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Emergence of Complexity from Synchronization and Cooperation
The dynamical origin of complexity is an object of intense debate and, up to moment of writing this manuscript, no unified approach exists as to how it should be properly addressed. This research work adopts the perspective of complexity as characterized by the emergence of non-Poisson renewal processes. In particular I introduce two new complex system models, namely the two-state stochastic clocks and the integrate-and-fire stochastic neurons, and investigate its coupled dynamics in different network topologies. Based on the foundations of renewal theory, I show how complexity, as manifested by the occurrence of non-exponential distribution of events, emerges from the interaction of the units of the system. Conclusion is made on the work's applicability to explaining the dynamics of blinking nanocrystals, neuron interaction in the human brain, and synchronization processes in complex networks.
Exploration of hierarchical leadership and connectivity in neural networks in vitro.
Living neural networks are capable of processing information much faster than a modern computer, despite running at significantly lower clock speeds. Therefore, understanding the mechanisms neural networks utilize is an issue of substantial importance. Neuronal interaction dynamics were studied using histiotypic networks growing on microelectrode arrays in vitro. Hierarchical relationships were explored using bursting (when many neurons fire in a short time frame) dynamics, pairwise neuronal activation, and information theoretic measures. Together, these methods reveal that global network activity results from ignition by a small group of burst leader neurons, which form a primary circuit that is responsible for initiating most network-wide burst events. Phase delays between leaders and followers reveal information about the nature of the connection between the two. Physical distance from a burst leader appears to be an important factor in follower response dynamics. Information theory reveals that mutual information between neuronal pairs is also a function of physical distance. Activation relationships in developing networks were studied and plating density was found to play an important role in network connectivity development. These measures provide unique views of network connectivity and hierarchical relationship in vitro which should be included in biologically meaningful models of neural networks.
Microscopic Foundations of Thermodynamics and Generalized Statistical Ensembles
This dissertation aims at addressing two important theoretical questions which are still debated in the statistical mechanical community. The first question has to do with the outstanding problem of how to reconcile time-reversal asymmetric macroscopic laws with the time-reversal symmetric laws of microscopic dynamics. This problem is addressed by developing a novel mechanical approach inspired by the work of Helmholtz on monocyclic systems and the Heat Theorem, i.e., the Helmholtz Theorem. By following a line of investigation initiated by Boltzmann, a Generalized Helmholtz Theorem is stated and proved. This theorem provides us with a good microscopic analogue of thermodynamic entropy. This is the volume entropy, namely the logarithm of the volume of phase space enclosed by the constant energy hyper-surface. By using quantum mechanics only, it is shown that such entropy can only increase. This can be seen as a novel rigorous proof of the Second Law of Thermodynamics that sheds new light onto the arrow of time problem. The volume entropy behaves in a thermodynamic-like way independent of the number of degrees of freedom of the system, indicating that a whole thermodynamic-like world exists at the microscopic level. It is also shown that breaking of ergodicity leads to microcanonical phase transitions associated with nonanalyticities of volume entropy. The second part of the dissertation deals with the problem of the foundations of generalized ensembles in statistical mechanics. The starting point is Boltzmann's work on statistical ensembles and its relation with the Heat Theorem. We first focus on the nonextensive thermostatistics of Tsallis and the associated deformed exponential ensembles. These ensembles are analyzed in detail and proved (a) to comply with the requirements posed by the Heat Theorem, and (b) to interpolate between canonical and microcanonical ensembles. Further they are showed to describe finite systems in contact with finite heat baths. …
Multifunctional Organic-Inorganic Hybrid Nanophotonic Devices
The emergence of optical applications, such as lasers, fiber optics, and semiconductor based sources and detectors, has created a drive for smaller and more specialized devices. Nanophotonics is an emerging field of study that encompasses the disciplines of physics, engineering, chemistry, biology, applied sciences and biomedical technology. In particular, nanophotonics explores optical processes on a nanoscale. This dissertation presents nanophotonic applications that incorporate various forms of the organic polymer N-isopropylacrylamide (NIPA) with inorganic semiconductors. This includes the material characterization of NIPA, with such techniques as ellipsometry and dynamic light scattering. Two devices were constructed incorporating the NIPA hydrogel with semiconductors. The first device comprises a PNIPAM-CdTe hybrid material. The PNIPAM is a means for the control of distances between CdTe quantum dots encapsulated within the hydrogel. Controlling the distance between the quantum dots allows for the control of resonant energy transfer between neighboring quantum dots. Whereby, providing a means for controlling the temperature dependent red-shifts in photoluminescent peaks and FWHM. Further, enhancement of photoluminescent due to increased scattering in the medium is shown as a function of temperature. The second device incorporates NIPA into a 2D photonic crystal patterned on GaAs. The refractive index change of the NIPA hydrogel as it undergoes its phase change creates a controllable mechanism for adjusting the transmittance of light frequencies through a linear defect in a photonic crystal. The NIPA infiltrated photonic crystal shows greater shifts in the bandwidth per ºC than any liquid crystal methods. This dissertation demonstrates the versatile uses of hydrogel, as a means of control in nanophotonic devices, and will likely lead to development of other hybrid applications. The development of smaller light based applications will facilitate the need to augment the devices with control mechanism and will play an increasing important role in the future.
The Nonadditive Generalization of Klimontovich's S-Theorem for Open Systems and Boltzmann's Orthodes
We show that the nonadditive open systems can be studied in a consistent manner by using a generalized version of S-theorem. This new generalized S-theorem can further be considered as an indication of self-organization in nonadditive open systems as prescribed by Haken. The nonadditive S-theorem is then illustrated by using the modified Van der Pol oscillator. Finally, Tsallis entropy as an equilibrium entropy is studied by using Boltzmann's method of orthodes. This part of dissertation shows that Tsallis ensemble is on equal footing with the microcanonical, canonical and grand canonical ensembles. However, the associated entropy turns out to be Renyi entropy.
Oligonucleotide guanosine conjugated to gallium nitride nano-structures for photonics.
In this work, I studied the hybrid system based on self-assembled guanosine crystal (SAGC) conjugated to wide-bandgap semiconductor gallium nitride (GaN). Guanosine is one of the four bases of DNA and has the lowest oxidation energy, which favors carrier transport. It also has large dipole moment. Guanosine molecules self-assemble to ribbon-like structure in confined space. GaN surface can have positive or negative polarity depending on whether the surface is Ga- or N-terminated. I studied SAGC in confined space between two electrodes. The current-voltage characteristics can be explained very well with the theory of metal-semiconductor-metal (MSM) structure. I-V curves also show strong rectification effect, which can be explained by the intrinsic polarization along the axis of ribbon-like structure of SAGC. GaN substrate property influences the properties of SAGC. So SAGC has semiconductor properties within the confined space up to 458nm. When the gap distance gets up to 484nm, the structure with guanosine shows resistance characteristics. The photocurrent measurements show that the bandgap of SAGC is about 3.3-3.4eV and affected by substrate properties. The MSM structure based on SAGC can be used as photodetector in UV region. Then I show that the periodic structure based on GaN and SAGC can have photonic bandgaps. The bandgap size and the band edges can be tuned by tuning lattice parameters. Light propagation and emission can be tuned by photonic crystals. So the hybrid photonic crystal can be potentially used to detect guanosine molecules. If guanosine molecules are used as functional linker to other biomolecules which usually absorb or emit light in blue to UV region, the hybrid photonic crystal can also be used to tune the coupling of light source to guanosine molecules, then to other biomolecules.
Perturbation of renewal processes
Renewal theory began development in the early 1940s, as the need for it in the industrial engineering sub-discipline operations research had risen. In time, the theory found applications in many stochastic processes. In this thesis I investigated the effect of seasonal effects on Poisson and non-Poisson renewal processes in the form of perturbations. It was determined that the statistical analysis methods developed at UNT Center for Nonlinear Science can be used to detect the effects of seasonality on the data obtained from Poisson/non-Poisson renewal systems. It is proved that a perturbed Poisson process can serve as a paradigmatic model for a case where seasonality is correlated to the noise and that diffusion entropy method can be utilized in revealing this relation. A renewal model making a connection with the stochastic resonance phenomena is used to analyze a previous neurological experiment, and it was shown that under the effect of a nonlinear perturbation, a non-Poisson system statistics may make a transition and end up in the of Poisson basin of statistics. I determine that nonlinear perturbation of the power index for a complex system will lead to a change in the complexity characteristics of the system, i.e., the system will reach a new form of complexity.
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