Time-Domain TeraHertz Spectroscopy and Observational Probes of Prebiotic Interstellar Gas and Ice Chemistry

Understanding the origin of life on Earth has long fascinated the minds of the global community, and has been a driving factor in interdisciplinary research for centuries. Beyond the pioneering work of Darwin, perhaps the most widely known study in the last century is that of Miller and Urey, who examined the possibility of the formation of prebiotic chemical precursors on the primordial Earth [1]. More recent studies have shown that amino acids, the chemical building blocks of the biopolymers that comprise life as we know it on Earth, are present in meteoritic samples, and that the molecules extracted from the meteorites display isotopic signatures indicative of an extraterrestrial origin [2]. The most recent major discovery in this area has been the detection of glycine (NH₂CH₂COOH), the simplest amino acid, in pristine cometary samples returned by the NASA STARDUST mission [3]. Indeed, the open questions left by these discoveries, both in the public and scientific communities, hold such fascination that NASA has designated the understanding of our "Cosmic Origins" as a key mission priority.

Despite these exciting discoveries, our understanding of the chemical and physical pathways to the formation of prebiotic molecules is woefully incomplete. This is largely because we do not yet fully understand how the interplay between grain-surface and sub-surface ice reactions and the gas-phase affects astrophysical chemical evolution, and our knowledge of chemical inventories in these regions is incomplete. The research presented here aims to directly address both these issues, so that future work to understand the formation of prebiotic molecules has a solid foundation from which to work.

From an observational standpoint, a dedicated campaign to identify hydroxylamine (NH₂OH), potentially a direct precursor to glycine, in the gas-phase was undertaken. No trace of NH₂OH was found. These observations motivated a refinement of the chemical models of glycine formation, and have largely ruled out a gas-phase route to the synthesis of the simplest amino acid in the ISM. A molecular mystery in the case of the carrier of a series of transitions was resolved using observational data toward a large number of sources, confirming the identity of this important carbon-chemistry intermediate B11244 as l-C₃H⁺ and identifying it in at least two new environments. Finally, the doubly-nitrogenated molecule carbodiimide HNCNH was identified in the ISM for the first time through maser emission features in the centimeter-wavelength regime.

In the laboratory, a TeraHertz Time-Domain Spectrometer was constructed to obtain the experimental spectra necessary to search for solid-phase species in the ISM in the THz region of the spectrum. These investigations have shown a striking dependence on large-scale, long-range (i.e. lattice) structure of the ices on the spectra they present in the THz. A database of molecular spectra has been started, and both the simplest and most abundant ice species, which have already been identified, as well as a number of more complex species, have been studied. The exquisite sensitivity of the THz spectra to both the structure and thermal history of these ices may lead to better probes of complex chemical and dynamical evolution in interstellar environments.

Upper hybrid resonance absorption and scattering from a plasma column

The electromagnetic scattering and absorption properties of small (kr~1/2) inhomogeneous magnetoplasma columns are calculated via the full set of Maxwell's equations with tensor dielectric constitutive relation. The cold plasma model with collisional damping is used to describe the column. The equations are solved numerically, subject to boundary conditions appropriate to an infinite parallel strip line and to an incident plane wave. The results are similar for several density profiles and exhibit semiquantitative agreement with measurements in waveguide. The absorption is spatially limited, especially for small collision frequency, to a narrow hybrid resonant layer and is essentially zero when there is no hybrid layer in the column. The reflection is also enhanced when the hybrid layer is present, but the value of the reflection coefficient is strongly modified by the presence of the glass tube. The nature of the solutions and an extensive discussion of the conditions under which the cold collisional model should yield valid results is presented.

Distributed Control and Optimization for Communication and Power Systems

We are at the cusp of a historic transformation of both communication system and electricity system. This creates challenges as well as opportunities for the study of networked systems. Problems of these systems typically involve a huge number of end points that require intelligent coordination in a distributed manner. In this thesis, we develop models, theories, and scalable distributed optimization and control algorithms to overcome these challenges.

This thesis focuses on two specific areas: multi-path TCP (Transmission Control Protocol) and electricity distribution system operation and control. Multi-path TCP (MP-TCP) is a TCP extension that allows a single data stream to be split across multiple paths. MP-TCP has the potential to greatly improve reliability as well as efficiency of communication devices. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate a new algorithm Balia (balanced linked adaptation) which generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented Balia in the Linux kernel. We use our prototype to compare the new proposed algorithm Balia with existing MP-TCP algorithms.

Our second focus is on designing computationally efficient algorithms for electricity distribution system operation and control. First, we develop efficient algorithms for feeder reconfiguration in distribution networks. The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed integer nonlinear program and hence hard to solve. We propose a heuristic algorithm that is based on the recently developed convex relaxation of the optimal power flow problem. The algorithm is efficient and can successfully computes an optimal configuration on all networks that we have tested. Moreover we prove that the algorithm solves the feeder reconfiguration problem optimally under certain conditions. We also propose a more efficient algorithm and it incurs a loss in optimality of less than 3% on the test networks.

Second, we develop efficient distributed algorithms that solve the optimal power flow (OPF) problem on distribution networks. The OPF problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally OPF is solved in a centralized manner. With increasing penetration of volatile renewable energy resources in distribution systems, we need faster and distributed solutions for real-time feedback control. This is difficult because power flow equations are nonlinear and kirchhoff's law is global. We propose solutions for both balanced and unbalanced radial distribution networks. They exploit recent results that suggest solving for a globally optimal solution of OPF over a radial network through a second-order cone program (SOCP) or semi-definite program (SDP) relaxation. Our distributed algorithms are based on the alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative methods, the proposed solutions exploit the problem structure that greatly reduce the computation time. Specifically, for balanced networks, our decomposition allows us to derive closed form solutions for these subproblems and it speeds up the convergence by 1000x times in simulations. For unbalanced networks, the subproblems reduce to either closed form solutions or eigenvalue problems whose size remains constant as the network scales up and computation time is reduced by 100x compared with iterative methods.