Theses (Physics and Astronomy)

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    Exploration of applications of photon-counting detector computed tomography (CT) using a table-top CT system
    (2024) Richtsmeier, Devon; Bazalova-Carter, Magdalena; Moffitt, Matthew
    Computed Tomography (CT) is an essential diagnostic tool in healthcare, widely used for various applications including cancer detection, vascular disease evaluations, and radiation therapy planning. Recent advancements in photon-counting detector (PCD) technology have led to the development of photon-counting detector CT (PCD-CT), a promising innovation offering high spatial resolution and superior contrast-to-noise ratios compared to traditional CT. PCD-CT excels in detecting and characterizing small structures in various body parts, enhancing tissue differentiation, and material decomposition, thus potentially improving disease diagnosis and radiotherapy treatment planning. This research explores the applications of PCD-CT using a bench-top system, offering insights into its potential benefits over conventional CT systems. Despite its limitations in fully representing a clinical CT system, the bench-top model provides flexibility in assessing clinically useful features. This dissertation investigates four key applications of PCD-CT: material decomposition, multi-contrast imaging, metal artifact reduction, and high-resolution imaging. We investigated the material decomposition capabilities of our bench-top PCD-CT scanner using a dual-energy CT (DECT) method for extracting effective atomic number (Zeff) and relative electron density (ρe) of tissues. We demonstrated that the method with PCD-CT was more accurate in extracting Zeff and ρe for a set of electron density phantom materials with known Zeff and ρe than the method with DECT. In addition, four tissue types were correctly identified in an ex-vivo tissue sample and an injected gold contrast agent was separated from the other four tissue types using K-edge subtraction imaging. Multi-contrast imaging was demonstrated in a phantom model with four contrast agents: gadolinium, dysprosium, lutetium, and gold. The four contrast agents were inserted into the same cylindrical phantom and imaged in one scan. Using K-edge subtraction, we were able to demonstrate complete separation and accurate quantification of the four contrast agents, even of gadolinium and dysprosium, which have K-edge energies of 50.2 keV and 53.8 keV, respectively. Additionally, we optimized the acquisition parameters for the various contrast agents. We also developed a novel metal artifact reduction (MAR) method using PCD-CT. As metal attenuates fewer higher energy x-rays than low energy x-rays, we showed that the high-energy range of 100–110 keV demonstrated fewer metal artifacts. The high energy range is separable from the other x-ray data with the PCD. With this in mind, we developed trace replacement metal artifact reduction (TRMAR). The metal traces in the corrupted conventional CT sinogram space are replaced with the high-energy trace data from the 100-110 keV range. With this, we maintained the contrast and image quality of the full spectrum conventional CT image and also kept the reduced metal artifacts from the high energy data. Finally, we demonstrated the high spatial resolution of our PCD-CT system by imaging coronary artery stents and comparing the same stents imaged with two conventional CT scanners. PCD-CT demonstrated more accurate measurement of the stent strut, or wire, width, stent lumen diameter, and lumen CT number compared to conventional CT. In addition, this led to more accurate 3D representations of the stents. The higher accuracy of strut width and stent visualization is due to the higher spatial resolution of the PCD-CT system and the reduced metal and blooming artifacts it offers over conventional CT. Each of these applications demonstrates the significant potential of PCD-CT in enhancing medical diagnostics and treatment, particularly in cardiovascular imaging, highlighting its diverse contributions to the field of medical imaging.
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    A Novel Synergetic Combined Modality of Nanotechnology, Chemotherapy, and Radiotherapy for the Treatment of Pancreatic Cancer
    (2024-01-15) Alhussan, Abdulaziz; Chithrani, Devika
    Pancreatic cancer is one of the deadliest types of cancer, with a five-year survival rate of less than 8%. Despite the current advances in medicine, innovative treatment options are needed. Nanotechnology offers a novel perspective to treat such deadly cancers through their incorporation into radiotherapy (RT), as radiosensitizers, and chemotherapy, as drug carriers, for the goal of having better therapeutic efficacy and reducing normal tissue toxicity. However, the interaction of nanoparticles (NPs) with major cells of the tumor microenvironment (TME) is yet to be understood. Therefore, our first goal was to shed light on the dynamics of NPs within a TME of pancreatic origin. In addition to cancer cells, normal fibroblasts (NFs) and cancer-associated fibroblasts (CAFs) were examined due to their important yet opposite roles of suppressing tumor growth and promoting tumor growth, respectively. Gold nanoparticles (GNPs) were used as promising radiosensitizers due to their biocompatibility and physical and chemical proprieties. Our in vitro 2D monocultures studies revealed that NFs take up less than 50% of GNPs compared to cancer cells, while CAFs had over 300% increase in GNPs uptake compared to cancer cells. Cancer cells, CAFs, and NFs lost ~ 25% of GNPs 24 h post-dosing. We were able to significantly enhance the uptake and retention using the radiosensitizing drug docetaxel (DTX). GNP uptake was improved by a factor of three in cancer cells and a factor of two in CAFs. Both cell lines were able to retain ~ 70% of GNPs even 72 h post-treatment with DTX. Drawing on these encouraging findings, our second goal was to create a 2D co-culture of CAFs and cancer cells to model the interaction between cancer and stromal cells in the TME and allow for better testing of therapeutic combinations. To test the proposed co-culture model, cells were grown in co-culture with different ratios of CAFs to cancer cells. Co-cultured cells were treated with 2 Gy of radiation following GNP incubation. DNA damage and cell proliferation were examined to assess the combined effect of radiation and GNPs. Cancer cells in co-culture exhibited up to a 23% decrease in DNA double strand breaks (DSB) and up to a 35% increase in proliferation compared to monocultures. GNP/RT induced up to a 25% increase in DNA DSBs and up to a 15% decrease in proliferation compared to RT alone in both monocultured and co-cultured cells. The observed resistance in the co-culture system may be attributed to the role of CAFs in supporting cancer cells. In parallel, our third goal was to explore encapsulating the toxic DTX prodrug in lipid nanoparticles (LNPDTX-P) and how that affect GNP uptake in vitro and in vivo in NRG mice. The results show that LNPDTX-P treated tumor samples have double the amount GNPs compared to control samples in both in vitro and in vivo. Based on the outcomes of the preceding studies, we aimed to evaluate the anti-cancer efficacy of GNPs and LNPDTX-P in combination with RT on a 3D co-culture spheroid model. GNPs/RT and RT/LNPDTX-P showed a significant reduction in the spheroid size of 7% and 33%, respectively, and an increase in DNA DSB damage of 20% for RT/GNPs. However, the combination of the two nanoparticles with RT significantly enhanced the anti-cancer efficacy resulting in a 46% decrease in spheroid size and a 39% increase in DNA DSB. The combination of GNPs and LNPDTX-P with RT showed a synergistic effect due to their radiosensitizing properties improving the therapeutic efficacy of each treatment modality alone even in the more treatment resistant co-culture spheroid model. This triple modality presents a promising approach for enhancing cancer treatment while reducing side effects, and ongoing research in this area holds great promise for improving outcomes for cancer patients.
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    Skyward AI: Advancing Astronomy with Intelligent Machines
    (2024-01-05) Bialek, Spencer; Venn, Kimberley Ann; Fabbro, Sébastien
    This dissertation represents the work I did in integrating advanced machine learning techniques into three important challenges that the field of astronomy currently faces. Firstly, I tackled the emerging concern of contamination from low earth orbit satellites in the upcoming massive spectroscopic sky surveys. With the imminent launch of several hundred thousand satellites, there’s a potential for significant contamination in wide field, multi-fiber spectrographs. I employed a multi-staged approach to gauge the feasibility and constraints of pinpointing and reducing the impact of such contamination in a WEAVE-like stellar spectral survey. By crafting a series of convolutional-network based architectures, I managed to identify and separate stellar spectra that were artificially tainted with satellite (solar-like) spectra. My findings revealed a promising capability to flag a majority of contaminated sources and reconstruct the clean spectra with minimal error. This work offers a suite of machine learning strategies that can be harnessed to enhance stellar parameters for contaminated spectra in the WEAVE stellar spectroscopic survey and similar endeavours. In my second project, I introduced a novel solution to the well-studied problem of atmospheric turbulence compromising the clarity of astronomical images. By training a U-Net on simulated observations, I demonstrated how a sequence of short-exposure observations of a stellar field can be transformed into a turbulence- and noise-free image. This approach significantly boosts angular resolution over arbitrarily wide fields while preserving flux to a lower signal-to-noise than an averaged stack, without compromising the astrometric stability in the resultant image. It is technically simple as well, keeping costs of implementing and maintaining such a system low. Lastly, I explored the potential of self-supervised learning in extracting meaningful representations of galaxies from millions of unlabelled sources. Recognizing the power of self-supervised methods, particularly SimCLR, I aimed to validate their utility for the UNIONS Survey. My efforts were geared towards automating the clustering and classification of galaxy types, refining photometric redshift estimations, and leveraging these techniques to unearth rare astronomical phenomena such as ultra-faint dwarf galaxies, gravitational lenses, and merging galaxies. The initial results show that, by using a query galaxy image, the fully trained SimCLR model can successfully find similar types of galaxies using a self-similarity search in a database of millions of galaxies. Throughout these projects, I have combined machine learning and astronomical research, presenting innovative solutions to pressing challenges in the field. Each endeavour reflects my dedication to leveraging the capabilities of machine learning to propel astronomical discoveries forward, offering fresh perspectives and tools to address longstanding and emerging issues in the discipline.
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    An exploration of the production of negative ions from neutral gases using a negative hydrogen ion source driver
    (2024-01-04) Paul, Andrew; Junginger, Tobias
    Negative ion beams have wide-ranging applications from acceleration in cyclotrons for medical radioisotope production to areas where tandem accelerators are leveraged. The fields in which tandem accelerators are used include nuclear structure research, environ- mental studies, materials characterization, medical treatments and ion implantation in semiconductor devices. A commercially important case where negative helium ions are utilized is in the semiconductor industry where they are conventionally created by double- charge exchange ion sources using metallic vapours (typically Alkali’s). These metallic vapours lead to challenges such as contamination, electrical shorts, and maintenance difficulties. In an effort to overcome the significant disadvantage of metallic vapour charge exchange, this thesis will firstly investigate the production of negative helium ions using a non-metallic charge exchange method in which negative hydrogen ions will be impinged upon neutral helium gas. A charge exchange cell is developed for this project which includes an electrostatic accelerator to accelerate newly produced negative ions from the target gas. The main objective focuses on negative helium ion production but the method is applied to different gas targets including H2, CO2, and O2 with the goal of accelerating and measuring negative ions that are the products of these targets. This approach aims to avoid the significant contamination issues from the metallic vapour double-charge ex- change method and explore novel methods for negative ion production via charge transfer.
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    Development and Implications of ISOL Target-Materials with High-Carbon content for Short-Lived Radioactive Isotope Beam Production
    (2024-01-03) Cervantes Smith, Marla Stephanie; Gottberg, Alexander; Karlen, Dean
    In the Isotope Separation On-Line (ISOL) method, a high-energy particle beam strikes a target, inducing nuclear reactions that produce isotopes. After releasing from the target by diffusion, the isotopes are ionized, and separated by mass. ISAC, TRIUMF's ISOL facility, delivers RIBs to experiments on nuclear astrophysics, nuclear physics, particle physics, and material science. The Advanced Rare IsotopE Laboratory (ARIEL) is under construction to expand TRIUMF's scientific capabilities with the development of two additional ISOL target systems for TRIUMF. This expansion entails a greater demand for target material, promoting the research and development of new targets tailored for enhanced isotope release and improved resilience under high-power beam irradiation. This work presents the research and development towards reducing several limitations of the current ISOL-target paradigm. A new method for synthesizing UCx targets has been developed. Now UCx targets are synthesized eight times faster than before while complying with the required micrometric particle size and high open porosity to promote isotope release. The reduction in production time complies with ARIEL's future target material demand, and it has relieved personnel and equipment, allowing the development of a novel graphite-composite target. Both targets have been characterized and submitted online for isotope delivery to experiments. Their performance has been studied and related to microstructure and thermal properties. Both targets are now established and regularly operated at ISAC-TRIUMF and will be used in ARIEL. Furthermore, temperature investigations of both targets, have resulted in an analytical and a finite element model to predict their temperature during operation. Moreover, to further improve the performance of the targets, the implications of operating target materials with high carbon content have been investigated. Strategies are proposed for further learning about carbon penetration, the resulting target ovens' corrosion, and its prevention.
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    Flux Expulsion in Coaxial Superconducting Radiofrequency Cavities
    (2024-01-03) Gregory, RuthAnn Rose; Laxdal, Robert; Junginger, Tobias
    This thesis explores the effects of different cool-down speeds and applied magnetic fields on TRIUMF’s coaxial cavities using COMSOL® simulations and experimental results. Magnetic sensitivity describes how sensitive the surface resistance of a material is to an external magnetic field, and is an important characteristic of SRF accelerator design. Reducing magnetic sensitivity can improve cavity performance. Previous studies have shown that nitrogen doped elliptical cavities are very sensitive to external fields compared to conventionally treated cavities, resulting in stringent requirements for the residual field and cavity cool-down speed. Few such studies have been done on non-elliptical cavities such as half wave resonators (HWRs) and quarter wave resonators (QWRs). Factors affecting magnetic sensitivity include cavity treatment, rf field distribution inside the cavity, external magnetic field direction, cool-down speed, and thermal gradient during transition to the superconducting state. Reducing the magnetic sensitivity can improve cavity performance since in practice it is impossible to eliminate all residual magnetic fields from external sources such as Earth’s natural magnetic field during a cool-down. It was found that magnetic sensitivity is not an ideal parameter for characterizing TRIUMF’s HWR and QWR since these cavities exhibit non-uniform flux trapping. Therefore, the parameter normalized Rmag is introduced. Normalized Rmag, or RmagN is the additional surface resistance introduced by applying a dc magnetic field to the cavity, divided by the applied magnetic field. The HWR’s normalized Rmag is compared for different resonant frequencies after 400 and 120℃ bakes, with the 120℃ bake resulting in lower normalized Rmag. The normalized Rmag was found to generally increase with frequency for both the HWR and QWR. The study also seeks to maximize flux expulsion, which occurs when a cavity is cooled down through its superconducting temperature. Flux expulsion is affected by cool-down speed, temperature gradient, and cavity orientation relative to an applied magnetic field. The effects of cool-down speed and temperature gradient on flux expulsion were found to be insignificant for the QWR with a vertically applied magnetic field. However, a horizontal magnetic field can be nearly completely expelled by a fast, high temperature gradient cool-down.
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    Thermal Feedback in Coaxial Superconducting RF Cavities
    (2023-12-19) McMullin, Mattias; Junginger, Tobias; Laxdal, Robert
    Superconducting RF (SRF) cavities are used in particle accelerators to efficiently transfer energy from an RF power source to a beam of charged particles. The power losses associated with this process are inversely proportional to the cavity quality factor Q0, which decreases with increasing RF field strength in a phenomenon known as Q-slope. Q-slope limits the achievable RF field strength in SRF cavities because the increased power dissipation drives up the cost and complexity of an accelerator’s cryogenics infrastructure. Two effects contribute to Q-slope in SRF cavities: thermal feedback (TFB), an extrinsic effect in which Q0 decreases due to heating of the cavity walls, and field-dependent surface resistance, which is intrinsic to the RF surface. Q-slope is believed to be an unimportant effect in elliptical SRF cavities, but its effect in coaxial cavities is unknown. Additionally, the question of how much Q-slope should be attributed to TFB as opposed to field-dependent surface resistance has not been answered quantitatively for any cavity geometry because of a lack of data on boiling from niobium surfaces in liquid helium at the relevant scales of power dissipation. Without knowing these thermal parameters, computational models of heating in SRF cavities are incomplete. In the present study, direct measurements of liquid helium boiling from niobium surfaces were performed. Using these measured thermal parameters, a novel finite element code was developed to calculate the impact of TFB on Q-slope in coaxial cavities. This code removes TFB effects from measurements of Q-slope to reveal the underlying field-dependent surface resistance. Results are presented showing the impact of TFB on data from TRIUMF’s coaxial test cavity program at a wide range of RF frequencies. TFB was found to be a weak effect on Q-slope in coaxial cavities in the operating regimes relevant to acceleration.
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    A Journey to the Edge of the Solar System with an AI navigator
    (2023-12-19) Lee, Aram; Venn, Kim; Kavelaars, J. J.
    I present a deep learning method of searching for solar system objects (SSOs) in wide-field survey imaging data including trans-Neptunian objects (TNOs). Artificially generated sources are added to mosaic images taken with the Canada-France-Hawaii telescope (CFHT) MegaCam instrument to create the convolutional neural network (CNN) training set. The CFHT MegaCam data images are a time series of observations, and the location of the artificial SSO changes between images, in a way that is consistent with a heliocentric Keplarian orbit. The imaging characteristics of the artificial sources were found to be highly similar to those of real SSOs, with rates of sky motion consistent with TNOs. My deep learning approach is based on the detection of moving sources within 64×64-pixel sub-image pairs extracted from the time series of large-format mosaic astronomical imaging data. Each image pair extracted from the training images has been labelled with the presence or absence of a moving source, along with the source location and brightness measured in magnitudes. The labelled sub-images were fed into ImageNet algorithms to train classification models and regression models separately. The algorithm assigns a model-dependent probability that a particular sub-image contains an SSO. The probability threshold required to assert that an SSO has been detected is set based on the evaluation of retrieval and precision of the model and the requirements of the experiment. This thesis evaluates the capabilities of the range of deep learning models and determines which one is most effective in the detection of artificial SSOs. The MobileNet model was selected as the most efficient for this problem space. A trained classification model derived from the MobileNet model retrieved 91% of sub-images with a moving source with a 90% precision on test data sets. A separate regression model then predicted the location of the moving source with a mean absolute error of ±1.5 pixels for sources with SNR > 17 (m_r < 23 in my data set). Although the retrieval rate is high, due to the scarcity of real SSOs in imaging data, the precision achieved (90% of false positives rejected) results in a substantial number of false positives. Further data processing on the candidate list is required to improve the purity of the result. To improve sample purity, I investigated two post-processing approaches: • With the classification-filtered sub-images and their regression-measured locations in sky coordinates, each detected source was grouped with nearby detected sources as SSOs exhibit nearly linear sky motion for the duration of the observed time series. Any group of linear source tracks, detected in at least 1/3rd of the images, was considered a candidate detection. This approach achieves an effective detection limit (more than 50% of artificial sources in the data are detected) at SNR=7.2, and the source purity of the sample was greater than 99% in this case. However, the required combinatorics of this approach (NxN comparison) make it computationally slow, and the high SNR required for detection resulted in very few ‘real’ candidates being proposed. • I also investigate a ‘scoring’ approach for candidate selection. My CNN classification model output is a model-dependent probability that a particular sub-image contains a moving source. Each sub-image was given a score derived by scaling the classification model probability assigned to that sub-image. A sub-image was then determined to hold a candidate object if its score exceeded a given threshold (determined by the desired purity of the sample). With this approach, I achieved an effective detection limit (50% of artificial sources in the data are detected) at SNR=3.4 and discovered a number of real SSOs within the test data set. Visual inspection of 1800 scoring-based candidates revealed approximately 200 visibly bright real (not from the artificial source list) SSO candidates. I tested trained models on test sets from different sky regions and found that our models did not learn from the backgrounds or shapes of TNOs, but rather detected the motion of TNOs. I found that deep-learning object detection algorithms can aid in the discovery of TNOs and SSOs. When combined with a scoring approach, my algorithm provides a capability that is similar to that achieved with more classical approaches without making assumptions of motion rates of the SSOs and without requiring any substantive data engineering. The CNN approach to SSO detection is very promising and should be pursued in the development of future SSO discovery software pipelines.
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    Hall measurement-based study of ferromagnetic thin films stimulated by the idea of spin-orbit torque
    (2023-11-17) Aryal, Mukesh; Choi, Byoung-Chul
    This study is motivated by the idea of spin-orbit torque (SOT). The research attempts to study SOT effects in ferromagnetic systems through numerical and experimental approaches. The numerical simulation segment employs an object-oriented framework tool (OOMMF) to model magnetic systems with a focus on understanding critical parameters. The first part of the simulation incorporates thermal effects into a nanometer-sized CoFeB Hall structure, revealing a significant reduction in critical parameters for magnetization switching due to the inclusion of thermal effects. Subsequently, a micrometer-sized CoFeB Hall structure is simulated, although with compromises in accuracy due to discretization changes and the exclusion of thermal effects. The simulations predict current amplitude requirements for magnetization reversal and highlight the transient nature of magnetization changes under a short current pulse. The experimental facet involves the fabrication and assessment of tungsten films for their viability in SOT applications. Employing sheet resistance measurements via Van der Pauw's 4-point method, tungsten films exhibit varying resistivity based on thickness, suggesting the presence of distinct phases. The investigation then shifts to the study of magnetization in fabricated Hall structures through current-based Hall measurement techniques. Initial attempts utilizing cobalt films uncover in-plane anisotropy, motivating a shift to the use of Co20Fe60B20 films, a recognized ferromagnetic material in spintronics. Careful fabrication and annealing of CoFeB films appeared to improve film quality, yielding promising Hall signals; however, the expected out-of-plane anisotropy required for the targeted SOT experiment could not be achieved. Furthermore, attempts to measure SOT-induced effects encountered challenges, highlighting the need for superior film quality and a more sensitive measurement setup. Despite facing setbacks in detecting SOT-induced effects, the research includes a comparative study of Hall signals across different thicknesses in ferromagnetic devices. The study collectively contributes valuable insights into the complex interplay of spin-orbit torque effects, film quality, and magnetization characteristics within the realm of ferromagnetic systems. This work can serve as a reference for future endeavors in the exploration of spin-orbit torque-driven phenomena and their potential applications.
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    Application of Machine Learning Techniques To Young Stellar Object Classification
    (2023-11-06) Crompvoets, Breanna; Di Francesco, James; Willis, Jon
    Among the first observations released to the public from the James Webb Space Telescope (JWST) was a section of the star-forming region NGC 3324 known colloquially as the “Cos- mic Cliffs.” We build a photometric catalog of the region and analyze these data using the Probabilistic Random Forest machine learning method. We find 496 YSOs out of 19 497 total objects within the field, 474 of which have not been found in previous works. Using the obtained probabilities of objects being YSOs, we employ a Monte Carlo approach to determine a local star formation rate of 1 × 10^–4 M⊙/yr, for the region. We also find that the surface density of YSOs in the Cosmic Cliffs is largely coincident with column densi- ties derived from Herschel data, up to a column density of 1.37 × 10^22 cm–2. The newly determined number and spatial distribution of YSOs in the Cosmic Cliffs demonstrate that JWST is far more capable of detecting YSOs in dusty regions than Spitzer.
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    An ALMA search for substructure and fragmentation in starless cores in Orion B North
    (2023-11-01) Fielder, Samuel Dumaresq; Kirk, Helen; Venn, Kim
    We present Atacama Large Millimeter/submillimeter Array (ALMA) Cycle 3 observations of 73 starless and protostellar cores in the Orion B North molecular cloud. We detect a total of 34 continuum sources at 106 GHz, and after comparisons with other data, 4 of these sources appear to be starless. Three of these starless core detections are found at the edges of target fields, while the final one detection matches the peak of a starless core. We use synthetic observations of starless core collapse under the turbulent fragmentation model, to compute the expected number of starless cores that should be detectable with our ALMA observations and find one starless core should be detectable, consistent with our data. Comparable ALMA analyses have now been performed on three nearby molecular clouds; the number of detections in Orion B North and Ophiuchus are consistent with the turbulent fragmentation predictions, while the lack of detections in Chamaeleon I is inconsistent. We perform a virial analysis of the starless core population in all three clouds to test whether or not core boundedness can explain the differences in the number of ALMA observations. Using a simple alpha parameter analysis, we find that the starless core population in Chamaeleon I is systematically more unbound compared to Ophiuchus and Orion B North. With the addition of external pressure binding terms in our analysis, we conclude that the Chamaeleon I dense core population is still less bounded than the other two clouds. Furthermore, the pressure binding in Chamaeleon I contributes typically an order of magnitude more to the overall core boundedness than the other two regions. These differences may explain why the Chamaeleon I cores do not follow the turbulent fragmentation model predictions, while the Ophiuchus and Orion B North cores are consistent with the model.
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    Lights in Motion Observing Nearby Planets with Imaging, Wavefront Sensing, Orbital Detection, and Spectroscopy
    (2023-09-27) Thompson, William; Marois, Christian; Herwig, Falk
    To place our solar system into a wider context, astronomers must study a broad sample of planets around Sun-like stars in detail. This will require a combination of indirect evidence and direct imaging, which is the focus of this dissertation. Directly imaging solar system analogues is a challenging endeavour that is to a large extent, limited by our instruments and analysis techniques. This dissertation describes how some of these challenges can be overcome from many directions. First, it presents a new analysis technique that re-evaluates how we treat the problem of analyzing direct imaging data called direct signal-to-noise optimization. This approach can provide a three to five times reduction of speckle noise close to the star when applied to angular differential imaging data. Second, it presents applications of an approach for combining images in the presence of orbital motion. This removes a sensitivity limit to direct imaging caused by orbital smearing. It results in near-ideal scaling of sensitivity with square root of the number of observations. Additionally, this technique is extended to arbitrarily combine direct and indirect sources of evidence for planets. Next, this dissertation demonstrates improved instrumentation that could increase the sensitivity of future instruments. It demonstrates the Fast Atmospheric Self-Coherent Camera Technique in a laboratory environment and presents a five hundred times reduction in quasi-static speckles. It then presents a concept for an imaging Fourier transform spectrograph that could combine a self-coherent camera with high resolution spectral information at a resolution of 5,000 to 20,000. It demonstrates such an imaging spectrograph in a laboratory environment and shows how spectro-coherent differential imaging can lead to an approximately forty times reduction in speckle noise. Lastly, it describes a speculative concept for a constellation of orbital retroreflector beacons that could one day lead to the imaging of Earth-like planets from the ground. The analysis techniques developed in this dissertation are applied to a deep, targeted survey of the HR 8799 planetary system. This results in tight limits on any additional outer planets and the detection of a fifth candidate planet at just 4 AU separation, which would be one of the closest separation planets ever directly detected. These results will change how future surveys and searches for planets are completed, and ultimately contribute to understanding the Earth’s place in our local neighbourhood.
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    Measuring Light Distribution of LED Sources for Hyper-Kamiokande Detector Calibration
    (2023-09-11) Booth, Nicholas; Hartz, Mark; Karlen, Dean
    The Hyper-Kamiokande experiment uses water-Cherenkov detectors to study neutrino oscillation and charge conjugation parity (CP) violations with high precision. To reduce systematic errors, multi-photomultiplier tube modules (mPMTs) that comprise the Cherenkov photon detectors will include LED light sources for calibration purposes. This report describes how the LEDs are incorporated into mPMT design, how the distribution of LED light is measured, and discusses how the LEDs will be used for the experiment calibration upon detector completion.
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    Phase Dependent Variation in the Reflectivity of Kuiper Belt Object 2002 MS4
    (2023-09-08) Peng, Jinghan; Kavelaars, J. J.; Willis, Jon
    The Kuiper Belt Objects (KBOs) are the newly-discovered solar system objects located beyond the orbit of Neptune. Observations and study of the KBOs are vital to understanding the origin and evolution of our solar system. The KBO 2002MS4 is a large KBO, dwarf planet, and is my research focus. In order to study the phys- ical properties, I used archival observations from the 3.6 m Canada-France Hawaii Telescope on Maunakea in Hawaii, combined with observations from the New Hori- zon spacecraft, to derive 2002 MS ’s rotational period and phase function. I find 4 that this object does not have an obvious opposition surge and that the phase coeffi- cient / geometric albedo correlation of 2002 MS4 is inconsistent with the correlation expected for C-type asteroids, casting doubt on the concept that C-type asteroids originated in the Kuiper belt. Using occultation observations, obtained at Anarchist Mountain Observatory, I determine an estimate of the minimum size of 2002 MS4 of D > 820±20km, consistent with other occultation measurements of D = 800±20km. This size is smaller than that derived from thermal observations where 2002 MS4 is modeled as a zero-spin body. The reasonable resolution of this result is that 2002 MS4 has a thermal inertia that must be included in its thermal model, which is left for future work.
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    Tidal Evolution of Dwarf Spheroidal Satellites
    (2023-08-31) Borukhovetskaya, Alexandra; Navarro, Julio F.
    Dwarf spheroidal galaxies populate the faintest end of the galaxy luminosity function and yet they apparently reside in massive dark matter halos. With mass-to-light ratios as high as M/L ~ 10^4 , they are the key to understanding the nature of dark matter on galactic scales. Of particular interest are nearby dwarf spheroidals that appear at odds with predictions from LCDM, the standard model of cosmological structure formation. These are galaxies which exhibit unusually large sizes and low line-of-sight velocity dispersions, suggestive of surprisingly underdense dark matter halos, perhaps occurring as a result of tidal interactions with the Milky Way. In this dissertation I present a detailed study of three carefully selected such cases: the Fornax, Crater II and Antlia II dwarf spheroidal satellites of the Milky Way. Fornax is chosen for its relatively low mass-to-light ratio, which is suggestive of a lower mass halo than indicated by abundance matching. Crater II and Antlia II, termed ‘feeble giants’, are both chosen for their particularly low values of velocity dispersion, which are especially anomalous given their large half-light radii and low luminosities. Using N-body simulations, we investigate the evolution of these objects under the effects of Galactic tides imparted by the Milky Way potential. Our study leads us to conclude that the low measured velocity dispersions of these dwarf galaxies are indeed consistent with a tidal interpretation in the context of predictions put forth by cosmological simulations of the Local Group and recent measurements of the galaxies’ sky positions, proper motions, distances, and radial velocities. The large sizes of Crater II and Antlia II are much more difficult to reconcile in this scenario, however these are still possible to reproduce under the effect of Galactic tides, provided that initially the stellar binding energy distributions had a minimum “cutoff”. Such a limit, which may have been imposed by baryonic effects during the formation of the galaxy, or by the presence of a constant density dark matter core, leads to transient stages with large sizes and low velocity dispersions comparable to those of Crater II and Antlia II. Detailed observations of galaxies’ density profiles, corresponding logarithmic slopes, and velocity dispersion profiles may help provide insight into the likelihood of such a formation scenario for Crater II, Antlia II, and the emerging population of other feeble giant galaxies.
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    Searching for Dark Sectors with Proton Bremsstrahlung
    (2023-08-31) Foroughi-Abari, Saeid; Ritz, Adam
    This dissertation explores the sensitivity of high-luminosity colliders and fixed target facilities to low mass new physics in so-called dark sectors that are coupled to the Standard Model of particle physics. These new physics scenarios are motivated by the need to explain empirical puzzles, including the nature of the dark matter in the universe and the origin of neutrino mass. Avoiding over-production and reproducing the observed relic abundance of thermal dark matter candidates requires that low mass (sub-GeV) dark sector degrees of freedom are coupled to the Standard Model via new light force mediators. In this context, we revisit the minimal case of a scalar singlet S coupled to the Standard Model through the Higgs portal and impose new constraints by interpreting the dataset from the LSND experiment. Motivated by proposals for new searches at Fermilab and the Large Hadron Collider (LHC), the rate of proton bremsstrahlung of light dark vectors and scalars is revisited. The proton bremsstrahlung, which involves mixing with meson resonances, is a primary production mode in the forward direction near the resonance region. We derive an approximate method of evaluating the proton bremsstrahlung and compare the resulting distributions and rates with those obtained via variants of the Fermi- Weizsacker-Williams approximation. Additionally, the newly proposed LHC Forward Physics Facility (FPF) emerged as a highly promising site for searching for long-lived particles, millicharged particles, and especially for studying high-energy colliding neutrinos. Within this context, the FORMOSA experiment, located in the LHC forward region, is proposed to provide exceptional sensitivity in the search for millicharged particles by exploiting their scintillation signature. Furthermore, the thesis explores the FPF’s potential to probe the neutrino electromagnetic properties, including neutrino millicharge, magnetic moment, and charge radius, as well as the weak mixing angle, using an intense beam of highly energetic neutrinos of all three flavors. The study of new interactions within the neutrino sector can enhance our understanding of neutrinos and establish the connection between the dark sector and neutrino physics on a broader scale.
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    Developing Lower Cost Radiotherapy Solutions for Low and Middle Income Countries
    (2023-08-30) O'Connell, Jericho; Bazalova-Carter, Magdalena
    Radiotherapy research often focuses on state-of-the-art methods to provide small improvements in the treatment of patients in high-income countries, while less focus is put on providing low-cost treatments suitable for the majority of people in the world who have little or no access to radiotherapy. In an effort to remedy this paradigm we optimise, design, and benchmark lower cost radiotherapy treatment modalities with the overarching goal of increasing treatment accessibility in low- and middle-income countries (LMICs). This body of work has focused on the simulation of cost reducing modification to linacs, in an effort to reduce linac production cost while maintaining treatment efficacy. One method is to simplify current linacs through the elimination of the kilovoltage on-board CT imaging system (kV-OBI). The removal of the kV-OBI would greatly reduce production costs of treatment linacs. However, the removal of the makes many image guided radiotherapy (IGRT) treatments infeasible, treatments which form the bulk of modern radiotherapy. To allow IGRT without the kV-OBI, novel megavoltage cone beam CT (MV-CBCT) methods are simulated to find low-cost setups that provide image quality similar to kV-OBIs. Additionally, cost reduction can be achieved through redesigning current radiotherapy machines by replacing expensive linear accelerator-based treatment heads with low-cost x-ray tubes. To validate this methodology, arc treatments were simulated on a simplified isocentric kilovoltage arc (SITKA) treatment machine with a novel treatment planning system. Additionally, machine learning solutions are used to ameliorate the systems OBI image quality such that a separate planning CT machine is not needed. The Fastcat tool was developed to rapidly simulate CBCT through a combination of pre-calculated Monte Carlo (MC) data and GPU raytracing. To demonstrate this tool improvements, addressing the low contrast to noise ratio in MV-CBCT were studied and proposed. The rapid prototyping of CBCT setups available through Fastcat greatly improve the development of CBCT systems by providing a fast alternative to time-consuming MC simulations in key development situations: Allowing researchers to efficiently optimize a CBCT detector design based on quick feedback in terms of image quality in phantoms for a given dose. This was seen through utilization of Fastcat for the purpose of virtual clinical trials and detector design optimization of novel perovskite and cadmium tungstate (CWO) detectors. Design optimization results demonstrate the benefit of replacing existing cesium iodide (CsI) and gadolinium oxysulfide (GOS) detectors with next generation Perovskite direct conversion detectors. Perovskite detectors showed higher contrast to noise ratio (CNR) and spatial resolution, resulting in better image quality for clinical tasks such as patient positioning and micro-calcification detection, all at a very low manufacturing cost. Likewise, the novel, low-cost system in combination with adaptive machine learning methods and novel planning is demonstrated to provide clinically practical lung treatments that meet the urgent and increasing demand for radiotherapy treatment in low-income countries as well as rural and remote areas.
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    A Morphological Analysis of the Galaxy Cluster XLSSC 122
    (2023-08-24) Leste, Ophélie Karishma; Willis, Jon
    We present a morphological analysis of the 29 spectroscopically confirmed mem- bers of the most massive galaxy cluster at z ∼ 2, XLSSC 122. The cluster was dis- covered in the XMM Large Scale Structure survey as a faint, extended X-ray source and was later confirmed via a Sunyaev-Zel’dovich decrement along its line of sight. We perform photometry using Statmorph on images of the cluster members from the Hubble Space Telescope (HST) Wide Field Camera (WFC3) in the F140W and F105W bands. We perform visual assesment of the images, as well as non-parametric mor- phological analyses based on measurements such as the concentration C, asymmetry A, Gini and M20 to classify the cluster members as being bulge-dominated, disky or possible mergers. The properties of the XLSSC 122 members show clear evidence of bimodality. The bulge-dominated galaxies are redder, older and are found in the denser regions of the cluster, while the galaxies showing disturbed features are bluer, younger, and are found towards the outskirts of the cluster. XLSSC 122 is also found to be deficient of the blue and disturbed galaxy populations compared to galaxies from CANDELS/3D-HST field surveys. We further consider results from dark-matter only cosmological simulations presented in Cosmosim to derive the merger history of the members in cluster halos such as XLSSC 122 at the epoch of observation. The ana- lysis of the simulated data along with the morphological observations, suggest that the galaxy interactions that induce structural disturbances in the blue population of XLSSC 122 members occurred at redshifts in the range 2 < z < 3. This epoch is likely to indicate to the time prior to the infall of these galaxies into the virial radius of the cluster, where galaxy mergers and star formation are eventually suppressed, resulting in their evolution into bulge-dominated red-sequence galaxies.
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    Dust Dynamics in Protoplanetary Disks: Fables of the Sun and the Wind in the Pre- and Post-Planet-Formation Eras
    (2023-08-22) Bi, Jiaqing; Dong, Ruobing
    Dust grains in protoplanetary disks are the most fundamental building blocks of planetary embryos. Therefore, they play a crucial role in the planet formation process. In this dissertation, we focus on the topic of dust dynamics, aiming at exploring the origin of the observed dust substructures in protoplanetary disks and the correlation between the substructures and planets. Dust dynamics in two main periods of time are studied in this dissertation: before and after the formation of the planet. In the first part, we focus on the micron-sized dust grains that are susceptible to the radiation pressure from the star. We present a newly found irradiation instability that leads to the clumping effects of dust grains. We also found that the dust clumps make the disk more transparent, promoting disk edge recession due to radiation pressure, and shedding light on the formation of large dust cavities in transitional disks. In the second part, we focus on the sub-mm-sized dust grains trapped at the planet-induced pressure bump. We show that planet-disk interactions tend to widen dust rings. We also model the planet's effect on the dust via diffusion and quantify the enhanced dust ring width with analytical tools. Our findings bridge the correlations between the confirmed planets and the accompanying wide dust rings.
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    Fast quantum gate design with deep reinforcement learning using real-time feedback on readout signals
    (2023-08-17) Wright, Emily; de Sousa, Rogério
    The design of high-fidelity quantum gates is difficult because it requires the optimization of two competing effects, namely maximizing gate speed and minimizing leakage out of the qubit subspace. We propose a deep reinforcement learning algorithm that uses two agents to address the speed and leakage challenges simultaneously on superconducting transmon qubits. The first agent constructs the qubit in-phase control pulse using a policy learned from rewards that compensate short gate times. The rewards are obtained at intermediate time steps throughout the construction of a full-length pulse, allowing the agent to explore the landscape of shorter pulses. The second agent determines an out-of-phase pulse to target leakage. Both agents are trained on real-time data from noisy hardware, thus providing model-free gate design that adapts to unpredictable hardware noise. To reduce the effect of measurement classification errors, the agents are trained directly on the readout signal from probing the qubit. We present proof-of-concept experiments by designing X and square root of X gates of various durations on IBM hardware. After just 200 training iterations, our algorithm is able to construct novel control pulses up to two times faster than the default IBM gates, while matching their performance in terms of state fidelity and leakage rate. As the length of our custom control pulses increases, they begin to out-perform the default gates. Improvements to the speed and fidelity of gate operations open the way for higher circuit depth in quantum simulation, quantum chemistry and other algorithms on near-term and future quantum devices.