Department of Physics, Engineering Physics and Astronomy Graduate Theses

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    The Universality of Intrinsic Flattening in Extragalactic Stellar Disks
    Favaro, Jeremy P.; Physics, Engineering Physics and Astronomy; Widrow, Lawrence
    Highly inclined (edge-on) galaxies provide the unique perspective necessary to constrain the intrinsic flattening, 𝑐/𝑎, of galactic disks. We use “dust-free” 3.6 𝜇m maps of 141 edge-on spiral galaxies from the Spitzer Survey of Stellar Structure in Galaxies (S4G) and its early-type galaxy extension to determine the intrinsic flattening of stellar disks. The proper assessment of the intrinsic flattening of galaxies requires careful consideration of galactic structure. To this end, we take inspiration from the findings of surface brightness profile decompositions to develop a robust method for the identification and analysis of isophotes that characterize the disk. Isophote axis ratios are averaged within two axial bins between 20% of the optical radius of the 25th magnitude isophote in the 𝐵-band, 𝑅25, and 80% of 𝑅25, which we demonstrate characterises the stellar disk’s 𝑐/𝑎. We then test for correlation between 𝑐/𝑎 and Hubble type. The relationships between 𝑐/𝑎 and other galactic physical parameters – total stellar mass, concentration index, total HI mass, mass of the central mass concentration (CMC), and circular velocity – are also investigated. We find that: (i) the intrinsic flattening of spiral galaxies is ⟨𝑐/𝑎⟩ = 0.130 ± 0.002 (stat) ± 0.034 (intrinsic/systematic); (ii) the intrinsic flattening of spiral galaxies is similar across morphological types; (iii) intrinsic flattening shows good positive correlation with measures of CMC size; and (iv) intrinsic flattening correlates well with the model-dependent ratio of scale height to scale length.
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    Next-Generation Photonic Signal Processors
    Ibrah, Ahmed; Physics, Engineering Physics and Astronomy; Shastri, Bhavin
    Digital electronics have advanced through miniaturization and neuromorphic architectures, enabling faster and more energy-efficient computing. However, they encounter challenges such as Moore's law saturation, speed constraints, and energy efficiency limitations due to wiring capacitance and transistor leakage. Photonic processors, leveraging light, are devoid of these effects and utilize wavelength-division multiplexing for increased throughput and energy efficiency. Yet, their WDM scalability is limited by the free spectral range (FSR) of photonic weights. Additionally, their energy efficiency and speed are limited by thermal weights and electronic memory, necessitating regular electronic-optical transitions. Their reliance on a single weight type also restricts their reconfigurability and application scope. In this thesis, we extend photonic hardware scalability by integrating mode-division with wavelength-division multiplexing, thus overcoming FSR limits and increasing throughput. We developed multimode WDM-compatible processors and components, such as multimode adiabatic multiplexers with insertion loss down to 0.5 dB and crosstalk isolation up to 57 dB, multimode micro-ring resonator weights, and photodetectors with responsivity up to 1 A/W. We also realized inverse-designed mode multiplexers, reducing multiplexer size by 2100\%. Our processor's capabilities were demonstrated in high-speed applications, including Radio-frequency signal unjamming, optical signal unscrambling, and photonic tensor core processing. Furthermore, we introduced electrostatic MEMS weights to reduce power consumption, enhance tuning speed, and provide cryogenic compatibility. These MEMS weights were integrated into neural networks, achieving fast update rates of up to 0.5 Mega updates per second. Additionally, we compared their performance with thermal weights in terms of power consumption. We also demonstrated monolithically integrated capacitive analog memory cells within photonic weights to minimize electronic-optical transitions, achieving a memory retention time of 0.8435 ms and a power consumption of 32.1 nW. We also emulated its performance in neural networks under limitations of memory leakage, noise, and control bit precision. Lastly, we proposed a reconfigurable tensor core (PTC) architecture that supports multiple weight types. We demonstrated a 3×3 PTC and used it in neural network emulations, employing a general matrix multiply compiler to adapt matrix-vector multiplication operations to the PTC size. We also explored the advantages of hybrid electronic-photonic neural networks over purely electronic or photonic networks.
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    Growth and Characterization of Graphene via Chemical Vapour Deposition (CVD)
    Zhao, Guangyuan G. Z.; Physics, Engineering Physics and Astronomy; Knobel, Robert
    Graphene is a two-dimensional (2D) material with a single atomic layer of carbon atoms, with unique properties such as high electrical and thermal conductivity, high optical transparency and tensile strength. It can be fabricated by mechanically exfoliation from bulk graphite, since graphite is made of the stacked layers of graphene bonded together by Van der Waals (VdW) forces. Graphene has a great potential to be used in flexible ultra-sensitive sensor applications, or as transparent conductive layer in displays and solar cells. However, a major issue in graphene commercialization is the difficulty in scaling up high-quality graphene production efficiently and cost-effectively.
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    Generating and Simulating CANDU® Fuel Channel Eddy Current Data to Demonstrate Multi-Parameter Extraction Capabilities
    Purdy, Owen; Physics, Engineering Physics and Astronomy; Krause, Thomas
    An eddy current probe known as the gap probe is used in CANDU® (CANadian Deuterium Uranium) nuclear reactors to verify that Pressure Tube to Calandria Tube (PT-CT) gap in Fuel Channels is larger than the minimum requirement. Contact between the two tubes can severely reduce the structural integrity of the PT. The measurement is affected by nearby conducting structures, which include Liquid Injection Shutdown System (LISS) Nozzles, Garter Spring (GS) spacers and the tooling body itself, which is shielded by a flat copper plate. The electrical properties of the PT and its distance from the face of the gap probe also impact the measurement. Generating and simulating data, which accounts for these factors enable changes in the gap probe eddy current response from PT-CT gap variations to be isolated from variations caused by the other conducting structures and parameters of interest. This thesis presents an analytical model of the eddy current gap probe response with the addition of a copper plate. This analytical model was shown to have excellent agreement with simulation data from a validated Finite Element Method (FEM) model. Efforts made to detect tight-fitting GSs with disconnected girdle wires are also presented. This method of detection was determined as not being feasible, as there are insufficient eddy currents induced into the conducting volume of the GS connector. A validated FEM model, which can simulate the change in receive coil voltage measured by the gap probe caused by a nearby LISS Nozzle, is developed. The FEM model displayed excellent agreement with experimental data. A Deep Neural Network (DNN) was implemented to simultaneously extract PT-CT gap, and LISS-CT distance from experimental PT-CT gap inspection data. The extraction of PT-CT gap in the proximity of LISS nozzles has not previously been demonstrated. It was also shown that a DNN could be used to simultaneously predict PT-CT gap, PT wall thickness, PT resistivity, and probe liftoff from experimental validation data. The demonstration of this capability is of significant value to nuclear utilities as DNNs could be used for other types of similar inspection applications.
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    The Role of Fuelling and Efficiency in Triggered Star Formation in Interacting Galaxies
    Faria, Lawrence A.; Physics, Engineering Physics and Astronomy; Spekkens, Kristine; Patton, David; Courteau, Stéphane
    Mergers and interactions play pivotal roles in the evolutionary trajectory of galaxies, significantly influencing various dynamical and baryonic properties through their histories. Characterizing roles of major/minor interactions in galaxy evolution can help constrain various galaxy formation processes. Cosmological hydrodynamical simulations provide a unique opportunity for us to study these processes as a function of time. In this thesis, using the IllustrisTNG-100 cosmological simulations, we explore how galaxy properties, such as specific star formation rate (sSFR), gas fraction (fgas) and star formation efficiency (SFEH), change over the course of galaxy-galaxy interactions. Using 18,534 encounters identified from the reconstructed orbits of a sample of massive galaxies with companions within a stellar mass ratio of 0.1 to 10, the variation of galaxy properties is studied over time to and from the pericentric encounters over a redshift range of 0 ≤ z ≤ 1. We find that star formation rates, gas fraction and star formation efficiency are significantly enhanced on average within the central stellar half mass radius following pericentric encounter of a host galaxy with its companion in comparison to the pre-encounter values. sSFR is enhanced by a factor of 1.6±0.1, fgas by a factor of 1.2±0.1 and SFEH by a factor of 1.4 ± 0.1 following the pericentre of an encounter. Our results show a time delay between pericentre and maximum property enhancement of ∼0.1 Gyr with a mean galaxy separation of 75 kpc. Additionally, we find evidence of inflowing gas towards the centre measured by comparing the fgas and metallicity within the central stellar half mass radius to galactic outskirts. In examining whether enhanced fgas or enhanced SFEH drive the observed enhancement in sSFR, SFEH is found to act as the primary driver, accounting for approximately 70% of the maximum sSFR enhancement. These results help to better link observational pair studies of interacting galaxies with the findings of high resolution merger simulations. The encounter catalog assembled and utilised in this work presents a powerful tool for studying how other galaxy properties, such as active galactic nuclei, vary during interactions.