Matching Items (91)
Description
In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
Description
What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.
ContributorsNi, Xuan (Author) / Lai, Ying-Cheng (Thesis advisor) / Huang, Liang (Committee member) / Yu, Hongbin (Committee member) / Akis, Richard (Committee member) / Arizona State University (Publisher)
Created2012
Description
Complex human controls is a topic of much interest in the fields of robotics, manufacturing, space exploration and many others. Even simple tasks that humans perform with ease can be extremely complicated when observed from a controls and complex systems perspective. One such simple task is that of a human carrying and moving a coffee cup. Though this may be a mundane task for humans, when this task is modelled and analyzed, the system may be quite chaotic in nature. Understanding such systems is key to the development robots and autonomous systems that can perform these tasks themselves.
The coffee cup system can be simplified and modeled by a cart-and-pendulum system. Bazzi et al. and Maurice et al. present two different cart-and-pendulum systems to represent the coffee cup system [1],[2]. The purpose of this project was to build upon these systems and to gain a better understanding of the coffee cup system and to determine where chaos existed within the system. The honors thesis team first worked with their senior design group to develop a mathematical model for the cart-and-pendulum system based on the Bazzi and Maurice papers [1],[2]. This system was analyzed and then built upon by the honors thesis team to build a cart-and-two-pendulum model to represent the coffee cup system more accurately.
Analysis of the single pendulum model showed that there exists a low frequency region where the pendulum and the cart remain in phase with each other and a high frequency region where the cart and pendulum have a π phase difference between them. The transition point of the low and high frequency region is determined by the resonant frequency of the pendulum. The analysis of the two-pendulum system also confirmed this result and revealed that differences in length between the pendulum cause the pendulums to transition to the high frequency regions at separate frequency. The pendulums have different resonance frequencies and transition into the high frequency region based on their own resonant frequency. This causes a range of frequencies where the pendulums are out of phase from each other. After both pendulums have transitioned, they remain in phase with each other and out of phase from the cart.
However, if the length of the pendulum is decreased too much, the system starts to exhibit chaotic behavior. The short pendulum starts to act in a chaotic manner and the phase relationship between the pendulums and the carts is no longer maintained. Since the pendulum length represents the distance between the particle of coffee and the top of the cup, this implies that coffee near the top of the cup would cause the system to act chaotically. Further analysis would be needed to determine the reason why the length affects the system in this way.
The coffee cup system can be simplified and modeled by a cart-and-pendulum system. Bazzi et al. and Maurice et al. present two different cart-and-pendulum systems to represent the coffee cup system [1],[2]. The purpose of this project was to build upon these systems and to gain a better understanding of the coffee cup system and to determine where chaos existed within the system. The honors thesis team first worked with their senior design group to develop a mathematical model for the cart-and-pendulum system based on the Bazzi and Maurice papers [1],[2]. This system was analyzed and then built upon by the honors thesis team to build a cart-and-two-pendulum model to represent the coffee cup system more accurately.
Analysis of the single pendulum model showed that there exists a low frequency region where the pendulum and the cart remain in phase with each other and a high frequency region where the cart and pendulum have a π phase difference between them. The transition point of the low and high frequency region is determined by the resonant frequency of the pendulum. The analysis of the two-pendulum system also confirmed this result and revealed that differences in length between the pendulum cause the pendulums to transition to the high frequency regions at separate frequency. The pendulums have different resonance frequencies and transition into the high frequency region based on their own resonant frequency. This causes a range of frequencies where the pendulums are out of phase from each other. After both pendulums have transitioned, they remain in phase with each other and out of phase from the cart.
However, if the length of the pendulum is decreased too much, the system starts to exhibit chaotic behavior. The short pendulum starts to act in a chaotic manner and the phase relationship between the pendulums and the carts is no longer maintained. Since the pendulum length represents the distance between the particle of coffee and the top of the cup, this implies that coffee near the top of the cup would cause the system to act chaotically. Further analysis would be needed to determine the reason why the length affects the system in this way.
ContributorsZindani, Abdul Rahman (Co-author) / Crane, Kari (Co-author) / Lai, Ying-Cheng (Thesis director) / Jiang, Junjie (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
This paper reviews several current designs of Cube Satellite (CubeSat) Electrical Power Systems (EPS) based on Silicon FET technologies and their current deficiencies, such as radiation-incurred defects and switching power losses. A strategy to fix these is proposed by the way of using Gallium Nitride (GaN) High Electron-Mobility Transistors (HEMTs) as switching devices within Buck/Boost Converters and other regulators. This work summarizes the EPS designs of several CubeSat missions, classifies them, and outlines their efficiency. An in-depth example of an EPS is also given, explaining the process in which these systems are designed. Areas of deficiency are explained along with reasoning as to why GaN can mitigate these losses, including its wide bandgap properties such as high RDS(on) and High Breakdown Voltage. Special design considerations must be kept in mind when using GaN HEMTs in this application and an example of a CubeSat using GaN HEMTs is mentioned. Finally, challenges ahead for GaN are explored including manufacturing considerations and long-term reliability.
ContributorsWilloughby, Alexander George (Author) / Kitchen, Jennifer (Thesis director) / Zhao, Yuji (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The development of biosensing platforms not only has an immediate lifesaving effect but also has a significant socio-economic impact. In this dissertation, three very important biomarkers with immense importance were chosen for further investigation, reducing the technological gap and improving their sensing platform.Firstly, gold nanoparticles (AuNP) aggregation and sedimentation-based assays were developed for the sensitive, specific, and rapid detection of Ebola virus secreted glycoprotein (sGP)and severe acute respiratory syndrome coronavirus 2 (SARS-COV2) receptor-binding domain (RBD) antigens. An extensive study was done to develop a complete assay workflow from critical nanobody generation to optimization of AuNP size for rapid detection. A rapid portable electronic reader costing (<$5, <100 cm3), and digital data output was developed. Together with the developed workflow, this portable electronic reader showed a high sensitivity (limit of detection of ~10 pg/mL, or 0.13 pM for sGP and ~40 pg/mL, or ~1.3 pM for RBD in diluted human serum), a high specificity, a large dynamic range (~7 logs), and accelerated readout within minutes. Secondly, A general framework was established for small molecule detection using plasmonic metal nanoparticles through wide-ranging investigation and optimization of assay parameters with demonstrated detection of Cannabidiol (CBD). An unfiltered assay suitable for personalized dosage monitoring was developed and demonstrated. A portable electronic reader demonstrated optoelectronic detection of CBD with a limit of detection (LOD) of <100 pM in urine and saliva, a large dynamic range (5 logs), and a high specificity that differentiates closely related Tetrahydrocannabinol (THC). Finally, with careful biomolecular design and expansion of the portable reader to a dual-wavelength detector the classification of antibodies based on their affinity to SARS-COV2 RBD and their ability to neutralize the RBD from binding to the human Angiotensin-Converting Enzyme 2 (ACE2) was demonstrated with the capability to detect antibody concentration as low as 1 pM and observed neutralization starting as low as 10 pM with different viral load and variant. This portable, low-cost, and versatile readout system holds great promise for rapid, digital, and portable data collection in the field of biosensing.
ContributorsIkbal, Md Ashif (Author) / Wang, Chao (Thesis advisor) / Goryll, Michael (Committee member) / Zhao, Yuji (Committee member) / Wang, Shaopeng (Committee member) / Arizona State University (Publisher)
Created2022
Description
A remarkable phenomenon in contemporary physics is quantum scarring in classically chaoticsystems, where the wave functions tend to concentrate on classical periodic orbits. Quantum
scarring has been studied for more than four decades, but the problem of efficiently detecting
quantum scars has remained to be challenging, relying mostly on human visualization of
wave function patterns. This paper develops a machine learning approach to detecting
quantum scars in an automated and highly efficient manner. In particular, this paper exploits Meta
learning. The first step is to construct a few-shot classification algorithm, under the
requirement that the one-shot classification accuracy be larger than 90%. Then propose a
scheme based on a combination of neural networks to improve the accuracy. This paper shows that
the machine learning scheme can find the correct quantum scars from thousands images of
wave functions, without any human intervention, regardless of the symmetry of the underlying
classical system. This will be the first application of Meta learning to quantum systems. Interacting spin networks are fundamental to quantum computing. Data-based tomography oftime-independent spin networks has been achieved, but an open challenge is to ascertain the
structures of time-dependent spin networks using time series measurements taken locally
from a small subset of the spins. Physically, the dynamical evolution of a spin network under
time-dependent driving or perturbation is described by the Heisenberg equation of motion.
Motivated by this basic fact, this paper articulates a physics-enhanced machine learning framework
whose core is Heisenberg neural networks. This paper demonstrates that, from local measurements, not only the local Hamiltonian can be recovered but the Hamiltonian reflecting the interacting structure of the whole system can
also be faithfully reconstructed. Using Heisenberg neural machine on spin networks of a
variety of structures. In the extreme case where measurements are taken from only one spin,
the achieved tomography fidelity values can reach about 90%. The developed machine
learning framework is applicable to any time-dependent systems whose quantum dynamical
evolution is governed by the Heisenberg equation of motion.
ContributorsHan, Chendi (Author) / Lai, Ying-Cheng (Thesis advisor) / Yu, Hongbin (Committee member) / Dasarathy, Gautam (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2022
Description
Few-layer black phosphorous (FLBP) is one of the most important two-dimensional (2D) materials due to its strongly layer-dependent quantized bandstructure, which leads to wavelength-tunable optical and electrical properties. This thesis focuses on the preparation of stable, high-quality FLBP, the characterization of its optical properties, and device applications.Part I presents an approach to preparing high-quality, stable FLBP samples by combining O2 plasma etching, boron nitride (BN) sandwiching, and subsequent rapid thermal annealing (RTA). Such a strategy has successfully produced FLBP samples with a record-long lifetime, with 80% of photoluminescence (PL) intensity remaining after 7 months. The improved material quality of FLBP allows the establishment of a more definitive relationship between the layer number and PL energies.
Part II presents the study of oxygen incorporation in FLBP. The natural oxidation formed in the air environment is dominated by the formation of interstitial oxygen and dangling oxygen. By the real-time PL and Raman spectroscopy, it is found that continuous laser excitation breaks the bonds of interstitial oxygen, and free oxygen atoms can diffuse around or form dangling oxygen under low heat. RTA at 450 °C can turn the interstitial oxygen into dangling oxygen more thoroughly. Such oxygen-containing samples show similar optical properties to the pristine BP samples. The bandgap of such FLBP samples increases with the concentration of the incorporated oxygen.
Part III deals with the investigation of emission natures of the prepared samples. The power- and temperature-dependent measurements demonstrate that PL emissions are dominated by excitons and trions, with a combined percentage larger than 80% at room temperature. Such measurements allow the determination of trion and exciton binding energies of 2-, 3-, and 4-layer BP, with values around 33, 23, 15 meV for trions and 297, 276, 179 meV for excitons at 77K, respectively.
Part IV presents the initial exploration of device applications of such FLBP samples. The coupling between photonic crystal cavity (PCC) modes and FLBP's emission is realized by integrating the prepared sandwich structure onto 2D PCC. Electroluminescence has also been achieved by integrating such materials onto interdigital electrodes driven by alternating electric fields.
ContributorsLi, Dongying (Author) / Ning, Cun-Zheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Lai, Ying-Cheng (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2022
Description
In this dissertation, atomic layer processing and surface characterization techniques were used to investigate surface conditions of wide band gap materials, gallium nitride (GaN) and gallium oxide (Ga2O3). These studies largely focused on mitigation and removal of defect formation induced by ions used in conventional plasma-based dry etching techniques. Band bending measured by x-ray photoelectron spectroscopy (XPS) was used to characterize charge compensation at the surface of GaN (0001) and determine densities of charged surface states produced by dry etching. Mitigation and removal of these dry-etch induced defects was investigated by varying inductively coupled plasma (ICP) etching conditions, performing thermal and plasma-based treatments, and development of a novel low-damage, self-limiting atomic layer etching (ALE) process to remove damaged material. Atomic layer deposition (ALD) and ALE techniques were developed for Ga2O3 using trimethylgallium (TMG). Ga2O3 was deposited by ALD on Si using TMG and O2 plasma with a growth rate of 1.0 ± 0.1 Å/cycle. Ga2O3 films were then etched using HF and TMG using a fully thermal ALE process with an etch rate of 0.9 ± Å/cycle. O2 plasma oxidation of GaN for surface conversion to Ga2O3 was investigated as a pathway for ALE of GaN using HF and TMG. This process was characterized using XPS, in situ multi-wavelength ellipsometry, and transmission electron microscopy. This study indicated that the etch rate was lower than anticipated, which was attributed to crystallinity of the converted surface oxide on GaN (0001).
ContributorsHatch, Kevin Andrew (Author) / Nemanich, Robert J (Thesis advisor) / Ponce, Fernando A (Committee member) / Smith, David J (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2021
Description
The advent of silicon, germanium, narrow-gap III-V materials, and later the wide bandgap (WBG) semiconductors, and their subsequent revolution and enrichment of daily life begs the question: what is the next generation of semiconductor electronics poised to look like? Ultrawide bandgap (UWBG) semiconductors are the class of semiconducting materials that possess an electronic bandgap (EG) greater than that of gallium nitride (GaN), which is 3.4 eV. They currently consist of beta-phase gallium oxide (β-Ga2O3 ; EG = 4.6–4.9 eV), diamond (EG = 5.5 eV), aluminum nitride (AlN; EG =6.2 eV), cubic boron nitride (BN; EG = 6.4 eV), and other materials hitherto undiscovered. Such a strong emphasis is placed on the semiconductor bandgap because so many relevant electronic performance properties scale positively with the bandgap. Where power electronics is concerned, the Baliga's Figure of Merit (BFOM) quantifies how much voltage a device can block in the off state and how high its conductivity is in the on state. The BFOM has a sixth-order dependence on the bandgap. The UWBG class of semiconductors also possess the potential for higher switching efficiencies and power densities and better suitability for deep-UV and RF optoelectronics. Many UWBG materials have very tight atomic lattices and high displacement energies, which makes them suitable for extreme applications such as radiation-harsh environments commonly found in military, industrial, and outer space applications. In addition, the UWBG materials also show promise for applications in quantum information sciences. For all the inherent promise and burgeoning research efforts, key breakthroughs in UWBG research have only occurred as recently as within the last two to three decades, making them extremely immature in comparison with the well-known WBG materials and others before them. In particular, AlN suffers from a lack of wide availability of low-cost, highquality substrates, a stark contrast to β-Ga2O3, which is now readily commercially available. In order to realize more efficient and varied devices on the relatively nascent UWBG materials platform, a deeper understanding of the various devices and physics is necessary. The following thesis focuses on the UWBG materials AlN and β-Ga2O3, overlooking radiation studies, a novel device heterojunction, and electronic defect study.
ContributorsMontes, Jossue (Author) / Zhao, Yuji (Thesis advisor) / Vasileska, Dragica (Committee member) / Goodnick, Stephen (Committee member) / Sanchez Esqueda, Ivan (Committee member) / Arizona State University (Publisher)
Created2021