Sergey G. Rykovanov

We derive compact analytical formulas for the spectrum of nonlinear Compton scattering in a finite plane-wave pulse with a smooth temporal envelope. The strong-field QED probability is reduced to finite-pulse phase integrals, which are evaluated asymptotically for multicycle pulses with a broad class of smooth envelopes. We use the uniform approximation to remove the caustic divergences that appear at the nonlinear edges of broadened harmonics. Away from the caustics, it reduces to the standard saddle-point result. The behavior near the linear edge is further improved by an envelope-corrected saddle-point approximation. The approach retains the harmonic substructure in the spectral-angular region carrying the dominant part of the emitted radiation. The locally monochromatic approximation is recovered by averaging the finite-pulse interference. Within their asymptotic domain of applicability, the resulting formulas agree with direct numerical calculations and can be used to evaluate spectra from an electron beam.

Attosecond coherent synchrotron emission from relativistic plasma surfaces is a promising route to intense UV and X-ray bursts that can be transmitted through solid-density targets without external spectral filtering. In this work, we demonstrate that the same overdense plasma responsible for attosecond radiation generation also imposes a strong dispersion limit on the usable target thickness. One- and two-dimensional particle-in-cell simulations combined with a simple wave-propagation model are employed to quantify the dispersion-induced temporal broadening and the chirp of transmitted attosecond pulses. Compact scaling laws are derived as functions of plasma density, target thickness, and effective harmonic order and are formulated as an accumulated-dispersion criterion that determines the conditions under which the attosecond temporal structure is lost. These results provide practical design rules for plasma-based attosecond sources and plasma-optics elements, such as attosecond plasma lenses, by defining the maximum target thickness compatible with sub-femtosecond pulse delivery.

An enhanced Bayesian optimization method, named History-Aware Dynamic Bayesian Optimization (HAD-BO), is proposed and applied to optimize the ellipticity in laser-driven plasma surface high-harmonic generation (SHHG). While Bayesian optimization is a cornerstone of black-box function optimization, established methods like the Gaussian Process Hedge (GP-Hedge) algorithm often fail to effectively leverage historical performance when selecting acquisition functions. This results in suboptimal strategies and unstable convergence. To address this, HAD-BO introduces a global, time-series-based dynamic adjustment mechanism that integrates historical gain updates with a weight decay factor, significantly improving the flexibility and adaptability of acquisition selection. We first validate HAD-BO’s effectiveness through numerical experiments on classical benchmark functions and then demonstrate its performance in a three-dimensional parameter optimization of SHHG ellipticity. The results indicate that HAD-BO not only accelerates convergence but also achieves superior stability in complex and multi-dimensional systems. This work provides a novel and efficient optimization tool for complex physical systems.

We propose a method to generate isolated and circularly polarized (CP) attosecond pulses through the interaction of a relativistic linearly polarized laser pulse with magnetized subcritical density plasma. When the strength of the magnetic field is comparable with the normalized laser intensity, the left-handed CP component of the laser can easily transmit through the plasma while the right-handed CP one is almost reflected, which is named the extreme birefringence effect (EBE). EBE serves as a handedness splitter and time-domain gate, reflecting an intense few-cycle CP laser pulse. Along with EBE, a high-density and backward-moving relativistic electron sheet is formed due to the strong electrostatic separation force, further compressing the few-cycle CP laser to a bright and isolated CP attosecond pulse. This work therefore provides a novel approach to generating single attosecond pulses that is directly compatible with existing laser systems operating with multi-cycle pulses and more moderate contrast ratios.

Numerical solutions of partial differential equations (PDEs) on regular domains provide simplicity as we can rely on the structure of the space. We investigate a novel neural network (NN) - based approach to generate 2-dimensional body-fitted curvilinear coordinate systems (BFCs) that allow to stay on regular grids even when the complex geometry is considered. We describe a feed-forward neural network (FNN) as a geometric transformation that can represent a diffeomorphism under certain constraints and approximations, followed by the ways of training it to create BFCs. We show that the optimization system is similar to a physics informed neural network (PINN) based solution of Winslow equations. Unlike in classical BFC generation, FNN provides a differentiable mapping between spaces, and all the Jacobian matrices may be obtained exactly at any given point. Also, it allows to change an interior nodes distribution without the need of recreating the whole mapping.