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Recent Submissions
Knowing Language: The Poetics of Epistemology in Jan Zwicky, Paul Muldoon, and Geoffrey Hill
(University of Waterloo, 2025-05-16) Giannakopoulos, Christopher
This dissertation investigates the poetics of epistemology in the works of Jan Zwicky (1955-), Paul
Muldoon (1951-), and Geoffrey Hill (1932-2016), three contemporary poets who engage
epistemology by way of diverse interdisciplinary proxies. Principally, my dissertation shows that
in Zwicky, Muldoon, and Hill, poetry is not representative as a knowledge-producing discourse
but is instead meta-epistemological: as a cultural artefact of language that is exemplary for the
way it self-reflexively expresses epistemological themes (thinking, thought, knowledge, etc.),
poetry calls into question the stability of linguistic meaning by challenging the epistemological
assumptions and rhetorical commonplaces of other discourses on knowing—especially
philosophy (Zwicky), history (Muldoon), and theology (Hill)—discourses whose epistemological
foundations are based on a language-as-knowledge-producing model.
For Zwicky, the paradigm of “lyric philosophy” informs and is informed by the poem’s
capacity as a phenomenological gestalt, where poetry’s knowing occurs in a matrix of linguistic
resonances. Gestalt insight in Zwicky’s work relies for its rhetorical force on the lyric integration
of linguistic elements rather than on language’s formal logical procedures. Muldoon’s framework
for poetic knowing—and not-knowing, and un-knowing—is the result of an aesthetics of
encyclopedic reference, etymological punning, and intertextual allusion deployed in the form of
riddles. As a locus of facts, data, and information, knowing in Muldoon’s poetry is contingent on
the play and ply of both the locally synchronic and the intertextually diachronic aspects of the
language used to structure it. These riddling dynamics are indefinitely played out in Muldoon’s
work, where reference and ambiguity as competing linguistic forces together constitute an
interminable weaving and unweaving of epistemological multiplicities. In Hill’s work, knowing is
disclosed negatively through a variety of apophatic tropes: combined with an aesthetics of
theological sublimity as well as the ethical demand for responsible language, Hill’s poetry
expresses knowing as an apophatic epistemological mystery.
Poems accomplish this interdisciplinary thinking about knowing through their resistance
to the rhetorics of representation, thematization, and closure, all of which are central features of
epistemological discourses that work to reveal, establish, or reinforce truth claims. In Zwicky,
Muldoon, and Hill, poetry complicates, problematizes, and resists the ontological simplifications
implied by the language-as-knowledge-producing model of epistemological discourse. By
exploring the paradigmatically gestalt, riddling, and apophatic qualities of poetry, this
dissertation provides insight into the contingencies of linguistically-derived truth, offering a view
of poetry not as an expression of knowledge but as “knowing language”.
What Slows Down FMware Development? An Empirical Study of Developer Challenges and Resolution Times
(University of Waterloo, 2025-05-16) Wang, Zitao
Foundation Models (FMs), such as GPT-4, have revolutionized software engineering by enabling the development of FMware — applications and infrastructures built around these
powerful models. Despite their transformative potential, FMware solutions face significant
challenges in their development, deployment, and maintenance, particularly across cloudbased and on-premise platforms; this is because many of the goals, processes, tools, and
technical assets of FMware development are different from those of traditional software
systems. This study presents an empirical investigation of the current FMware ecosystem,
focusing on three key questions: (1) what topics are most prevalent in issue discussions of
FMware systems, (2) what specific challenges are commonly faced by FMware developers,
and (3) what kinds of issues in FMware development have the longest resolution times?
Our analysis uses data extracted from both GitHub repositories of FMware systems as
well as systems hosted on popular FMware platforms such as HuggingFace, GPTStore,
Ora, and Poe. Our findings reveal a strong emphasis on education, content creation, and
business strategy, alongside critical technical challenges such as memory errors, dependency management, and tokenizer configurations. We further identify bug reports and
core functionality issues as the most common problem types on GitHub, and show that
topics concerning code review, similarity search, and prompt template design require the
longest time to resolve. By uncovering insights into developer practices and pain points,
this research highlights opportunities for improving FMware development tools, workflows,
and community support. These insights contribute to a deeper understanding of the current FMware landscape and provide actionable recommendations for practitioners and
researchers.
High-Frame-Rate Ultrasound Characterization of Carotid Pulse Waves to Assess Cerebrovascular Resistance
(University of Waterloo, 2025-05-16) Hsu, Yi Han
Objective: Devise an ultrasound imaging framework for cerebrovascular resistance assessment by characterization of carotid pulse waves.
Background: The resistance of cerebrovasculature regulates blood flow to the brain that could serve as a biomarker for detection of early dementia. The onset of dementia, leading to higher cerebrovascular resistance (CVR), is theorized as the cerebrovascular damage due to elevated pulse pressure, one heartbeat at a time. The increased pulse pressure causes mechanical stress to the cerebral microvasculature as it propagates into the brain and alters cerebral hemodynamics. This change in cerebral hemodynamics can be explained from the classical Ohm’s law, whereby resistance is the ratio of potential difference (pressure) to current (blood flow). In fact, early dementia patients were identified with higher CVR in several brain regions. CVR can be assessed by measuring the pulse pressure wave and blood flow wave present in the carotid artery during each cardiac contraction. The forward pulse wave propagates along the carotid artery to the brain and is partially reflected back to the heart when encountering a change in resistance in the brain. Higher CVR affects the reflected pulse wave and, accordingly, alters the measured pulse wave in the carotid artery with distinct characteristics such as greater amplitude, broader peak, and higher pulse wave velocity. By examining the forward and reflected pulse wave, pressure and flow information can be acquired and in turn assess CVR.
Proposed Solution: To assess CVR from the carotid, an ultrasound imaging framework is proposed due to its low-cost and high accessibility compared to fMRI and PET. This ultrasound framework is developed based on high-frame-rate ultrasound (HiFRUS) paradigm with frame rate up to 10k frame per second. HiFRUS enables the estimation of blood flow velocity and the capture of transient pressure dynamics in the carotid artery where conventional ultrasound cannot achieve. To realize the innovation, four research modules will be pursued: (1) to separate the pulse waves into forward and reflected pulse wave, a wave separation algorithm is developed. (2) to characterize the separated pulse waves, a sensitive analysis was performed by manipulating downstream resistance in vitro study. (3) to transit in vitro to in vivo study, a motion-compensation algorithm was developed. (4) to assess CVR by the pulse wave in the carotid artery, an in-vivo study will be conducted.
Impact: This thesis establishes the feasibility of assessing CVR through our proposed pulse wave analysis platform, providing a new method for researchers to investigate new possibilities in the dementia fields. Future work will benchmark our approach against the established imaging methods.
Reduced-Order Modeling and Data Assimilation of the El Niño–Southern Oscillation
(University of Waterloo, 2025-05-16) Aydogdu, Yusuf
Simulations of complex fluid dynamics problems or climate models take weeks to complete even when run parallel in state-of-the-art supercomputers. Given computational resource constraints and the need for adaptable simulation settings, cost-efficient and accurate algorithms are essential. In this thesis, we explore stable, efficient, and accurate methodologies when applied to the El Niño–Southern Oscillation (ENSO), which integrates coupled atmosphere, ocean, and sea surface temperature (SST) mechanisms in the equatorial Pacific. ENSO is one of the most influential and complex climate phenomena, affecting weather patterns across the globe.
ENSO consists of irregular oscillations between warm (El Niño) and cold (La Niña) phases in the Pacific Ocean, significantly impacting global weather patterns. Due to ENSO's inherent complexity and uncertainties, it is particularly suited for stochastic modeling. By modeling these uncertainties, stochastic simulations offer a more accurate representation of ENSO's variability, including its irregular periods and amplitudes. We first study the effects of stochastic perturbations on ENSO dynamics and introduce novel modeling and numerical schemes based on the Wiener Chaos Expansion (WCE). The key idea behind WCE is the explicit discretization of white noise through Fourier expansion. We also compare these methods with Monte Carlo (MC) simulations. Our findings demonstrate that the simulation of the linear stochastic ENSO model driven by the Ornstein-Uhlenbeck process using WCE requires far less computational resources and gives more accurate results compared to MC ensembles. This part of the thesis provides an alternative efficient approach for simulations of stochastic climate models and quantification of statistical moments,i.e, mean and variance.
In the next stage of this research, we explore a reduced-order modeling (ROM) framework based on the POD-Galerkin method when applied to a nonlinear ENSO model. POD-Galerkin reduced order modeling aims to reduce the computational complexity and present high-dimensional problems~(usually PDEs) with reduced-order equations (ODEs). POD modes are optimal in capturing the system’s dominant
features, making it particularly effective for reducing the dimensionality of systems governed by PDEs. By capturing the full-order ENSO (PDE) model with only four modes and four reduced-order equations, we achieve a substantial reduction in computational complexity without significant loss of accuracy. Due to the special properties of the model, we introduce a novel approach using different POD bases, but the same time coefficients for all model components. Moreover, we employ machine learning methods to explore different ROM and model discovery techniques in this part.
The final part of this thesis focuses on the data assimilation of the nonlinear stochastic ENSO model, which forms the core results of this research. We first demonstrate the validity of POD-Galerkin reduced order modeling for the stochastic ENSO driven by the Ornstein-Uhlenbeck process. We project SPDEs onto POD modes derived from the deterministic model and introduce the reduced-order stochastic equations (SDEs). After setting up the filtering framework, we combine these equations and artificial observations in the Pacific ocean, based on realistic experiments, to estimate the ENSO-related SST anomalies. We employ particle filters and test the efficiency using different number of particles and ensembles. From novel ENSO modeling to uncertainty quantification, from reduced order modeling to nonlinear filtering, this thesis provides a promising approach for accurate and efficient predictions of ENSO-related climate variables.
Synchronous and quantum games: Graphical and algebraic methods
(University of Waterloo, 2025-05-15) Goldberg, Adina
This is a mathematics thesis that contributes to an understanding of nonlocal games as formal objects. With that said, it does have connections to quantum physics and information theory.
Nonlocal games are interactive protocols modelling two players attempting to win a game, by answering a pair of questions posed by the referee, who then checks whether their answers are correct. The players may have access to a shared quantum resource state and may use a pre-arranged strategy. Upon receiving their questions, they can measure this state, subject to some separation constraints, in order to select their answers. A famous example is the CHSH game of [Cla+69], where making use of shared quantum entanglement gives the players an advantage over using classical strategies.
This thesis contributes to two separate questions arising in the study of synchronous nonlocal games: their algebraic properties, and their generalization to the quantum question-and-answer setting. Synchronous games are those in which players must respond with the same answer, given the same question. First, we study a synchronous version of the linear constraint game, where the players must attempt to convince the referee that they share a solution to a system of linear equations over a finite field. We give a correspondence between two different algebraic objects modelling perfect strategies for this game, showing one is isomorphic to a quotient of the other. These objects are the game algebra of [OP16] and the solution group algebra of [CLS17]. We also demonstrate an equivalence of these linear system games to graph isomorphism games on graphs parameterized by the linear system.
Second, we extend nonlocal games to quantum games, in the sense that we allow the questions and answers to be quantum states of a bipartite system. We do this by quantizing the rule function, games, strategies, and correlations using a graphical calculus for symmetric monoidal categories applied to the category of finite dimensional Hilbert spaces. This approach follows the overall program of categorical quantum mechanics. To this generalized setting of quantum games, we extend definitions and results around synchronicity. We also introduce quantum versions of the classical graph homomorphism [MR16] and isomorphism [Ats+16] games, where the question and answer spaces are the algebras representing the “vertices” of quantum graphs, and we show that quantum tensor strategies realizing perfect correlations for these games correspond to morphisms between the underlying quantum graphs.