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 ,
    Harvesting entanglement on the lattice and in holography
    (University of Waterloo, 2026-10-02) Wurtz, Kelly
    Entanglement in quantum field theory is difficult not only to calculate but also to interpret: continuum entanglement entropies are ultraviolet divergent, and holographic entanglement measures do not by themselves specify what a local experiment can access. This thesis studies field entanglement through localised probes: finite quantum systems coupled to quantum fields whose final states contain accessible correlations. The first part studies a free scalar field on a harmonic lattice. For a given spatial region of the field, the reduced vacuum decomposes into Williamson normal modes that isolate the entanglement between the subregion and its complement. The most entangled modes are shown to be optimal targets for extraction into detector degrees of freedom, and detector couplings are constructed that realise this extraction by swapping selected field modes with probes. These modes are supported near the boundary, so the probe degrees of freedom needed to reproduce the area-law contribution scale with boundary area rather than volume. The extraction is then assigned an energetic cost by putting selected modes in their vacuum states and evaluating the change in the original lattice Hamiltonian. Numerically, both the extracted entropy and the energy cost obey area-law behaviour over the regimes studied. The second part turns to conformal field theories and their AdS holographic duals. First, we couple Unruh-Dewitt detectors to scalar primary operators in a conformal field theory, and study their ability to harvest entanglement. At leading perturbative order, the detector state is fixed by the universal CFT two-point function, allowing harvested negativity and mutual information to be studied as functions of scaling dimension and detector geometry. In holographic CFTs, the bulk dual also provides an operational way to separate genuine harvesting from causal communication. The final part uses HKLL reconstruction to describe bulk detector interactions in anti-de Sitter space from the boundary perspective. A local bulk detector is represented on the boundary by a nonlocal, time-dependent coupling whose smearing is fixed by the reconstruction kernel.
  • Thumbnail Image
    Item type: Item ,
    Impacts of a Porous Surface on Flame Acceleration
    (University of Waterloo, 2026-10-02) Kresnyak, Ariyanna
    Deflagration-to-detonation transition (DDT) is a critical phenomenon in the development of detonation-based propulsion systems and in industrial gas safety. Recent experimental investigations by Jiang et al. and Lin et al. demonstrated that porous copper foam integrated into the walls of a square combustion channel reduced the detonation onset distance of a stoichiometric ethylene-oxygen mixture. Understanding the mechanisms responsible for this behaviour remains incomplete. This work investigates the influence of a porous boundary on flame acceleration and pressure-field development through direct numerical simulation using the compressible reacting-flow solver PeleC. Simulations were performed for a stoichiometric ethylene-oxygen mixture within a 30 mm × 30 mm square tube. The porous medium was represented using a simplified custom boundary condition consisting of evenly spaced circular outlet pores. This representation was intentionally designed to isolate surface-level mass and flow interactions while excluding combustion and transport within the internal pore structure. Post-processing techniques were developed to quantify flame propagation, shock formation, pressure-field evolution, and transport through the porous boundary. Equal-resolution comparison of the smooth-wall and porous simulations demonstrated no measurable reduction in bulk flame velocity over the available simulation interval. However, the porous boundary substantially altered pressure-wave development. Shock formation was delayed by approximately 56 μs relative to the smooth-wall simulation while occurring at a similar axial location, indicating that the porous boundary primarily influenced the rate of pressure-wave buildup. Interaction between the developing pressure field and porous boundary began prior to direct flame interaction with the pores, while mass and kinetic-energy transport increased substantially following arrival of the flame and high-pressure products. Velocity-field analysis additionally identified a reversal in transverse near-wall flow that provides a potential coupling mechanism between the bulk flame and processes occurring within the porous structure. The results demonstrate that, under the simplifying assumption of representing the porous medium as surface-level outlet pores, the experimentally observed enhancement in flame acceleration is not reproduced. The simulations instead demonstrate pressure-wave attenuation and delayed shock development while retaining similar bulk flame propagation at equal resolution. These findings indicate that physical processes excluded by the simplified boundary representation, particularly combustion and flow transport within the porous volume, may be important to reproducing the acceleration observed experimentally.
  • Thumbnail Image
    Item type: Item ,
    High-performance InGaN µLEDs integrated onto flexible substrates
    (University of Waterloo, 2026-10-02) Gavirneni, Pranav
    Flexible optoelectronic systems, from wearable biomedical devices to conformal displays, demand light sources that combine high efficiency with mechanical compliance. Indium Gallium Nitride (InGaN) microLEDs (µLEDs) are a leading candidate, yet two constraints have limited their adoption on flexible platforms: lateral scaling into the few-micrometer regime often incurs severe efficiency losses, and high-quality III-nitride epitaxy requires high-temperature growth on rigid substrates. This thesis shows that the size-dependent efficiency degradation of scaled µLEDs is largely governed by process-induced surface recombination that can be systematically suppressed. A device-centric framework is developed to decouple electrical injection, internal radiative efficiency, photon extraction, and mechanical integration, enabling the dominant loss mechanisms to be isolated and addressed in a deliberate hierarchy. Optimized ohmic contacts to n-type Gallium Nitride (n-GaN) and p-type Gallium Nitride (p-GaN) establish a low-loss electrical baseline for interpreting size effects. Sidewall-induced Shockley–Read–Hall (SRH) recombination is identified as the primary scaling-limited loss and is quantified through a practical critical diameter, critical diameter (dcrit), separating bulk- and surface-dominated regimes. Combined chemical sidewall repair and polymeric encapsulation reduce the surface recombination velocity (vs) from∼ 3×10^3 cm s^−1 to below 10 cm s^−1, with model extrapolation predicting a shift in dcrit from 43 µm to below 0.1 µm; experimentally, no size-dependent efficiency penalty was observed over the measured diameter range of 6 to 17 µm. With surface losses suppressed, geometry-driven extraction strategies become viable: perforated device architectures introduce internal sidewalls to enhance light extraction without a recombination penalty. Fully optimized devices are then transferred from sapphire onto polyethylene naphthalate substrates (PEN) via a photonic-assisted process while preserving reverse leakage below 100 fA and wall-plug efficiency (WPE) (∼ 28%). Backside potassium hydroxide (KOH) texturing of the exposed n-polar Gallium Nitride (GaN) raises the peak WPE of 5 µm devices to∼ 31%, with less than 5% variation under bending at an 11 mm radius of curvature (ROC). Overall, the results show that surface and interface physics set the practical performance limits of scaled InGaN µLEDs. The framework developed here provides guidance for engineering efficient, mechanically compliant light sources for high-resolution displays and biophotonic systems.
  • Thumbnail Image
    Item type: Item ,
    Decision-Focused Learning for Surgical Resource Allocation
    (University of Waterloo, 2026-10-02) Li, CHUNRUI
    Hospitals allocate operating-room (OR) capacity before future surgical demand is fully known, so they must rely on demand predictions when making resource-allocation decisions. A conventional predict-then-optimize approach trains a demand predictor for statistical accuracy and subsequently optimizes against its point forecast. We study whether the predictor should instead be trained directly for the quality of the OR allocation it induces. We formulate a contextual, multi-period OR-capacity allocation problem and develop a decision-focused learning approach that trains the demand predictor through the downstream allocation objective. We first establish consistency of empirical decision-risk minimization. We then analyze a two-class specialization to characterize the difference between decision-focused training and accuracy-based training using squared loss. We show that under suitable conditions, decision-focused training is decision-consistent, whereas squared-loss training targets the conditional mean and can incur a strictly positive decision regret that persists even with unlimited data. The analysis identifies capacity scarcity, reward–urgency asymmetry, and demand uncertainty as key drivers of this gap. Extensive numerical experiments confirm our analytical results. Using five years of data from a public hospital, decision-focused training reduces out-of-sample regret from 3.69% to 1.98%, eliminating 46.1% of the regret incurred by the accuracy-based predictor.
  • Thumbnail Image
    Item type: Item ,
    Independent Verification of Untrusted Systems: A Side-Channel Approach to Anomaly and Intrusion Detection
    (University of Waterloo, 2026-10-02) Grisel-Davy, Arthur
    Compromised machines are not trustworthy. This simple and apparently obvious statement clashes with the way most Intrusion Detection Systems (IDSs) operate. Whether they analyze binaries, logs, files, or network traffic, they share the flaw of relying on software running on the monitored machine for information collection. But what if the machine is compromised? Should we still use and trust input data that may have been tampered with by an attacker? This flaw is the root of this investigation on side-channel-based IDS. To circumvent this lack of trust, it is required to move the information collection process out of the target and only consider independent and tamper-resistant information. Side-channel information is an ideal candidate for this task because its presence is guaranteed and its variations are intrinsically linked to the activity of the system. Moreover, measuring side-channel information does not require the cooperation of the system. Many side-channels are viable candidates but power consumption quickly proves to be the most practical, reliable, and available. Throughout successive studies, power consumption was leveraged to build complementary IDSs aiming to provide an additional layer of defence, one sitting at the very bottom of the technology stack. These studies revealed that the main obstacle for using power consumption to detect intrusion is the interpretation of the power patterns. The power consumption of a machine in the real world is noisy and inconsistent. In order to make a decision, each proposed algorithm first converts the real-valued time series into categorical and consistent information. This conversion of power patterns into actionable labels is the core of all approaches and thus relies on different techniques depending on the machine or the type of attack to detect. This thesis presents the results of developing and applying power capture, signal processing, machine learning, and intrusion detection tools to a wide range of devices to detect attacks such as firmware tampering, hardware tampering, unauthorized access, anomalous activities, and evasion techniques. Each study provides experiments performed with real-world machines to evaluate the capabilities of the proposed approaches to detect attacks. These studies led to the conclusion that power consumption is a viable source of information for the detection of a wide range of attacks and that its use as a complementary layer of defence would be beneficial for a wide range of devices.