UWSpace

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Recent Submissions

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    From Asymptotic to Finite-Size Security in Decoy-State Quantum Key Distribution
    (University of Waterloo, 2026-03-24) Kamin, Lars
    Quantum Key Distribution (QKD) promises information-theoretic security, yet bridging the gap between theoretical proofs and practical implementations, specifically those operating with finite resources and imperfect devices against general coherent attacks, remains a critical challenge. This thesis develops a spectrum of efficient security proof techniques within the composable security framework, calculating key rates for both fixed- and variable-length protocols while accounting for realistic imperfections. We begin by addressing detection setups through an extension of a squashing map, the flag-state squasher, used for reducing the infinite-dimensional Hilbert spaces of optical elements to finite dimensions. This extension accommodates arbitrary passive linear optical setups while allowing for the inclusion of detection inefficiencies and dark counts in the security analysis. Subsequently, we advance the analysis of decoy-state protocols and introduce two major improvements. First, we reformulate the decoy-state analysis to recover no-decoy key rates, tightening the optimization. Second, we derive a unified framework that performs the key rate optimization and decoy analysis in a single step. This enables the bounding of the relevant entropies with arbitrary precision in the finite-size regime and successfully recovers the Devetak-Winter formula in the asymptotic limit. Furthermore, we improve the security analysis for generic QKD protocols against independent and identically distributed (IID) collective attacks. Our refined analysis yields finite-size corrections proportional to detected rather than transmitted signals and, by developing sharper concentration inequalities, achieves significantly improved finite-size scaling. Finally, leveraging the marginal constrained entropy accumulation theorem (MEAT), we establish a flexible numerical Rényi security framework against coherent attacks for both fixed- and variable-length protocols. This approach consistently outperforms existing reference proof techniques, including those based on entropic uncertainty relations, providing significantly higher key rates for both qubit and practically relevant decoy-state protocols. Moreover, we present finite-size key rates for generic QKD protocols accounting for realistic intensity and phase imperfections. Overall, this thesis provides the necessary theoretical framework to bridge the gap between idealized models and experimental reality, offering a scalable path toward secure quantum communication under realistic conditions, as demonstrated by the application of these techniques in experimental collaborations.
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    [UN]PREDICTABLE SUBURBIA: An Exploration of Rules, Representation, & Rigidity
    (University of Waterloo, 2026-03-23) Ma, Nhuy Cindy
    Suburbia presents itself as an uninspiring, homogenous landscape, where our personal lot lines define our boundaries of care. Characterized by detached houses with private gardens and fences, the controlled and uniform design of these spaces, which are rooted in historical policy, greatly limits potential for social and spatial complexity. As experts in charge of understanding the rules, guidelines, and best practices that dictate the design of urban zones, we often confront this entrenched reality, built through decades of regulatory frameworks. This thesis anchors itself within urbanism, exploring the boundaries and intersections between rules, guidelines, and suggestions. It tests various design methodologies that work within established frameworks of control to subvert suburban monotony and enable greater agency and complexity. Rather than rejecting urban rules outright, the research examines how both control and agency can coexist to produce varied and unexpected outcomes within a suburban context. Drawing upon the work of Michael Sorkin’s Local Code, Alex Lehnerer’s Grand Urban Rules, Ekim Tan’s Play the City, and Archizoom’s No Stop City, the thesis develops a novel, iterative design methodology combining analytical study with tests of agency and complexity. This method critically examines and reimagines urban rules through design experimentation aimed at uncovering new possibilities for suburban transformation. This thesis offers both a theoretical critique of suburban spatial and social homogeneity, as well as a practical methodology for designers to engage with and reshape suburban environments. By reframing suburbia as a space of controlled agency, this work encourages architectural and urban innovation within traditionally rigid, mono-programmatic landscapes. Thus, suburbia is positioned not as a fixed condition, but rather a mutable environment capable of supporting complexity and social diversity.
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    Measuring the Weak Gravitational Lensing Signal from Cosmic Voids
    (University of Waterloo, 2026-03-23) Martin, Hunter
    The field of cosmology is currently in an era principally focused on statistical precision. To achieve greater precision, deeper and wider surveys are actively being developed and conducted to gather more and more information about the surrounding cosmos. Alternatively, there are efforts to develop new statistical probes to better utilize currently-existing data to obtain tighter constraints. Cosmic voids, as vast underdense regions, then represent an ideal candidate to complement the statistical information already extracted from the opposite density extremes: massive luminous galaxies and galaxy clusters. Voids have already seen some success in constraining cosmology through probes like the void size function and void-galaxy cross-correlations. This thesis introduces the matter distribution within cosmic voids as measured by weak gravitational lensing as a new probe that is significantly detectable within current and future data sets. The goal of this demonstration is to justify future efforts in extracting the cosmological information from this newfound signal. For data currently available, we make use of the large overlap of the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS) and the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS). We measure void lensing around BOSS voids and find that we can detect the signal at 6.2 sigma significance, the most significant detection from spectroscopically-identified voids to date. We additionally are able to significantly detect differences in the void profile with void size between the larger half and smaller half of the void catalogue at 2.3 sigma. To help perform this measurement, we present and validate a novel method for computing the Gaussian component of the conventional weak lensing covariance, adapted for use with void studies. Comparing the void profile to a measurement of the void-galaxy cross-correlation to test the linearity of the relationship between mass and light, we find good visual agreement between the two, and a galaxy bias factor of 2.45 pm 0.36, consistent with other works. We additionally assist in future developments of the UNIONS data by running quality control tests for the future photometric redshift data sets. These future releases will provide additional data to make these detections stronger. For future data, we use the Flagship simulation of the Euclid survey to simulate the expected data from the Euclid VISible imager (VIS) and Near-Infrared Spectrometer and Photometer (NISP) instruments across an octant of the sky. This octant then roughly corresponds to an equivalent area of the planned second data release of the survey. We extend the methodology and covariance model to a lensing tomography setup by binning voids and sources along the line of sight. We then stack information along source bins. From this, we are able to detect the void lensing profiles with 12 sigma, 11 sigma, 7.1 sigma, and 4.7 sigma significance across the four different void redshift bins. Scaling the most significant result to the expected areas for the first and final data releases, we get 6.9 sigma and 21 sigma respectively. We additionally find a 4.4 sigma difference between the lensing profiles of the smallest voids and the largest voids.
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    Communities on-Track: A Spatial Reprogramming of Regional Railway Stations for Interinstitutional and Civic Exchange
    (University of Waterloo, 2026-03-23) Yuen, Hoi Man Neli
    As our society grows more mobile, public transport is becoming an increasingly important alternative to private transport. In Ontario, this shift is compounded by the decentralization of post-secondary education, accelerated by the expansion of satellite campuses and changing patterns of study following the COVID-19 pandemic. As a result, post-secondary students are becoming more reliant on public transport than ever before. However, in the North American context, public transit is often still seen as secondary to private transit, resulting in stations which are underutilized, and underperform socially and functionally. This work addresses the site of the regional railway station. Having once been central to the socio-economic development of towns and cities, this role has since diminished as the result of a fixation on network connectivity alone. In response, this thesis leverages the transformational developments in both sectors to propose a network-based strategy, where public transit and post-secondary systems are conceived of and developed in conjunction. By positioning stations as sites of intersection between mobility and knowledge production, the project frames them as spaces for civic exchange, where the rhythms of travel create opportunities for collective encounter. The implementation of design interventions at three stations along GO Transit’s Kitchener Line demonstrates how context-specific programming can reactivate stations as civic anchors. Together, they offer a distributed model for linking mobility, learning, and community across the regional railway network, repositioning railway infrastructure as an active component of social life rather than a purely functional system.
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    Decentralized Traffic Correlation Using Programmable Switches
    (University of Waterloo, 2026-03-19) Singh, Gurjot
    Attributing network attacks to their sources is challenging as adversaries employ proxy chains, virtual private networks, and anonymity infrastructures to obscure their origins. Traffic correlation techniques mitigate this challenge by linking flows observed at multiple network vantage points using invariant characteristics such as timing and packet volume. However, existing attack attribution systems largely rely on centralized architectures that aggregate flow features at dedicated correlators, introducing computational and communication overheads that hinder scalability in high-speed networks. This thesis discusses RevealNet, a decentralized framework for attack attribution that leverages P4-programmable switches to perform traffic correlation directly within the network fabric. RevealNet distributes feature extraction and correlation across cooperating networks, reducing dependence on centralized processing and minimizing telemetry offloading. Upon detection of a malicious flow, flow features are disseminated to participating switches, which locally correlate them against outgoing traffic using lightweight similarity metrics. To operate within the constraints of programmable data planes, RevealNet employs compact flow feature representations based on traffic aggregation matrices and sketching techniques designed for integer-only computation. The framework further incorporates heuristic optimizations that exploit temporal alignment and traffic-volume similarity to reduce correlation complexity and limit false positives. Experimental evaluation conducted over a prototype of our framework using multiple real-world attack datasets demonstrates that RevealNet achieves attack attribution accuracy comparable to state-of-the-art centralized systems while significantly improving scalability. Notably, compact flow feature representations achieve accuracy comparable to complete flow representations, substantially reducing memory requirements without sacrificing attribution performance. Overall, RevealNet's distributed design reduces bandwidth overhead by up to 96\% when deployed on a testbed consisting of 20 P4-enabled switches and enables programmable switches to correlate a significantly larger number of flows concurrently, demonstrating that attack attribution can be effectively decentralized within programmable network infrastructures.