Temporal confinement and enhancement of high-order harmonic emission with a synthesized laser field

We demonstrated that a synthesized laser field consisting of an intense long (45 fs, multi-optical-cycle) laser pulse and a weak short (7 fs, few-optical-cycle) laser pulse can control the electron dynamics and high-order harmonic generation in argon, and generate extreme ultraviolet supercontinuum towards the production of a single strong attosecond pulse. The long pulse offers a large amplitude field, and the short pulse creates a temporally narrow enhancement of the laser field and a gate for the highest energy harmonic emission. This scheme paves the way to generate intense isolated attosecond pulses with strong multi-optical-cycle laser pulses.

Phase-matching control of high-order harmonic generation in a two-color laser field

The phase-matching condition of high-order harmonic generation driven by intense few-cycle pulses could be controlled by adding second-harmonic pulses to change the ionization fraction of the gaseous medium. The harmonic generation efficiency could be improved by moving the phase-matching point with an all-optical control of the ionization fraction or a proper change of the confocal parameter. A specific order of harmonics could be easily controlled to reach phase matching at a fixed higher gas pressure by adding second-harmonic pulses with a suitable intensity. Such an all-optical phase-matching control was demonstrated to be dependent upon the temporal delay between the fundamental-wave and second harmonic pulses.

Efficient methods for stochastic optimal control

The Hamilton Jacobi Bellman (HJB) equation is central to stochastic optimal control (SOC) theory, yielding the optimal solution to general problems specified by known dynamics and a specified cost functional. Given the assumption of quadratic cost on the control input, it is well known that the HJB reduces to a particular partial differential equation (PDE). While powerful, this reduction is not commonly used as the PDE is of second order, is nonlinear, and examples exist where the problem may not have a solution in a classical sense. Furthermore, each state of the system appears as another dimension of the PDE, giving rise to the curse of dimensionality. Since the number of degrees of freedom required to solve the optimal control problem grows exponentially with dimension, the problem becomes intractable for systems with all but modest dimension.

In the last decade researchers have found that under certain, fairly non-restrictive structural assumptions, the HJB may be transformed into a linear PDE, with an interesting analogue in the discretized domain of Markov Decision Processes (MDP). The work presented in this thesis uses the linearity of this particular form of the HJB PDE to push the computational boundaries of stochastic optimal control.

This is done by crafting together previously disjoint lines of research in computation. The first of these is the use of Sum of Squares (SOS) techniques for synthesis of control policies. A candidate polynomial with variable coefficients is proposed as the solution to the stochastic optimal control problem. An SOS relaxation is then taken to the partial differential constraints, leading to a hierarchy of semidefinite relaxations with improving sub-optimality gap. The resulting approximate solutions are shown to be guaranteed over- and under-approximations for the optimal value function. It is shown that these results extend to arbitrary parabolic and elliptic PDEs, yielding a novel method for Uncertainty Quantification (UQ) of systems governed by partial differential constraints. Domain decomposition techniques are also made available, allowing for such problems to be solved via parallelization and low-order polynomials.

The optimization-based SOS technique is then contrasted with the Separated Representation (SR) approach from the applied mathematics community. The technique allows for systems of equations to be solved through a low-rank decomposition that results in algorithms that scale linearly with dimensionality. Its application in stochastic optimal control allows for previously uncomputable problems to be solved quickly, scaling to such complex systems as the Quadcopter and VTOL aircraft. This technique may be combined with the SOS approach, yielding not only a numerical technique, but also an analytical one that allows for entirely new classes of systems to be studied and for stability properties to be guaranteed.

The analysis of the linear HJB is completed by the study of its implications in application. It is shown that the HJB and a popular technique in robotics, the use of navigation functions, sit on opposite ends of a spectrum of optimization problems, upon which tradeoffs may be made in problem complexity. Analytical solutions to the HJB in these settings are available in simplified domains, yielding guidance towards optimality for approximation schemes. Finally, the use of HJB equations in temporal multi-task planning problems is investigated. It is demonstrated that such problems are reducible to a sequence of SOC problems linked via boundary conditions. The linearity of the PDE allows us to pre-compute control policy primitives and then compose them, at essentially zero cost, to satisfy a complex temporal logic specification.

Damping and saturation of a second order electron plasma wave echo

A description is given of experimental work on the damping of a second order electron plasma wave echo due to velocity space diffusion in a low temperature magnetoplasma. Sufficient precision was obtained to verify the theoretically predicted cubic rather than quadratic or quartic dependence of the damping on exciter separation. Compared to the damping predicted for Coulomb collisions in a thermal plasma in an infinite magnetic field, the magnitude of the damping was approximately as predicted, while the velocity dependence of the damping was weaker than predicted. The discrepancy is consistent with the actual non-Maxwellian electron distribution of the plasma.

In conjunction with the damping work, echo amplitude saturation was measured as a function of the velocity of the electrons contributing to the echo. Good agreement was obtained with the predicted J₁ Bessel function amplitude dependence, as well as a demonstration that saturation did not influence the damping results.

Ghost imaging with thermal light by third-order correlation

Ghost imaging with classical incoherent light by third-order correlation is investigated. We discuss the similarities and the differences between ghost imaging by third-order correlation and by second-order correlation, and analyze the effect from each correlation part of the third-order correlation function on the imaging process. It is shown that the third-order correlated imaging includes richer correlated imaging effects than the second-order correlated one, while the imaging information originates mainly from the correlation of the intensity fluctuations between the test detector and each reference detector, as does ghost imaging by second-order correlation.