial overlap between the laser and the backward energetic electrons. At peak laser intensity of 1.4 × 10²⁰ W/cm², backward emitted photons (energies above 100 keV and 10^◦ divergence angle) account for 2 × 10⁻⁵ of the incident laser energy. This conversion efficiency is three times higher than that for similarly selected forward emitted photons. The source size of the backward photons (5 µm) is three times smaller than the source size of the forward photons.

High-intensity laser-plasma interactions have been shown to generate dense populations of gamma-rays, so these interactions are expected to generate electron-positron pairs via binary photon collisions (linear Breit-Wheeler process). However, particle-in-cell (PIC) codes that are used for studies of laser plasma interactions are not yet equipped to compute the yield from the linear Breit-Wheeler process. We present a post-processing algorithm that allows one to quickly calculate the yield of the linear Breit-Wheeler process inside a photon-emitting plasma using PIC simulation data. The algorithm splits the PIC computational domain into smaller sub-domains whose shape and size are determined based on a specific problem. The photons emitted within each sub-domain are grouped into collimated mono-energetic beams called beamlets. The algorithm computes the yield by evaluating beamlet-beamlet collisions without the spatial integration over the interaction region. Presented benchmarking shows that the computational time is reduced by two orders of magnitude compared to the direct approach that involves the spatial integration, while the resulting error in the total yield remains around 10%. We also show how the algorithm can be leveraged to compute the density of the pair-producing events and the positron momentum distribution at the time of their creation. The ability of our algorithm to quickly compute the pair yield makes it a useful tool for studies of high-intensity laser-plasma interactions. It can also be useful for testing future implementations of the linear Breit-Wheeler process into plasma simulation codes.

Strong laser-driven magnetic fields are crucial for high-energy-density physics and laboratory astrophysics research, but generation of axial multikilotesla fields remains a challenge. The difficulty comes from the inability of a conventional linearly polarized laser beam to induce the required azimuthal current or, equivalently, angular momentum (AM). We show that several laser beams can overcome this difficulty. Our three-dimensional kinetic simulations demonstrate that a twist in their pointing directions enables them to carry orbital AM and transfer it to the plasma, thus generating a hot electron population carrying AM needed to sustain the magnetic field. The resulting multikilotesla field occupies a volume that is tens of thousands of cubic microns and it persists on a picosecond timescale. The mechanism can be realized for a wide range of laser intensities and pulse durations. Our scheme is well suited for implementation using multikilojoule petawatt-class lasers, because, by design, they have multiple beamlets and because the scheme requires only linear polarization.

We discovered a simple regime where a near-critical plasma irradiated by a laser of experimentally available intensity can self-organize to produce positrons and accelerate them to ultrarelativistic energies. The laser pulse piles up electrons at its leading edge, producing a strong longitudinal plasma electric field. The field creates a moving gamma-ray collider that generates positrons via the linear Breit-Wheeler process— annihilation of two gamma rays into an electron-positron pair. At the same time, the plasma field, rather than the laser, serves as an accelerator for the positrons. The discovery of positron acceleration was enabled by a first-of-its-kind kinetic simulation that generates pairs via photon-photon collisions. Using available laser intensities of 10²² W/cm², the discovered regime can generate a GeV positron beam with a divergence angle of around 10° and a total charge of 0.1 pC. The result paves the way to experimental observation of the linear Breit-Wheeler process and to applications requiring positron beams.

The interaction of high-intensity lasers with plasma is predicted to produce extreme quasi-static magnetic fields with magnitudes approach- ing Megatesla levels. In relativistically transparent plasmas, these fields can enhance direct laser acceleration and allow efficient gamma-ray emission by accelerated electrons. However, due to the so-called magnetic suppression effect, the magnetic field can also affect radiating electron trajectories and, thus, reduce the emission probability of the bremsstrahlung. This is the first study to examine the bremsstrahlung suppression mechanism in the context of high-intensity laser–plasma interactions. Our paper describes a new module that integrates the suppression effect into the standard bremsstrahlung module of the EPOCH particle-in-cell code by considering the impact of magnetic fields and extending the analysis to electric fields. We also investigate this suppressing mechanism’s effect on the emitting electron’s dynamics. Our findings show that this mechanism not only suppresses low-energy emissions but also has an impact on the dynamics of the radiating electrons.

Intense laser fields interact very differently with micrometric rough surfaces than with flat objects. The interaction features high laser energy absorption and increased emission of MeV electrons, ions, and of hard x‐rays. In this work, we irradiated isolated, translationally‐symmetric objects in the form of micrometric Au bars. The interaction resulted in the emission of two forward‐directed electron jets having a small opening angle, a narrow energy spread in the MeV range, and a positive angle to energy correlation. Our numerical simulations show that following ionization, those electrons that are pulled into vacuum near the object’s edge, remain in‐phase with the laser pulse for long enough so that the Lorentz force they experience drive them around the object’s edge. After these electrons pass the object, they form attosecond duration bunches and interact with the laser field over large distances in vacuum in confined volumes that trap and accelerate them within a narrow range of momentum. The selectivity in energy of the interaction, its directionality, and the preservation of the attosecond duration of the electron bunches over large distances, offer new means for designing future laser‐based light sources.

Low-intensity light beams carrying orbital angular momentum (OAM), commonly known as vortex beams, have garnered significant attention due to promising applications in areas ranging from optical trapping to communication. In recent years, there has been a surge in global research exploring the potential of high-intensity vortex laser beams and specifically their interactions with plasmas. This paper provides a comprehensive review of recent advances in this area. Compared with conventional laser beams, intense vortex beams exhibit unique properties such as twisted phase fronts, OAM delivery, hollow intensity distribution, and spatially isolated longitudinal fields. These distinct characteristics give rise to a multitude of rich phenomena, profoundly influencing laser-plasma interactions and offering diverse applications. The paper also discusses future prospects and identifies promising general research areas involving vortex beams. These areas include low-divergence particle acceleration, instability suppression, high-energy photon delivery with OAM, and the generation of strong magnetic fields. With growing scientific interest and application potential, the study of intense vortex lasers is poised for rapid development in the coming years.

Fast analysis of collective Thomson scattering ion acoustic wave features using a deep convolutional neural network model is presented. The network was trained from spectra to predict the plasma parameters, including ion velocities, population fractions, and ion and electron temperatures. A fully kinetic particle-in-cell simulation was used to model a laboratory astrophysics experiment and simulate a diagnostic image of the ion acoustic wave feature. Network predictions were compared with Bayesian inference of the plasma model parameters for both the simulated and experimentally measured images. Both approaches were fairly accurate predicting the simulated image and the network predictions matched a good portion of the Bayesian results for the experimentally measured image. The Bayesian approach is more robust to noise and motivates future work to train deep learning models with realistic noise. The advantage of the deep learning model is making thousands of predictions in a few hundred milliseconds, compared to a few seconds to minutes per prediction for the optimization and Bayesian approaches presented here. The results demonstrate promising capabilities of deep learning models to analyze Thomson data orders of magnitude faster than conventional methods when using the neural network for standalone analysis. If more rigorous analysis is needed, neural network predictions can be used to quickly initialize other optimization methods and increase chances of success. This is especially useful when the dataset becomes very large or highly dimensional and manually refining initial conditions for the entire dataset are no longer tractable.