Laser wakefield accelerators (LWFAs) provide extremely large accelerating gradients for compact electron accelerators and photon sources but are limited by dephasing, where trapped electrons outrun the accelerating phase of the wakefield. Flying-focus pulses can eliminate dephasing by driving a wake at the vacuum speed of light, but these pulses involve tradeoffs such as varying spot size, long duration, or large plasma volume. Here we show that a spatiotemporally structured laser pulse propagating in a plasma waveguide can drive a wakefield at the vacuum speed of light while maintaining a constant spot size and ultrashort duration. The pulse is formed by superposing plasma-waveguide modes with appropriately selected frequencies. Compared with flying-focus approaches, the waveguide substantially reduces the required plasma volume. Scaling laws and quasi-3D particle-in-cell simulations show that the single-stage energy gain increases linearly with the number of modes used to construct the pulse, enabling larger energy gains or shorter stages than standard LWFA.

Modern stellarators are typically designed by optimizing the shape of the plasma boundary surface, with the parameters taken to be Fourier amplitudes. Many promising optimization algorithms such as Bayesian methods require bound constraints on the parameters and are most efficient when each parameter is scaled similarly to the others. With the typical Fourier parameterization, it is unclear how to set these bounds: wide constraints lead to self-intersecting boundaries and frequent failures of the MHD equilibrium calculation, while tight bound constraints limit expressiveness. To address these issues, here we propose two new parameter spaces for stellarator optimization. Both begin with a dataset of existing stellarator boundaries. In the first approach, a quantile transformation is applied to each Fourier degree of freedom, mapping the data distribution to a uniform distribution on the unit interval. In the second approach, principal component analysis (PCA) is applied to points on the boundaries, followed by a quantile transformation. For both approaches, the transformed variables become the degrees of freedom, naturally bounded to [0, 1]. The PCA method has the additional benefit of dimensionality reduction, with high expressiveness for a small number of parameters. The methods are demonstrated via Bayesian optimization for good alpha-particle confinement with guiding-center tracing inside the optimization loop, using asynchronous parallelization. These optimizations yield stellarator configurations with excellent fast-particle confinement in fields that can be far from quasisymmetric or quasi-isodynamic.

In this work, we investigate the impact of fusion-born alpha particles on core turbulence and transport in the ARC tokamak fusion power plant using linear and nonlinear gyrokinetic CGYRO simulations. A significant reduction in ion-scale turbulent heat and particle fluxes is observed in the inner core (r/a $\leq$ 0.5), which is associated with multiscale interactions between fast ion-destabilized modes, zonal flows, and the background turbulence. A nonlinear upshift in the ITG critical gradient is observed in the simulations with fast alphas compared to those with artificially thermalized alphas. The turbulence reduction is found to scale beneficially with alpha particle density and plasma $β_e$, and the radial extent of the turbulence suppression is limited to the volume containing a significant density of fast particles. The suitability of local gyrokinetics and potential impacts of fast ion effects on fusion performance are discussed.

We demonstrate that caustic microlensing occurring in a liquid jet efficiently drives linear, nonlinear, and high-energy-density phenomena. In the linear regime, caustics provide localized focusing, distinct from external high-NA optics. In the nonlinear regime, they enhance the input field at the liquid-air interface and boost surface-sensitive processes. In the high-energy-density domain, caustic-driven localized laser absorption generates gigapascal shocks using microjoule femtosecond pulses, with scalability up to repetition rates of 0.2 MHz. Caustic-driven fluidic microlensing offers opportunities for surface nonlinear optics, ultrafast science, and high-energy-density physics.

By a detailed comparison of leaky magnetohydrodynamic waves in coronal magnetic flux tubes with leaky electromagnetic waves in dielectric media it is shown that the latter kind may be called quasi-normal modes, since they can be regularised by a normalisation which systematically cuts off the contribution of the external homogeneous region, whereas such a possibility is forbidden for the former kind by the conservation of magnetic flux. Consequently, leaky magnetohydrodynamic waves cannot be systematically applied to coronal seismology, i.e. to the inverse spectral problem of determining the different equilibrium distributions of the fields by comparing the spectra they produce with the observed ones.

When exact magnetic surfaces are assumed to exist, the gyrokinetic theory of microturbulence gives the same radial transport for ions and electrons. But, exact magnetic surfaces do not exist in the presence of what is called electrostatic microturbulence. When the plasma pressure is non-zero, a turbulent electric potential is accompanied by a turbulent magnetic field, which splits the rational magnetic surfaces with which it resonates. If the magnetic field is assumed to have an ideal topology-conserving evolution, delta function current densities arise on resonant surfaces. The singularity of the current density allows islands to open quickly, but there is no singularity that allows a rapid closure. Islands remain and do not flutter into and out of existence. A relative rotation of the electron fluid in neighboring island chains produces a non-dissipative force that can lock the islands together and produce a non-ambipolar transport. At sufficient plasma pressure, the islands associated with different resonant rational surfaces can overlap. When this occurs some magnetic field lines will cross the entire radial region occupied by overlapping islands. The effect on the electron fluid is to create a viscosity-like force, which is dissipative and tends to remove gradients in the electron rotation. This also produces a non-ambipolar transport. Under many assumptions, the island locking force is larger than the viscosity-like force.

The requirement for large-scale global simulations of plasma is an ongoing challenge in both space and laboratory plasma physics. Any simulation based on a fluid model inherently requires a closure relation for the high order plasma moments. This review compiles and analyses the recent surge of machine learning approaches developing improved plasma closure models capable of capturing kinetic phenomena within plasma fluid models. We survey two methodological families: neural-network surrogates (from multilayer perceptrons to Fourier neural operators, the latter recently reproducing both linear and non-linear Landau damping online within a fluid solver) and equation-discovery methods such as sparse regression; and organise the studies by whether they are tested offline against reference data or online within a time-evolving solver. We outline the challenges associated with machine-learning closures, including off-diagonal pressure-tensor accuracy, generalisation beyond the training distribution, and stable integration into large-scale simulations, and the directions future research might take to address them.

Radiation reaction cooling plays an important role in describing the extreme plasma conditions found in the magnetospheres of astrophysical compact objects. Strong electromagnetic fields, characteristic of these environments, can trigger the development of anisotropic ring-shaped plasma distributions with inverted Landau populations in momentum space. In this work, we present the first systematic investigation of this mechanism in realistic astrophysical configurations, by accounting for how non-uniform electromagnetic field geometries and general-relativistic effects modify the phase-space dynamics of radiatively cooled plasmas. We demonstrate analytically that drift velocities favour the formation of spiral-shaped momentum distributions that still display inverted Landau populations, and estimate the minimum and maximum plasma injection distances required for inverted momentum distributions to be able to power the emission of coherent radiation through kinetic instabilities. From numerical simulations, we conclude that curved spacetime increases the gradient of the distribution function responsible for the development of kinetic instabilities, and prolongs the persistence of the inverted momentum structure relative to flat spacetime, confirming that realistic astrophysical conditions preserve and enhance the conditions necessary for synchrotron-powered emission of coherent radiation to occur.

Identification of the particle interaction potential is a challenging and important task in dusty plasma, colloids, and smart materials as it allows the characterization of structure formation and helps predict phase transitions. With the advent of machine learning methods, this interaction can be extracted from particle position data, leading to a generalizable expression which is applicable in different systems. Methods such as sparse regression aim to provide a physically interpretable model that can generalize well, while avoiding unnecessary complexity due to overfitting. In this work, we present the use of the Sparse Identification of Nonlinear Dynamics (SINDy) with the weak formulation to learn equations of motion for noisy data from simple simulations of two dust particles interacting with a Yukawa (shielded Coulomb) potential. The application of these methods to experimental dusty plasma data is discussed, particularly in the case of simulation data and glass box experiments in RF discharge gravity environments and DC discharge microgravity environments, such as the Plasmakristall-4 (PK-4) experiment.

We derive a generalized Beth-Uhlenbeck formula for the entropy of a dense fermion system with strong two-particle correlations, including scattering states and bound states. We work within the $Φ-$derivable approach to the thermodynamic potential. The formula takes the form of an energy-momentum integral over a statistical distribution function times a unique spectral density. In the near mass-shell limit, the spectral density reduces, contrary to naïve expectations, not to a Lorentzian but rather to a "squared Lorentzian" shape. The relation of the Beth-Uhlenbeck formula to the $Φ$-derivable approach is exact at the two-loop level for $Φ$. The formalism we develop, which extends the Beth-Uhlenbeck approach beyond the low-density limit, includes Mott dissociation of bound states, in accordance with Levinson's theorem, and the self-consistent back reaction of correlations in the fermion propagation. We discuss applications to further systems, such as quark matter and nuclear matter.

We report a fully kinetic, quantum study of Kinetic Electrostatic Electron Nonlinear (KEEN) waves, showing that quantum diffraction systematically erodes the classical trapping mechanism, narrow harmonic locking to the fundamental, and hasten post-drive decay. Electrons are evolved with a second-order Strang-split 1D1V Wigner-Poisson solver that couples conservative semi-Lagrangian WENO advection to an analytic Fourier space update for the non-local Wigner term, while ions remain classical. Short, frequency-tuned ponderomotive pulses drive KEEN formation in a uniform Maxwellian plasma; as the dimensionless quantum parameter H rises from the classical limit to values relevant to warm-dense matter, doped semiconductors, and 2D electron systems, the drive threshold increases, higher harmonics are damped, trapped electron vortices diffuse, and the subplasma electrostatic energy relaxes to a lower stationary level, as confirmed by continuous wavelet analysis. These microscopic changes carry macroscopic weight. Ignition-scale capsules now compress matter to regimes where the electron de Broglie wavelength rivals the Debye length, making classical kinetic descriptions insufficient. By extending KEEN physics into this quantum domain, our results offer a potential diagnostic of nonequilibrium electron dynamics for next-generation inertial-confinement designs and high-energy-density platforms, indicating that predictive fusion modeling may benefit from the integration of kinetic fidelity with quantum effects.