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The research on the topology and dynamics of complex networks is one of the most focused area in complex system science. The goals are to structure our understanding of the real-world social, economical, technological, and biological systems in the aspect of networks consisting a large number of interacting units and to develop corresponding detection, prediction, and control strategies. In this highly interdisciplinary field, my research mainly concentrates on universal estimation schemes, physical controllability, as well as mechanisms behind extreme events and cascading failure for complex networked systems.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
ContributorsChen, Yuzhong (Author) / Lai, Ying-Cheng (Thesis advisor) / Spanias, Andreas (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2016
Description
Humanity’s demand for energy is increasing exponentially and the dependence on fossil fuels is both unsustainable and detrimental to the environment. To provide a solution to the impending energy crisis, it is reasonable to look toward utilizing solar energy, which is abundant and renewable. One approach to harvesting solar irradiation for fuel purposes is through mimicking the processes of natural photosynthesis in an artificial design to use sunlight and water to store energy in chemical bonds for later use. Thus, in order to design an efficient energy conversion device, the underlying processes of the natural system must be understood. An artificial photosynthetic device has many components and each can be optimized separately. This work deals with the design, construction and study of some of those components. The first chapter provides an introduction to this work. The second chapter shows a proof of concept for a water splitting dye sensitized photoelectrochemical cell followed by the presentation of a new p-type semiconductor, the design of a modular cluster binding protein that can be used for incorporating catalysts, and a new anchoring group for semiconducting oxides with high electron injection efficiency. The third chapter investigates the role of electronic coupling and thermodynamics for photoprotection in artificial systems by triplet-triplet energy transfer from tetrapyrroles to carotenoids. The fourth chapter describes a mimic of the proton-coupled electron transfer in photosystem II and confirms that in the artificial system a concerted mechanism operates. In the fifth chapter, a microbial system is designed to work in tandem with a photovoltaic device to produce high energy fuels. A variety of quinone redox mediators have been synthesized to shuttle electrons from an electron donor to the microbial system. Lastly, the synthesis of a variety of photosensitizers is detailed for possible future use in artificial systems. The results of this work helps with the understanding of the processes of natural photosynthesis and suggests ways to design artificial photosynthetic devices that can contribute to solving the renewable energy challenge.
ContributorsBrown, Chelsea L (Author) / Moore, Ana L (Thesis advisor) / Gust, Devens (Committee member) / Woodbury, Neal (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purpose of information source detection problem (or called rumor source detection) is to identify the source of information diffusion in networks based on available observations like the states of the nodes and the timestamps at which nodes adopted the information (or called infected). The solution of the problem can be used to answer a wide range of important questions in epidemiology, computer network security, etc. This dissertation studies the fundamental theory and the design of efficient and robust algorithms for the information source detection problem.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
ContributorsZhu, Kai (Author) / Ying, Lei (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Liu, Huan (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2015
Description
The manipulation of biological targets using synthetic compounds has been the focal point of medicinal chemistry. The work described herein centers on the synthesis of organic small molecules that act either as probes for studying protein conformational changes or DNA–protein interaction, or as multifunctional radical quenchers.
Fluorescent labeling is of paramount importance to biological studies of proteins. For the development of new extrinsic small fluorophores, a series of tryptophan analogues has been designed and synthesized. Their pdCpA derivatives have been synthesized for tRNA activation and in vitro protein synthesis. The photophysical properties of the tryptophan (Trp) analogues have been examined, some of which can be selectively monitored even in the presence of multiple native tryptophan residues. Further, some of the Trp analogues form efficient FRET pairs with acceptors such as acridon-2-ylalanine (Acd) or L-(7-hydroxycoumarin-4-yl)ethylglycine (HCO) for the selective study of conformational changes in proteins.
Molecules which can bind with high sequence selectivity to a chosen target in a gene sequence are of interest for the development of gene therapy, diagnostic devices for genetic analysis, and as molecular tools for nucleic acid manipulations. Stereoselective synthesis of different alanyl nucleobase amino acids is described. Their pdCpA derivatives have been synthesized for tRNA activation and site-specific incorporation into the DNA-binding protein RRM1 of hnRNP LL. It is proposed that the nucleobase moieties in the protein may specifically recognize base sequence in the i-motif DNA through H-bonding and base-stacking interactions.
The mitochondrial respiratory chain accumulates more oxidative damage than any other organelle within the cell. Dysfunction of this organelle is believed to drive the progression of many diseases, thus mitochondria are an important potential drug target. Reactive oxygen species (ROS) are generated when electrons from the respiratory chain escape and interact with oxygen. ROS can react with proteins, lipids or DNA causing cell death. For the development of effective neuroprotective drugs, a series of N-hydroxy-4-pyridones have been designed and synthesized as CoQ10 analogues. All the analogues synthesized were evaluated for their ability to quench lipid peroxidation and reactive oxygen species (ROS).
Fluorescent labeling is of paramount importance to biological studies of proteins. For the development of new extrinsic small fluorophores, a series of tryptophan analogues has been designed and synthesized. Their pdCpA derivatives have been synthesized for tRNA activation and in vitro protein synthesis. The photophysical properties of the tryptophan (Trp) analogues have been examined, some of which can be selectively monitored even in the presence of multiple native tryptophan residues. Further, some of the Trp analogues form efficient FRET pairs with acceptors such as acridon-2-ylalanine (Acd) or L-(7-hydroxycoumarin-4-yl)ethylglycine (HCO) for the selective study of conformational changes in proteins.
Molecules which can bind with high sequence selectivity to a chosen target in a gene sequence are of interest for the development of gene therapy, diagnostic devices for genetic analysis, and as molecular tools for nucleic acid manipulations. Stereoselective synthesis of different alanyl nucleobase amino acids is described. Their pdCpA derivatives have been synthesized for tRNA activation and site-specific incorporation into the DNA-binding protein RRM1 of hnRNP LL. It is proposed that the nucleobase moieties in the protein may specifically recognize base sequence in the i-motif DNA through H-bonding and base-stacking interactions.
The mitochondrial respiratory chain accumulates more oxidative damage than any other organelle within the cell. Dysfunction of this organelle is believed to drive the progression of many diseases, thus mitochondria are an important potential drug target. Reactive oxygen species (ROS) are generated when electrons from the respiratory chain escape and interact with oxygen. ROS can react with proteins, lipids or DNA causing cell death. For the development of effective neuroprotective drugs, a series of N-hydroxy-4-pyridones have been designed and synthesized as CoQ10 analogues. All the analogues synthesized were evaluated for their ability to quench lipid peroxidation and reactive oxygen species (ROS).
ContributorsTalukder, Poulami (Author) / Hecht, Sidney M. (Thesis advisor) / Woodbury, Neal (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2016
Description
In this thesis, I present the study of nucleon structure from distinct perspectives. I start by elaborating the motivations behind the endeavors and then introducing the key concept, namely the generalized parton distribution functions (GPDs), which serves as the frame- work describing hadronic particles in terms of their fundamental constituents. The second chapter is then devoted to a detailed phenomenological study of the Virtual Compton Scattering (VCS) process, where a more comprehensive parametrization is suggested. In the third chapter, the renormalization kernels that enters the QCD evolution equations at twist- 4 accuracy are computed in terms of Feynman diagrams in momentum space, which can be viewed as an extension of the work by Bukhvostov, Frolov, Lipatov, and Kuraev (BKLK). The results can be used for determining the QCD background interaction for future precision measurements.
ContributorsJi, Yao, Ph. D (Author) / Belitsky, Andrei (Thesis advisor) / Lebed, Richard (Committee member) / Schmidt, Kevin E (Committee member) / Vachaspati, Tanmay (Committee member) / Arizona State University (Publisher)
Created2016
Description
Sunlight, the most abundant source of energy available, is diffuse and intermittent; therefore it needs to be stored in chemicals bonds in order to be used any time. Photosynthesis converts sunlight into useful chemical energy that organisms can use for their functions. Artificial photosynthesis aims to use the essential chemistry of natural photosynthesis to harvest solar energy and convert it into fuels such as hydrogen gas. By splitting water, tandem photoelectrochemical solar cells (PESC) can produce hydrogen gas, which can be stored and used as fuel. Understanding the mechanisms of photosynthesis, such as photoinduced electron transfer, proton-coupled electron transfer (PCET) and energy transfer (singlet-singlet and triplet-triplet) can provide a detailed knowledge of those processes which can later be applied to the design of artificial photosynthetic systems. This dissertation has three main research projects. The first part focuses on design, synthesis and characterization of suitable photosensitizers for tandem cells. Different factors that can influence the performance of the photosensitizers in PESC and the attachment and use of a biomimetic electron relay to a water oxidation catalyst are explored. The second part studies PCET, using Nuclear Magnetic Resonance and computational chemistry to elucidate the structure and stability of tautomers that comprise biomimetic electron relays, focusing on the formation of intramolecular hydrogen bonds. The third part of this dissertation uses computational calculations to understand triplet-triplet energy transfer and the mechanism of quenching of the excited singlet state of phthalocyanines in antenna models by covalently attached carotenoids.
ContributorsTejeda Ferrari, Marely (Author) / Moore, Ana (Thesis advisor) / Mujica, Vladimiro (Thesis advisor) / Gust, John (Committee member) / Woodbury, Neal (Committee member) / Arizona State University (Publisher)
Created2016
Description
The work presented in this dissertation examines three different nonequilibrium particle physics processes that could play a role in answering the question “how was the particle content of today’s universe produced after the big bang?” Cosmic strings produced from spontaneous breaking of a hidden sector $U(1)_{\rm X}$ symmetry could couple to Standard Model fields through Higgs Portal or Kinetic Mixing operators and radiate particles that contribute to the diffuse gamma ray background. In this work we calculate the properties of these strings, including finding effective couplings between the strings and Standard Model fields. Explosive particle production after inflation, known as preheating, would have produced a stochastic background of gravitational waves (GW). This work shows how the presence of realistic additional fields and interactions can affect this prediction dramatically. Specifically, it considers the inflaton to be coupled to a light scalar field, and shows that even a very small quartic self-interaction term will reduce the amplitude of the gravitational wave spectrum. For self-coupling $\lambda_{\chi} \gtrsim g^2$, where $g^2$ is the inflaton-scalar coupling, the peak energy density goes as $\Omega_{\rm GW}^{(\lambda_{\chi})} / \Omega_{\rm GW}^{(\lambda_{\chi}=0)} \sim (g^2/\lambda_{\chi})^{2}$. Finally, leptonic charge-parity (CP) violation could be an important clue to understanding the origin of our universe's matter-antimatter asymmetry, and long-baseline neutrino oscillation experiments in the coming decade may uncover this. The CP violating effects of a possible fourth ``sterile" neutrino can interfere with the usual three neutrinos; this work shows how combinations of various measurements can help break those degeneracies.
ContributorsHyde, Jeffrey Morgan (Author) / Vachaspati, Tanmay (Thesis advisor) / Easson, Damien (Committee member) / Belitsky, Andrei (Committee member) / Comfort, Joseph (Committee member) / Arizona State University (Publisher)
Created2016
Description
Conductance fluctuations associated with quantum transport through quantumdot systems are currently understood to depend on the nature of the corresponding classical dynamics, i.e., integrable or chaotic. There are a couple of interesting phenomena about conductance fluctuation and quantum tunneling related to geometrical shapes of graphene systems. Firstly, in graphene quantum-dot systems, when a magnetic field is present, as the Fermi energy or the magnetic flux is varied, both regular oscillations and random fluctuations in the conductance can occur, with alternating transitions between the two. Secondly, a scheme based on geometrical rotation of rectangular devices to effectively modulate the conductance fluctuations is presented. Thirdly, when graphene is placed on a substrate of heavy metal, Rashba spin-orbit interaction of substantial strength can occur. In an open system such as a quantum dot, the interaction can induce spin polarization. Finally, a problem using graphene systems with electron-electron interactions described by the Hubbard Hamiltonian in the setting of resonant tunneling is investigated.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
ContributorsYing, Lei (Author) / Lai, Ying-Cheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Chen, Tingyong (Committee member) / Yao, Yu (Committee member) / Arizona State University (Publisher)
Created2016
Description
With the discovery of the Higgs Boson in 2012, particle physics has decidedly moved beyond the Standard Model into a new epoch. Though the Standard Model particle content is now completely accounted for, there remain many theoretical issues about the structure of the theory in need of resolution. Among these is the hierarchy problem: since the renormalized Higgs mass receives quadratic corrections from a higher cutoff scale, what keeps the Higgs boson light? Many possible solutions to this problem have been advanced, such as supersymmetry, Randall-Sundrum models, or sub-millimeter corrections to gravity. One such solution has been advanced by the Lee-Wick Standard Model. In this theory, higher-derivative operators are added to the Lagrangian for each Standard Model field, which result in propagators that possess two physical poles and fall off more rapidly in the ultraviolet regime. It can be shown by an auxiliary field transformation that the higher-derivative theory is identical to positing a second, manifestly renormalizable theory in which new fields with opposite-sign kinetic and mass terms are found. These so-called Lee-Wick fields have opposite-sign propagators, and famously cancel off the quadratic divergences that plague the renormalized Higgs mass. The states in the Hilbert space corresponding to Lee-Wick particles have negative norm, and implications for causality and unitarity are examined.
This dissertation explores a variant of the theory called the N = 3 Lee-Wick
Standard Model. The Lagrangian of this theory features a yet-higher derivative operator, which produces a propagator with three physical poles and possesses even better high-energy behavior than the minimal Lee-Wick theory. An analogous auxiliary field transformation takes this higher-derivative theory into a renormalizable theory with states of alternating positive, negative, and positive norm. The phenomenology of this theory is examined in detail, with particular emphasis on the collider signatures of Lee-Wick particles, electroweak precision constraints on the masses that the new particles can take on, and scenarios in early-universe cosmology in which Lee-Wick particles can play a significant role.
This dissertation explores a variant of the theory called the N = 3 Lee-Wick
Standard Model. The Lagrangian of this theory features a yet-higher derivative operator, which produces a propagator with three physical poles and possesses even better high-energy behavior than the minimal Lee-Wick theory. An analogous auxiliary field transformation takes this higher-derivative theory into a renormalizable theory with states of alternating positive, negative, and positive norm. The phenomenology of this theory is examined in detail, with particular emphasis on the collider signatures of Lee-Wick particles, electroweak precision constraints on the masses that the new particles can take on, and scenarios in early-universe cosmology in which Lee-Wick particles can play a significant role.
ContributorsTerBeek, Russell Henry (Author) / Lebed, Richard F (Thesis advisor) / Alarcon, Ricardo (Committee member) / Belitsky, Andrei (Committee member) / Chamberlin, Ralph (Committee member) / Parikh, Maulik (Committee member) / Arizona State University (Publisher)
Created2015
Description
The healthcare system in this country is currently unacceptable. New technologies may contribute to reducing cost and improving outcomes. Early diagnosis and treatment represents the least risky option for addressing this issue. Such a technology needs to be inexpensive, highly sensitive, highly specific, and amenable to adoption in a clinic. This thesis explores an immunodiagnostic technology based on highly scalable, non-natural sequence peptide microarrays designed to profile the humoral immune response and address the healthcare problem. The primary aim of this thesis is to explore the ability of these arrays to map continuous (linear) epitopes. I discovered that using a technique termed subsequence analysis where epitopes could be decisively mapped to an eliciting protein with high success rate. This led to the discovery of novel linear epitopes from Plasmodium falciparum (Malaria) and Treponema palladium (Syphilis), as well as validation of previously discovered epitopes in Dengue and monoclonal antibodies. Next, I developed and tested a classification scheme based on Support Vector Machines for development of a Dengue Fever diagnostic, achieving higher sensitivity and specificity than current FDA approved techniques. The software underlying this method is available for download under the BSD license. Following this, I developed a kinetic model for immunosignatures and tested it against existing data driven by previously unexplained phenomena. This model provides a framework and informs ways to optimize the platform for maximum stability and efficiency. I also explored the role of sequence composition in explaining an immunosignature binding profile, determining a strong role for charged residues that seems to have some predictive ability for disease. Finally, I developed a database, software and indexing strategy based on Apache Lucene for searching motif patterns (regular expressions) in large biological databases. These projects as a whole have advanced knowledge of how to approach high throughput immunodiagnostics and provide an example of how technology can be fused with biology in order to affect scientific and health outcomes.
ContributorsRicher, Joshua Amos (Author) / Johnston, Stephen A. (Thesis advisor) / Woodbury, Neal (Committee member) / Stafford, Phillip (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014