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Cornell Theses and Dissertations

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The theses and dissertations of graduate students at Cornell University have been deposited in Cornell's institutional repository (eCommons) since about 2004. This collection also includes a few earlier Cornell theses.

Students retain ownership of the copyright of their work. Students also have the option of imposing a temporary embargo on access to the full text of their theses for limited amount of time (see eCommons access policy). If access to a thesis is restricted, the metadata record for the thesis is still visible, but the text "Access to Document Restricted" is displayed, and a field labeled "No Access Until," which indicates the date when the full text of the thesis will become accessible.

More information about finding Cornell theses and dissertations is available on this library guide, and the eCommons help page for finding content in specific collections, including theses and dissertations.

In general, older theses and dissertations from Cornell University are not currently available as digital files in eCommons. The Library is willing to digitize and make available older Cornell theses on a cost recovery basis. If you are interested in this service, please contact dcaps@cornell.edu.

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    Learning with classical and quantum information constraints
    Liu, Yuhan (2024-12)
    In modern data analysis, data may not always be fully accessible to analysts, potentially due to social concerns or physical restrictions. Since data may be costly to acquire, it is important to design data-efficient algorithms under information restrictions. This thesis establishes a general framework for proving the fundamental limit of information-constrained learning and designs sample-optimal algorithms under settings of practical interest. We consider various information constraints, including privacy and communication constraints on classical computers, and inherent randomness governed by the laws of physics in quantum computers. First, we study distribution learning and testing with local information constraints such as local differential privacy (LDP) and communication constraints. We derive a general lower-bound framework for interactive communication protocols. The techniques and ideas in this part lay the foundation for the quantum part. We then investigate user-level information constraints, a practical setup where each user or device may hold multiple samples. We design the first optimal algorithms for distribution estimation under central differential privacy. Finally, we demonstrate how prior ideas for classical problems surprisingly translate to the quantum world. Extending techniques for classical distribution testing, we propose a unified lower-bound framework for quantum state testing with restricted unentangled measurements. As a result, we derive the first known tight sample/copy complexity bounds for finite-outcome unentangled measurements and demonstrate the power of randomness in quantum state testing.
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    ON MULTIPARTITE ENTANGLEMENT AND ITS USE
    Philip, Aby (2024-12)
    Entanglement is a unique feature of quantum mechanics. Over the years, we have understood bipartite entanglement a lot more, while our understanding of multipartite entanglement has lagged. In this work, we aim to fill some gaps in this knowledge. Firstly, we provide a quantum algorithm to test whether a given multipartite state is multipartite entangled or multipartite separable. To develop this separability test, we start with a separability test for the bipartite scenario using the quantum steering effect. Our separability test consists of a distributed quantum computation involving two parties: a computationally limited verifier, who prepares a purification of the state of interest, and a computationally unbounded prover. We then modified the separability test to get a variational quantum steering algorithm (VQSA), implementable on quantum computers that are available today. We then simulate our VQSA on noisy quantum simulators and find favorable convergence properties on the examples tested. We extend our separability test to the multipartite scenario by using the appropriate definitions. We expect that multipartite entanglement will find use in quantum network scenarios. Quantum networks consist of various quantum technologies, spread across vast distances, and involve various users at the same time. Certifying the functioning and efficiency of the individual components is a task that is well studied and widely used. However, the power of quantum networks can only be realized by integrating all the required quantum technologies and platforms across numerous users. In this work, we demonstrate how to certify the distillable entanglement available in multipartite states produced by quantum networks, without relying on the physical realization of its constituent components. We do so by using the paradigm of device independence. Finally, we introduce multipartite intrinsic non-locality as a method for quantifying resources in the multipartite scenario of device-independent (DI) conference key agreement. We prove that multipartite intrinsic non-locality is additive, convex, and monotone under a class of free operations called local operations and common randomness. As one of our technical contributions, we establish a chain rule for two variants of multipartite mutual information, which we then use to prove that multipartite intrinsic non-locality is additive. This chain rule may be of independent interest in other contexts. All of these properties of multipartite intrinsic non-locality are helpful in establishing the main result: multipartite intrinsic non-locality is an upper bound on secret key rate in the general multipartite scenario of DI conference key agreement.
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    Software-Oriented Hardware Prefetching and Vector Execution
    Adit, Neil (2024-12)
    The hardware-software abstraction enables programmers to write high-level algorithms without delving into low-level microarchitectural details. Compilers, positioned at the interface of hardware and software, perform numerous optimizations to enhance performance. Nonetheless, their functionality is limited by the ISA contract designed by hardware developers. Rethinking this abstraction can unlock powerful optimizations at the compiler stage. For instance, emerging scalable vector ISAs expose hardware vector length as a programmable constant to the software, which, with compiler support, can improve vectorization opportunities in addition to code portability. Additionally, hardware prefetchers come with software prefetching knobs to leverage programmer knowledge for performance gains. However, this control is limited, unable to influence dynamic prefetching decisions made by the hardware, which has been shown to cause performance regression in datacenter settings. This thesis aims to enhance compiler-guided optimizations for autovectorization and hardware prefetching. The auto-vectorization evaluation identifies compiler shortcomings with scalable vector ISAs, and proposes ScaleIR as a prototype, to improve mask representations in the LLVM IR. ProP uses profile-guided hints to better guide hardware prefetching decisions. Together, these projects enable compilers to effectively leverage and redefine the software-hardware abstraction, boosting performance and efficiency.
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    DESIGN AND CONTROL OF HIGH-PERFORMANCE WIDE-OPERATING-RANGE POWER CONVERTERS
    Gurara, Firehiwot (2024-12)
    As renewable energy systems and energy storage applications continue to expand, the demand for high-efficiency, high-power-density power converters capable of operating across wide voltage and power ranges has become increasingly critical. This thesis addresses these requirements by developing converter architectures, control strategies, and design methodologies to ensure compactness and high efficiency under wide operating conditions. First, to enable efficient energy harvesting from a solar thermoelectric generator (TEG), a multi-mode four-switch buck-boost dc-dc converter is proposed. Designed for a 5-15 V input, it efficiently delivers power to 3.7-V lithium-ion batteries and 5-V loads across four operational modes: buck, boost, buck with boost passthrough, and combined buck-boost. A 50-W prototype achieves an overall peak efficiency of 98.15%, utilizing optimized magnetics and robust gate drive circuitry. To enhance power density in ac-dc converters, a merged energy buffer architecture is also introduced in this thesis. This design incorporates series-stacked switchable capacitors for twice-line-frequency energy buffering. A simple control strategy, relying on the voltage of a single capacitor, ensures stable operation. A systematic optimization method reduces buffer volume by 17% in a 50-W/in³ 150-W LED driver. The thesis further investigates Impedance Control Network (ICN)-based converters for high-performance dc-dc and ac-dc power conversion applications. A bidirectional ICN-based dc-dc converter with a 200-400-V input and 12-V output employs a phase-shift control strategy to achieve near zero-current switching (ZCS), zero-voltage switching (ZVS), and output regulation. A 300-W converter prototype demonstrates a power density of 41 W/in³ with peak efficiencies of 93.7% and 93.3% during forward and reverse operation, respectively. A generalized phase shift control strategy is also developed for bidirectional ICN-based ac-dc converters to achieve power factor correction (PFC) and reactive power control. A 1.7-kW, universal input, 200-500-V output single stage ICN-based onboard electric vehicle charger prototype achieves a power density of 75 W/in³ and a peak efficiency of 93.5% and 92.4% during forward and reverse operation, respectively. Finally, the design and control of a dual-output ICN-based ac-dc converter is presented, enabling power delivery to both high-voltage and low-voltage output ports. The design methodology to optimally design this dual-output ICN converter is also presented. A 2-kW, universal input, prototype dual-output ICN-based ac-dc converter with 200-500 V and 9-15 V outputs achieves a power density of 60 W/in³.
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    NEURONAL CIRCUIT MECHANISMS UNDERLYING FOOD INTAKE IN DROSOPHILA MELANOGASTER
    Cui, Xinyue (2024-12)
    Proper regulation of food intake is essential for the survival of all animals, including humans. Although neural circuits that regulate food intake have been extensively investigated in rodent models, the entire sensorimotor circuits that regulate food intake have not been fully elucidated in any model organism. Previously, our lab has identified Ingestion Neuron 1 (IN1) as a regulator of food intake in adult Drosophila melanogaster (Yapici et al., 2016). Here, using optogenetics and two-photon calcium imaging, I revealed that IN1 neurons receive specific excitatory input from sugar-sensing enteric Gr43a neurons. We developed a new in vivo imaging method to record the activity of enteric neurons in behaving flies. Using this new method, we captured the acute response of Gr43a enteric neurons to sucrose ingestion and demonstrated that these neurons can activate IN1. In addition, I used the connectome of an entire adult fly brain to identify the major output neurons of IN1, crop innervating enteric motor (CEM) neurons. I showed that activation of CEM neurons can block the ingested food from entering the crop (a stomach-like organ). Furthermore, activation of IN1 neurons inhibits CEM neurons, allowing ingested food to be transported to the crop for storage, facilitating the later, slower process of regurgitation and digestion. Overall, my thesis research uncovered an IN1-centered sensory-motor neural circuit that acutely responds to the nutrient composition of ingested food, thereby directly influencing food ingestion in flies. By identifying this circuit's role in integrating sensory information from ingested nutrients, we have gained insights into the real-time mechanisms by which the fly brain assesses and adjusts food intake based on nutritional quality. I anticipate that our research will yield a more comprehensive understanding of how food intake is precisely regulated through complex interactions between the central brain and the enteric nervous system. This work not only sheds light on the fundamental neurobiology of feeding but also provides a foundation for exploring similar sensory-motor pathways in other organisms, potentially offering broader insights into appetite control and nutrient-based decision-making.
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    BAHHA: AN ANTHROPOLOGICAL RECEPTION HISTORY OF J. S. BACH IN JAPAN
    Cressy, Thomas (2024-12)
    Japan has produced some of the greatest performers and scholars of Johann Sebastian Bach’s music. Musicologist Isoyama Tadashi noted in 2003 that, almost every day in Japan there is a concert of Bach’s music somewhere, and recordings of his music and literature about him sell well. Since Masaaki Suzuki formed Bach Collegium Japan in 1990, he counted one to two-hundred amateur local choirs dedicated to Bach’s music springing up across the country. Bach, known in Japan as the “Father of Music,” and whose portrait hangs in the music classrooms of elementary and middle schools, has become a central figure in Japan’s musical modernity. This dissertation explores how and why. As a case study of global music history, this thesis ethnographically shows how music traditionally considered “Western” has been mediated by sociocultural configurations, forms of knowledge production, and contingent desires held by specific social actors in Japan. Perhaps most importantly, this study highlights the voices of Japanese musicians and scholars themselves and their global contributions to Bach. Beyond the passive “imitator of the West” tropes uncritically applied to Japan, I represent Japan as a “field” and elucidate wider global, institutional, historical, and sociocultural configurations that have afforded Japanese individuals opportunities to encounter Bach’s music, as well as the affordances that Bach as an idea and historical symbol offers them in turn. As an anthropological reception history of Japanese engagements with Bach’s music, my dissertation makes use of archival sources, interviews with scholars and musicians, ethnographic fieldwork, educational materials, Japanese musicological research, and music periodicals to further understand how and why Bach has featured in Japanese musical life for over a century.
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    BOTANICAL SPRAYS AND LOCAL WAYS: AN EXAMINATION OF PARTICIPATORY AGROECOLOGICAL PEST MANAGEMENT RESEARCH IN NORTHERN MALAWI
    Enloe, Stephanie (2024-12)
    This dissertation follows the evolution, outcomes, and social context shaping participatory research on homemade insecticidal plant extracts, otherwise known as botanical sprays. The project was embedded within a long-term, farmer-led initiative that advances agroecological knowledge and practice among smallholders in northern and central Malawi. The non-profit that leads this initiative – Soils Food and Healthy Communities – facilitates a farmer-to-farmer network that conducts participatory research, training events, and community dialogues. This study emerged in response to network members’ interest in rebuilding and strengthening practical knowledge of botanical sprays. Drawing on the fields of landscape and human ecology, political agroecology, and feminist political ecology, it discusses the material and social outcomes of participatory agroecological experimentation and considers how they are entangled with household and community knowledge politics. It demonstrates that homemade botanical sprays can effectively reduce pest pressure on maize and beans and that practice outcomes are influenced by landscape context. The dissertation offers insight into how farmers perceive and prioritize alternative paradigms for pest management. Taken together, these chapters reflect on the complexity and potential for participatory praxis and farmer-to-farmer approaches to enable food sovereign futures rooted in situated smallholder knowledge. It argues that scaling up agroecology requires participatory and transdisciplinary approaches that attend to the social processes of building situated knowledge.
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    Machine Learning Applications for Improving Accelerator Operations
    Lin, Lucy (2024-12)
    In this dissertation, we attempt to improve operation at particle accelerator facilities by applying various machine learning techniques to several key areas of acceleration operation for a particle accelerator, such as beam orbit control, beam quality measurement, and beam optimization. For complicated large scale machines such as accelerators, the inner mappings between control parameters and performance data are often only partially known, but they can be learned and simulated using machine learning methods without extensive physics understandings. In this dissertation, two major types of machine learning techniques were developed for and demonstrated on several accelerators located at Cornell University and Brookhaven National Laboratory: neural network design for constructing accurate mappings between control parameters and performance data, and optimization algorithm development for finding optimal operation parameters automatically. These successful applications show the benefits of integrating machine learning algorithms with accelerator control system, and build the foundation for including similar techniques in the ongoing development and construction of the Electron Ion Collider at Brookhaven National Laboratory.
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    Toxicity and Antibiotic Resistance Risk Assessment of Micropollutants Mixture in Drinking Water for Human Health Outcome
    Feng, Yinmei (2024-12)
    This dissertation investigates the occurrence, fate, and effects of mixture of organic micropollutants in water systems, emphasizing their roles in the induction of antibiotic resistance and toxicity, and their potential health implications. Current antibiotic resistance assessment assays predominantly rely on time-consuming culture-based or costly molecular methods. These approaches often incur high costs and may not align with current human health risk models for antibiotic resistance, underscoring the need for more efficient and representative testing methodologies. To address these challenges, this work introduces a novel screening method for assessing the antibiotic resistance potential. Integrating advanced molecular techniques and environmental engineering principles, this study provides comprehensive insights into the dynamics of mixture of micropollutants across various aquatic environments and their interactions with public health. First, a novel transcriptomics-based methodology is developed to assess the antibiotic resistance induction potential of water contaminants. Utilizing a GFP-fused E. coli ARG library, this approach enables the detailed examination of genetic expressions influenced by environmental pollutants, thereby advancing the understanding of antibiotic resistance mechanisms. Second, the study assesses the impacts of disinfection processes, specifically GAC treatment and its efficacy in mitigating disinfection byproducts and their toxic impacts. By employing genotoxicity bioassays, the study evaluates various water treatment methodologies, offering crucial insights into optimizing water quality while reducing potential health risks. Third, the study addresses the broader implications of disinfectants and DBPs on public health, with a particular focus on their roles in the induction of antibiotic resistance. This section provides evidence that continuous exposure to the mixture of DBPs can induce antibiotic resistance and reveal the potential mechanism. Last, the study explores the association between organic micropollutants in drinking water and human health, particularly focusing on phthalates and their correlation with adverse birth outcomes in North Puerto Rico. Through extensive sampling and analysis, this research establishes a link between environmental exposure and significant health effects, highlighting the urgent need for effective water treatment solutions. Collectively, this work not only enhances the scientific understanding of micropollutant dynamics but also informs policy-making and public health strategies, aiming to mitigate the risks associated with waterborne contaminants and improve global water quality.
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    Property in Transition: Architecture, Migration, and the Translation of Land Regimes in the Ottoman South Caucasus under the Russian Empire, 1877-1921
    Saricayir, Ecem (2024-12)
    Scholars in different disciplines have pointed out that land and property are key to understanding histories of imperialism, colonialism, and nation-building. However, architectural scholarship has only recently taken up the question of how land and property relations shape the built environment. Through transnational archival work and fieldwork, this dissertation looks at the intertwinement of imperialism, property, and architecture in the rarely studied South Caucasus. Focusing on the seldomly examined period of 1877-1921—from the annexation of the former Ottoman regions of Kars and Batumi by the Russian Empire to the dissolution of the Russian and Ottoman Empires and the emergence of nation-states in the region—this dissertation examines the material transformation and discursive production of the South Caucasus built and ruinated environment. After the Russian annexation, the borderlands of the South Caucasus became a center of power struggles where different imperialisms, as well as socialist and nationalist movements, overlapped and competed which resulted in rapid and consequential urban and rural developments, as well as archaeological excavations. The dissertation underscores how the reorganization of property relations in the region at times enabled capitalist urban and rural development and, at other times, played a role in resistance movements. It brings together underutilized legal and policy documents, property maps, title registers and deeds, court cases, architectural photographs, city plans, and site drawings, as well as the region’s remaining network of infrastructure, settlements, and buildings constructed at the turn of the twentieth century. Pursuing the late nineteenth-century metamorphosis of the region, this dissertation shows that the built and ruinated environment of the South Caucasus is a product of contestations over property and between property regimes during the period in which the region changed hands from the Ottoman to the Russian Empire. It brings together Russian, Eastern European, and Eurasian studies; Ottoman and Turkish studies; and postcolonial architectural scholarship around the questions of land and property.