Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

Nuclear weak interaction rates during stellar evolution and collapse

Nuclear weak interaction rates, including electron and positron emission rates, and continuum electron and positron capture rates , as well as the associated v and –/v energy loss rates are calculated on a detailed grid of temperature and density for the free nucleons and 226 nuclei with masses between A = 21 and 60. Gamow-Teller and Fermi discrete-state transition matrix element systematics and the Gamow-Teller T^< →/← T^> resonance transitions are discussed in depth and are implemented in the stellar rate calculations. Results of the calculations are presented on an abbreviated grid of temperature and density and comparison is made to terrestrial weak transition rates where possible. Neutron shell blocking of allowed electron capture on heavy nuclei during stellar core collapse is discussed along with several unblocking mechanisms operative at high temperature and density. The results of one-zone collapse calculations are presented which suggest that the effect of neutron shell blocking is to produce a larger core lepton fraction at neutrino trapping which leads to a larger inner-core mass and hence a stronger post-bounce shock.

Discontinuous yielding and fracture initiation near a notch in mild steel

This thesis presents the results of an experimental investigation of the initiation of brittle fracture and the nature of discontinuous yielding in small plastic enclaves in an annealed mild steel. Upper and lower yield stress data have been obtained from unnotched specimens and nominal fracture stress data have been obtained from specimens of two scale factors and two grain sizes over a range of nominal stress rates from 10^2 to 10^7 lb/in.^2 sec at -111°F and -200°F. The size and shape of plastic enclaves near the notches were revealed by an etch technique.

A stress analysis utilizing slip-line field theory in the plastic region has been developed for the notched specimen geometry employed in this investigation. The yield stress of the material in the plastic enclaves near the notch root has been correlated with the lower yield stress measured on unnotched specimens through a consideration of the plastic boundary velocity under dynamic loading. A maximum tensile stress of about 122,000 lb/in.^2 at the instant of fracture initiation was calculated with the aid of the stress analysis for the large scale specimens of ASTM grain size 8 1/4.

The plastic strain state adjacent to a plastic-elastic interface has been shown to cause the maximum shear stress to have a larger value on the elastic than the plastic side of the interface. This characteristic of dis continuous yielding is instrumental in causing the plastic boundaries to be nearly parallel to the slip-line field where the plastic strain is of the order of the Lüder's strain.

I. Proton magnetic resonance of polynucleotides and transfer RNA. II. Electron spin relaxation studies of manganese (II) complexes in acetonitrile

Part I. Proton Magnetic Resonance of Polynucleotides and Transfer RNA.

Proton magnetic resonance was used to follow the temperature dependent intramolecular stacking of the bases in the polynucleotides of adenine and cytosine. Analysis of the results on the basis of a two state stacked-unstacked model yielded values of -4.5 kcal/mole and -9.5 kcal/mole for the enthalpies of stacking in polyadenylic and polycytidylic acid, respectively.

The interaction of purine with these molecules was also studied by pmr. Analysis of these results and the comparison of the thermal unstacking of polynucleotides and short chain nucleotides indicates that the bases contained in stacks within the long chain poly nucleotides are, on the average, closer together than the bases contained in stacks in the short chain nucleotides.

Temperature and purine studies were also carried out with an aqueous solution of formylmethionine transfer ribonucleic acid. Comparison of these results with the results of similar experiments with the homopolynucleotides of adenine, cytosine and uracil indicate that the purine is probably intercalating into loop regions of the molecule.

The solvent denaturation of phenylalanine transfer ribonucleic acid was followed by pmr. In a solvent mixture containing 83 volume per cent dimethylsulf oxide and 17 per cent deuterium oxide, the tRNA molecule is rendered quite flexible. It is possible to resolve resonances of protons on the common bases and on certain modified bases.

Part II. Electron Spin Relaxation Studies of Manganese (II) Complexes in Acetonitrile.

The electron paramagnetic resonance spectra of three Mn⁺² complexes, [Mn(CH₃CN)₆]⁺², [MnCl₄]^-2, and [MnBr₄]^-2, in acetonitrile were studied in detail. The objective of this study was to relate changes in the effective spin Hamiltonian parameters and the resonance line widths to the structure of these molecular complexes as well as to dynamical processes in solution.

Of the three systems studied, the results obtained from the [Mn(CH₃CN)₆]⁺² system were the most straight-forward to interpret. Resonance broadening attributable to manganese spin-spin dipolar interactions was observed as the manganese concentration was increased.

In the [MnCl₄]^-2 system, solvent fluctuations and dynamical ion-pairing appear to be significant in determining electron spin relaxation.

In the [MnBr₄]^-2 system, solvent fluctuations, ion-pairing, and Br- ligand exchange provide the principal means of electron spin relaxation. It was also found that the spin relaxation in this system is dependent upon the field strength and is directly related to the manganese concentration. A relaxation theory based on a two state collisional model was developed to account for the observed behavior.