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Recent Submissions

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The Power of Experimental Approaches to Social Choice
(University of Waterloo, 2025-02-14) Armstrong, Ben
With increasing connectivity between humans and the rise of autonomous agents, group decision-making scenarios are becoming ever more commonplace. Simultaneously, the requirements placed upon decision-making procedures grow increasingly nuanced as social choices are made in more niche settings. To support these demands, a deeper understanding of the behaviour of social choice procedures is needed. The standard theoretical approach to analyze social choice procedures is limited in the type of question it can answer. Theoretical analyses can be rigid: It may speak to the incompatibility of different properties without also providing a deeper understanding of the properties themselves, or might stop at proving the worst-case outcome of a voting rule without communicating the rule's typical behaviour. In this dissertation, we address these limitations by demonstrating that experimental analysis of social choice domains can provide an understanding of social choice which is both complementary and additional to theoretical findings. In particular, experimental approaches can form a middle ground between theory and practice: more practical than theoretical approaches in a setting more controlled than real-world application. We apply this approach to a new form of delegative voting and to a task of learning existing and novel voting rules. In each area we find results of a type and scale which are infeasible to traditional analysis. We first examine an abstract model of delegative voting -- agents use liquid democracy to transitively delegate their vote -- in a setting where the voters collectively agree on a correct outcome. Through extensive simulations we show the dynamic effects on group accuracy from varying a wide range of parameters that collectively encompass many types of human behaviour. We identify two features of this paradigm which result in improvements to group accuracy and highlight a possible explanation for their effectiveness. Subsequently, we apply this liquid democracy framework to the process of training an ensemble of classifiers. We show that the experimental findings from our simulations are largely maintained on a task involving real-world data and result in further improvements when considering a novel metric of the training cost of ensembles. Additionally, we demonstrate the creation of a robust framework for axiomatic comparison of arbitrary voting rules. Rather than proving whether individual rules satisfy particular axioms, we establish a framework for showing experimentally the degree to which rules general satisfy sets of axioms. This enables a new type of question -- degrees of axiom satisfaction -- and provides a clear example of how to compare a wide range of single and multi-winner voting rules. Using this framework, we develop a procedure for training a model to act as a novel voting rule. This results in a trained model which realizes a far lower axiomatic violation rate than most existing rules and demonstrates the possibility for new rules which provide superior axiomatic properties.
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A Multi-Phase Analysis of Gas Dynamics and Perturbations in the Galaxy Cluster Cores
(University of Waterloo, 2025-02-14) Li, Muzi
This thesis provides a detailed analysis of gas kinematics and their interactions across various phases within galaxy cluster cores. It examines the processes that generate gas perturbations and the factors that contribute to the thermal stability of the intracluster medium (ICM). A focus is placed on exploring the origins of multi-phase gas and the mechanisms—particularly AGN feedback—that either couple or decouple their motions. Radio-mechanical AGN feedback is identified as one of the most promising heating mechanisms that prevent the cooling of gas. However, the debate on the details of the heating transport processes has remained open. The atmospheres of 5 cool-core clusters, Abell 2029, Abell 2107, Abell 2151, RBS0533 and RBS0540, have short central cooling times but little evidence of cold gas, and jet-inflated bubbles. The amplitudes of gas density fluctuations were measured using a new statistical analysis of X-ray surface brightness fluctuations within the cool cores of these ‘spoil’ clusters in Chapter 2. The derived velocities of gas motions, typically around 100 - 200 km/s, are comparable to those in atmospheres around central galaxies experiencing energetic feedback, such as in the Perseus Cluster, and align well with the turbulent velocities expected in the ICM. Regardless of the mechanisms driving these perturbations, turbulent heating appears sufficient to counteract radiative losses in four of the five spoiler cluster cores. We thus suggest that other mechanisms, such as gas sloshing, may be responsible for generating turbulence, offering a plausible solution to suppress cooling in these structureless atmospheres. Multiphase filaments, key byproducts of AGN feedback, are frequently observed near central galaxies, with their morphologies and kinematics closely linked to bubbles. In Chapter 3, we analyzed the velocity structure functions (VSFs) of warm ionized gas and cold molecular gas, identified through [OII] emission and CO emissions observed by the Keck Cosmic Web Imager (KCWI) and the Atacama Large Millimeter/submillimeter Array (ALMA), respectively, in four clusters: Abell 1835, PKS 0745-191, Abell 262, and RXJ0820.9+0752. Excluding Abell 262, where gas forms a circumnuclear disk, the remaining clusters exhibit VSFs steeper than the Kolmogorov slope. The VSFs of CO and [OII] in RXJ0820 and Abell 262 show close alignment, whereas in PKS 0745 and Abell 1835, were differentiated across most scales, likely due to the churning caused by the radio-AGN. The large-scale consistency in Abell 1835 and RXJ0820, together with scale-dependent velocity amplitudes of the hot atmospheres obtained from Chandra X-ray data, may support the idea of cold gas condensation from the hot atmospheres. X-ray observations have previously been constrained by low energy resolution, which has impeded direct measurements of velocity fields in galaxy clusters. However, the recent release of initial data from the X-ray Imaging and Spectroscopy Mission (XRISM) provides a non-dispersive energy resolution of about 5 eV, facilitating the measurement of line broadening and shifts. In Chapter 4 of this thesis, I detail my contributions to calibrating the optical blocking filters for XRISM using synchrotron beamlines at the Canadian Light Source (CLS) and Advanced Light Source (ALS) prior to its launch, and I discuss the model-based estimation of the parameters of the calibrated filters. This capability for direct measurement of plasma velocities is expected to greatly improve our understanding of the ICM dynamics with high accuracy.
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From For To With: Towards an Allographic Approach in Architecture
(University of Waterloo, 2025-02-13) Fournier, Marc-
Although transformations to buildings are inevitable, architecture often aims to achieve idealized, finalized artifacts that refute the passage of time. This professional bias towards temporality – or the problem of permanence – creates and perpetuates non-reciprocal relationships between architects, users, and the built environment that often results in the exploitation and alienation of the people the discipline attempts to serve. By examining architecture's failure to account for diverse temporalities, this research sheds light on the ways in which architects overlook their potential to cultivate meaningful social interactions with the built environment. The architect’s role, therefore, needs to be redefined as a translator of collective desires and needs, as a designer of structures that promote agency and empower individuals to engage with their environments. This paradigm shift implies an inquiry into the architect’s conventional design apparatus and the expansion of its scope to include tools that embrace temporality and contingency as key variables. The thesis proposes a shift in focus from the production of artifacts to the design of architectural scores inspired by allographic arts. Allographic thinking shifts the emphasis from end product to process; forcing a renegotiation of author-designer / performer-user relationships, focusing on affordances and obstacles, favoring user agency, and embracing contingency. The context of the Habitations Jeanne-Mance, a post-war social housing in Montréal, acts as a case study for an exploration of the disciplinary problems of permanence, alienation, and non-reciprocity, as well as the testing ground for a speculative design intervention that integrates allographic thinking into architecture to create a system that promotes user participation, indeterminacy, and reciprocal relationships between residents and their built environment.
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Learning-Based Safety-Critical Control Under Uncertainty with Applications to Mobile Robots
(University of Waterloo, 2025-02-13) Aali, Mohammad
Control theory is one of the key ingredients of the remarkable rise in robotics. Due to technological advancements, the use of automated robots, which was once primarily limited to industrial and manufacturing settings, has now expanded to impact many different parts of everyday life. Various control strategies have been developed to satisfy a wide range of performance criteria arising from recent applications. These strategies have different characteristics depending on the problem they solve. But, they all have to guarantee stability before satisfying any performance-driven criteria. However, as robotic technologies become increasingly integrated into everyday life, they introduce safety concerns. For autonomous systems to be trusted by the public, they must guarantee safety. In recent years, the concept of set invariance has been incorporated into modern control strategies to enable systematic safety guarantees. In this thesis, we aim to develop safety-critical control methods that can guarantee safety while satisfying performance-driven requirements. In the proposed strategies, we considered formal safety guarantees, robustness to uncertainty, and computational efficiency to be the highest design priorities. Each of them introduces new challenges which are addressed with theoretical contributions. We selected motion control in mobile robots as a use case for proposed controllers which is an active area of research integrating safety, stability, and performance in various scenarios. In particular, we focused on multi-body mobile robots, an area with limited research on safe operation. We provide a comprehensive survey of the recent methods that formalize safety for the dynamical systems via set invariance. A discussion on the strengths and limitations of each method demonstrates the capabilities of control barrier functions (CBFs) as a systematic tool for safety assurance in motion control. A safety filter module is also introduced as a tool to enforce safety. CBF constraints can be enforced as hard constraints in quadratic programming (QP) optimization, which rectifies the nominal control law based on the set of safe inputs. We propose a multiple CBF scheme that enforces several safety constraints with high relative degrees. Using the multi-input multi-output (MIMO) feedback linearization technique, we derive conditions that ensure all control inputs contribute effectively to safety. This control structure is essential for challenging robotic applications requiring multiple safety criteria to be met simultaneously. To demonstrate the capabilities of our approach, we address reactive obstacle avoidance for a class of multi-body mobile robots, specifically tractor-trailer systems. The lack of fast response due to poor maneuverability makes reactive obstacle avoidance difficult for these systems. We develop a control structure based on a multiple CBFs scheme for a multi-steering tractor-trailer system to ensure a collision-free maneuver for both the tractor and trailer in the presence of several obstacles. Model predictive control serves as the nominal tracking controller, and we validate the proposed strategy in several challenging scenarios. Although the CBF method has demonstrated a great potential for ensuring safety, it is a model-based method and its effectiveness is closely tied to an accurate system model. In practice, model uncertainty compromises safety guarantees and may lead to conservative safety constraints, or conversely, allow the system to operate in unsafe regions. To address this, we explore developing safety-critical controllers that account for model uncertainty. Achieving this requires combining the theoretical guarantees of model-based methods with the adaptability of data-driven techniques. For this study, we selected Gaussian processes (GPs) which bring together required capabilities. It provides bounds on the posterior distribution, enabling theoretical analysis, and producing reliable approximations even with a low amount of training data, which is common in data-driven control. The proposed strategy mitigates the adverse effects of uncertainty on high-order CBFs (HOCBFs). A particular structure of the covariance function is designed that enables us to convert the chance constraints of HOCBFs into a second-order cone constraint, which results in a convex constrained optimization as a safety filter. A discussion on the feasibility of the resulting optimization is presented which provides the necessary and sufficient conditions for feasibility. In addition, we consider an alternative approach that uses matrix variate GP (MVGP) to approximate unknown system dynamics. A comparative analysis is presented which highlights the differences and similarities of both methods. The proposed strategy is validated on adaptive cruise control and active suspension systems, common applications in mobile robots. This study next explores the safety of switching systems, focusing on cases where system stability is assured through control Lyapunov functions (CLFs) and CBFs are applied for safety. We show that the effect of uncertainty on the safety and stability constraint forms piecewise residuals for each switching surface. We introduce a batch multi-output Gaussian process (MOGP) framework to approximate these piecewise residuals, thereby mitigating the adverse effects of uncertainty. We show that by leveraging a specific covariance function, the chance constrained safety filter can be converted to a convex optimization, that is solvable in real-time. We analyze the feasibility of the resulting optimization and provide the necessary and sufficient conditions for feasibility. The effectiveness of the proposed strategy is validated through a simulation of a switching adaptive cruise control system.
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Long-term biophysical conditions and carbon dynamics of a temperate swamp in Southern Ontario, Canada
(University of Waterloo, 2025-02-13) Afolabi, Oluwabamise Lanre
In Canada, wetlands cover a land area of 1.5  106 km2 and store ~129 Pg C. However, the carbon (C) cycling of swamps has been understudied even though they store substantial quantity of C in their biomass and can also accumulate peat. In particular, southern Ontario swamps are estimated to hold ~1.1 Pg C under distinct hydroclimatic conditions. Previous studies on temperate swamp C fluxes were mostly based on short-term (<5 years) field measurements that limit our understanding of the multi-decadal dynamics that exist between this ecosystem’s C flux and biophysical conditions. To elucidate the long-term interactions and feedbacks that are important to temperate swamp C dynamics, a process-based model (CoupModel) was used to simulate plant processes, energy, water and C fluxes in one of the most well-preserved swamps in southern Ontario over 78-year period (1983–2060). CoupModel reasonably simulated the C flux and controlling variables when validated with compiled historic field measurements (1983–2023) with coefficient of determination (R2) values of 0.60, 0.95 & 0.61 for soil respiration, surface soil temperature (0–5 cm) and water table level (WTL). Systematic calibration of the initialized model for Beverly Swamp with the Generalized Likelihood Uncertainty Estimation (GLUE) approach moderately reduced the uncertainty associated with modelling processes and assisted in identifying the important parameters that greatly influence temperate swamp C flux simulations. Plant-related processes and hydrological variables exerted the strongest control on the simulation of carbon dioxide (CO2) efflux through soil respiration. The forcing of the GLUE calibrated CoupModel with an ensemble of climate projections downscaled from earth system models (ESMs) under shared socio-economic pathway (SSP5) by mid-century (2060) produced a decline in the swamp’s C uptake capacity as net ecosystem exchange (NEE) of CO2. Relative to the reference period of 1983–2002, the projected increase in mean air temperature (4.3 ± 0.8 oC) and precipitation (0.2 ± 0.1 mm) by 2050s triggered increase in 5 cm deep soil temperature, vapor pressure deficit, and evapotranspiration at Beverly Swamp. These changes to the swamp’s thermal and hydrological conditions dropped its WTL and VMC. Consequently, drier and warmer conditions raised the swamp’s CO2 efflux through ecosystem respiration, while its GPP moderately increased. These bidirectional feedbacks contributed to a reduction in the swamp’s net C uptake (NEE) by the 2050s but it mostly still maintained its net C sink role. While uncertainty in future climate projections and model fit limit our confidence in the precise estimate of future carbon exchange, it was clear that seasonal timing of warming and precipitation played an important role in the swamp response, with coincident declines in precipitation and warming temperatures in summer that caused water stress for plants. Results from this long-term study will help improve our understanding of the important ecohydrological interactions and feedbacks that drive the C cycle of temperate swamps, and their contributions to regional terrestrial C and water cycles. This will help inform decision making on the role of swamp peatlands as nature-based climate solutions through improved understanding of their net C exchange with the atmosphere.