UWSpace

UWSpace is the University of Waterloo’s institutional repository for the free, secure, and long-term home of research produced by faculty, students, and staff.

Depositing Theses/Dissertations or Research to UWSpace

Are you a Graduate Student depositing your thesis to UWSpace? See our Thesis Deposit Help and UWSpace Thesis FAQ pages to learn more.

Are you a Faculty or Staff member depositing research to UWSpace? See our Waterloo Research Deposit Help and Self-Archiving pages to learn more.

Photo by Waterloo staff

Communities in UWSpace

Select a community to browse its collections.

Recent Submissions

  • Thumbnail Image
    Item type: Item ,
    Content-Aware Pixel Art Rendering on Pixels of Multiple Shapes
    (University of Waterloo, 2026-06-23) Wang, Zane Z.
    Pixel art is a well studied art form that arose from technical limitations on computing hardware in the early 1980s. Although the discipline itself is often associated with video games, standalone character and landscape portraits in the pixel art style are also popular. Characterized by a deliberately limited resolution and colour palette, pixel art is as an artistic exercise in the conveyance of visual information with a limited number of samples, while avoiding certain unpleasant visual artifacts. In this thesis, we present a first solution to a novel problem in computer graphics: how do we render images in the pixel art style on other tilings of the plane besides the usual squares, all while respecting image features? We formulate the non-square (or "any-shape") pixel art rendering task as an energy minimization problem over tile-shaped filter supports, given a conventional raster image and geometric tiling data as input. We compute tile energy gradients via rasterization of the tiling geometry; using this information, we evolve an optimal filter support shape while imposing geometric constraints to balance between distortion and feature clarity. We then demonstrate that our method produces images with superior qualitative and quantitative properties in comparison with naive methods. Our program can compute finished images in seconds, and allows the user to watch the pixel art evolve in real time. We also provide some basic stylization and interaction features for artists, such as k-means colour quantization, colour palette generation in a perceptually uniform colour space, and brush-based vertex manipulation to adjust the shapes of the filter supports. This method has the potential to be useful in several artistic contexts, such as the creation of highly stylized portraiture and landscapes, and authoring of image and video for real hardware displays that use non-square pixels.
  • Thumbnail Image
    Item type: Item ,
    Exploring Inuvialuit youth food security experiences and supports in the Inuvialuit Settlement Region
    (University of Waterloo, 2026-06-23) Ramirez Prieto, Maria
    Background: The Inuvialuit Settlement Region (ISR) is in the Northwest Territories, Canada, and is the westernmost of the four Canadian Inuit regions. The ISR covers 906,430 km2 and includes six communities: Aklavik, Inuvik, Paulatuk, Sachs Harbour, Tuktoyaktuk, and Ulukhaktok. Today, Inuvialuit in the ISR are closely connected to and dependent on-the-land for physical, mental, spiritual, and emotional nourishment, which supports food security and well-being. Yet Inuvialuit youth face numerous barriers to participating in subsistence harvesting, and a growing body of literature documents a dietary shift away from country foods (CF) among younger generations. This is especially concerning as 69% of individuals aged 15 years or older in the ISR experience food insecurity. However, few studies have examined how Inuvialuit, including Inuvialuit youth, engage with CF and their relationships within the food web in relation to food security and well-being. While youth are the focus of the overall dissertation, Elders and families are also participants in this dissertation. Objectives: The purpose of this dissertation is to explore the web of relationships and experiences that shape the participation of Inuvialuit youth in the CF system, including the connection to the natural world, culture, and others, in order to generate community-driven evidence that fills gaps in the literature. Moreover, this dissertation aims to centre Inuvialuit knowledge holders through the co-production of knowledge, and use community based participatory action research (CBPAR) to conduct equitable and community-driven research. Methods: Using CBPAR, the studies in this dissertation employ diverse qualitative methods to conduct research with community members, including Community Research Leads (CRLs). Using a CBPAR approach provides an opportunity for research to move away from research on Indigenous communities to research with and for Indigenous communities and aligns itself with the National Inuit Strategy on Research. Photovoice, talking circles, and semi-structured interviews were used with purposive and snowball sampling of 11 Inuvialuit youth across all six ISR communities, 19 Elders in Aklavik, Paulatuk, Tuktoyaktuk, and Ulukhaktok, and nine families in Aklavik, Tuktoyaktuk and Ulukhaktok. Reflexive thematic analysis, using co-analysis methods, was used for all three studies. Results: Study 1 (Chapter 2) employed photovoice methodology, working with 11 youth participants who captured photographs of their CF experiences and shared ~5 photographs during semi-structured interviews. Through reflexive thematic analysis, our research team co-created five themes from the data: 1) CF supports Inuvialuit youth well-being; 2) preference for CF despite varied consumption and activity frequencies; 3) network of CF within communities; 4) strong foundational cultural knowledge and skills; and 5) cultural continuity. Study 2 (Chapter 3) brought together 10 youth from Study 1 and 19 Elders through talking circles to explore the relationship between youth, Elders, and intergenerational Inuvialuit knowledge (IK) transmission in relation to CF, food security, and well-being. In addition to semi-structured questions, photo-elicitation was used to initiate conversation between Elders and youth about the photograph’s subject matter and to invite storytelling (e.g., caribou harvest, goose roast for dinner). Our research team co-created four themes from the data: 1) fostering cultural connection and knowledge transmission through CF and family time; 2) emphasizing oral teachings as essential for well‑being; 3) recognizing the true cost of store‑bought food and goods; and 4) working together for community food security In Studies 1 and 2, family was identified as a crucial aspect of youth connection to CF and IK, in turn, supporting food security and well-being. As such, in Study 3 (Chapter 4), nine families (n = 28 participants) from Aklavik, Tuktoyaktuk, and Ulukhaktok were interviewed through semi-structured group interviews to explore the role of CF and family in the transmission of IK to support youth food security and well-being in the ISR. Our research team co-created four themes from the data: 1) learning on-the-land through experiences; 2) nourished by the land; 3) navigating barriers; and 4) the guiding principles for present and future generations’ well-being. Conclusion: Together, these studies examine Inuvialuit youth, Elders, and families’ experiences in the CF system, including identifying facilitators and barriers to accessing CF and IK. These studies make substantive contributions to the literature by documenting what Inuvialuit have long known – that CF is essential for youth, family, and community food security and well-being. Concurrently, these studies offer critical qualitative evidence that broadens the predominantly quantitative and store-bought-food-centered literature in the ISR. Adding to a growing body of literature, this research highlights that CF, along with the relationships it fosters with people, the land, culture, and community, supports food security while also nourishing the mind, body, and soul. This research employed a CBPAR approach, engaging community members at all stages of the research process and aligning with Inuit Tapiriit Kanatami’s National Inuit Strategy on Research and the Inuvialuit Regional Corporation’s ISR Research Data Strategy to ensure that Inuvialuit are included and respected as knowledge holders, thereby fostering respectful and beneficial research for Inuvialuit communities.
  • Thumbnail Image
    Item type: Item ,
    Effects of Noise on Optimization, Statistics, and Simulation of Quantum Systems
    (University of Waterloo, 2026-06-23) Duschenes, Matthew
    Understanding interactions between a system and its environment has consistently been at the centre of scientific studies. Indeed, environmental effects are far reaching and rich in behaviour, from heat baths leading to heat engines in thermodynamics, to non-conservative forces leading to dissipation in classical mechanics, to many-body interactions leading to emergent phenomena in statistical mechanics. As we transition from technologies based on classical phenomena, to technologies based on quantum phenomena, understanding system-environment interactions is the central challenge within quantum information sciences. These interactions arise frequently in quantum settings, due to intentional non-unitary dynamics as part of quantum algorithms, inherent random dynamics within chaotic systems, or unintentional environmental noise in the absence of error mitigation. It is thus essential to derive any underlying structure from these interactions, and to determine their implications on the viability of emerging quantum technologies. In this thesis, we conduct systematic analytical and numerical analyses of non-unitary dynamics. First, we study the practical effects of noise and experimental constraints on variational quantum algorithms. We find that objectives are initially robust to noise, and decrease exponentially with increased evolution time, before increasing polynomially with evolution time, due to an accumulation of errors. Second, we develop analytical tools to exactly compute statistics of ensembles of random quantum channels. Such formalisms allow us to derive hierarchies between ensembles, to define channel t-designs, and to show that generalized channel-design-induced concentration phenomena can occur. Third, we study distributions of probabilities of generalized measurement outcomes, given simulated noisy random quantum circuits. We develop an accurate and interpretable effective global noise model for these locally noisy distributions. Notably, we show that non-symmetric measurement distributions are multi-modal, whereas symmetric measurement distributions are uni-modal. Fourth, we propose and benchmark a classical simulation method, where measurement probabilities of states are represented by stochastic tensor networks, and non-unitary dynamics are represented by non-negative matrix factorizations. We conclude this thesis with a discussion of implications of the rich structures underlying non-unitary dynamics. We first interpret and provide examples and counter-examples of the utility of ensembles within channel-centric quantum algorithms. We proceed to discuss long term objectives posed by our studies, regarding constructing phase diagrams of optimization success, across ansatz expressiveness, noise scales, and system sizes. We also propose less passive applications of noise towards steering ensembles towards concentrated or non-concentrated behaviours. Finally, we raise questions of simulability of multi-modal distributions in the search for quantum versus classical advantage.
  • Thumbnail Image
    Item type: Item ,
    Head Kinematic Measurements and Finite Element Modeling of Canadian Armed Forces Operators Firing Three Long-Range Rifle Configurations
    (2026-06-12) Seeburrun, Tanvi; Hartlen, Devon C.; Bustamante, Michael B.; St-Onge, Gabriel; Ouellet, Simon; Cronin, Duane S.
    Mild traumatic brain injury (mTBI) symptoms have been associated with repeated exposure to the recoil of long-range rifles. However, there is limited physical data on head responses to rifle recoil and no consistent approach to quantitatively compare rifle configurations that may mitigate head response to recoil. In this study, the head kinematics of Canadian Armed Forces volunteers firing long-range rifles were measured and used as input to a finite element (FE) head model, enabling comparisons across different operators and rifle configurations. Head kinematics were measured with instrumented mouthguards for three rifle configurations: a 0.50 caliber rifle, a 0.338 caliber rifle, and a 0.338 caliber rifle with a recoil mitigation system (RMS). Measured head kinematics were used as input loading conditions to an FE head model to calculate brain tissue strains resulting from recoil, which were quantified using cumulative strain volume (CSV) curves. It was found that the 0.50 caliber rifle induced significantly higher strains than the 0.338 caliber rifle, while the RMS system reduced brain strain for the 0.338 caliber rifle. Characteristics such as differing anthropometrics, posture, or technique may influence brain strains, explaining the differences between volunteers. Isolating aspects of head kinematics, specifically rotation in the sagittal plane, identified it as having the largest contribution to brain strain. The findings from this study provide foundational data on the magnitudes of head kinematics experienced by volunteers when firing long-range rifles and serve as an important step toward mitigation of recoil exposures.
  • Thumbnail Image
    Item type: Item ,
    Scaling and generalization in neural quantum states
    (University of Waterloo, 2026-06-23) Moss, Megan Schuyler
    Because of their relevance to our understanding of quantum materials, the ground states of quantum many-body systems are a central object of study in condensed matter physics. However, the exponential growth of the Hilbert space with physical system size makes it difficult to study these states. Even with sophisticated numerical methods, we are often limited to studying finite-size systems that may not be representative of the thermodynamic limit, where properties of the system coincide with measurements of real materials. Scaling studies are therefore crucial for bridging the gap between what we can compute and what we want to understand. Quantum simulators, which are engineered and programmable quantum systems, offer an alternative approach to understanding quantum many-body systems. While these devices enable the direct preparation of certain quantum states, the need to verify the states prepared on these devices presents another exponentially difficult problem. The tools of modern deep learning, such as neural networks, have proven to be extraordinarily capable of extracting patterns in complex and high-dimensional data. Crucially, the learned patterns often correctly describe new data that the network was not exposed to during training, a phenomenon known as generalization. Despite belonging to exponentially large Hilbert spaces, quantum many-body ground states are often highly structured. Neural networks, which generalize precisely by learning and exploiting such structure, offer a promising approach to the problems of representing and characterizing such states. In this thesis, I focus on the use of neural networks to study the ground states of quantum many-body systems. When used in this context, neural networks are referred to as neural quantum states (NQS). Not only are NQS flexible and expressive ansätze, but they can be trained in different ways, depending on the information about the target state that is available. On the one hand, NQS can be trained with a data-driven approach, using measurement data from quantum simulators. We show that, because of their generalization abilities, NQS are poised to maximize the value of limited and imperfect data from experiments on today's quantum devices. On the other hand, NQS can be trained with a Hamiltonian-driven approach, which only requires knowledge of a system's Hamiltonian. Using this approach, we demonstrate how the generalization abilities of certain NQS architectures can be leveraged to enable efficient and accurate large-scale simulations of quantum many-body systems. Finally, we directly investigate generalization in the context of NQS, connecting our results to important observations in the broader machine learning research community. Together, these results demonstrate that the generalization abilities of NQS are not only essential for, but fundamentally linked to, their capacity to enable scalable studies of quantum many-body systems.