Physics and AstronomyNo Descriptionhttps://hdl.handle.net/10012/99492024-11-08T17:49:14Z2024-11-08T17:49:14Z8031The Evolution of Halo Properties Through Binary Major MergersMarchioni, Justinhttps://hdl.handle.net/10012/211492024-10-17T17:38:59Z2024-10-17T00:00:00Zdc.title: The Evolution of Halo Properties Through Binary Major Mergers
dc.contributor.author: Marchioni, Justin
dc.description.abstract: Galaxy clusters are massive, gravitationally bound objects composed of a large population of galaxies. Each of these galaxies occupies a dark matter halo and collectively the cluster has its own extended halo. Cluster halos can be described by many structural properties including their mass, concentration, shape, spin, and asymmetry. These properties, among others, can be used as proxies to constrain cosmology. The issue with galaxy clusters is that they are still assembling at the present-day. These clusters primarily grow through mergers, where smaller systems coalesce to form larger ones. If the mass ratio between the two merging components is sufficiently large (i.e. 3:1 or below), this is known as a major merger. The effect of major mergers is to significantly redistribute the matter distribution in the host system. This leads to pronounced fluctuations in the cluster's structural properties during the merger, making measurements of these properties hard to interpret. Therefore, accurately predicting how cluster properties vary during mergers is important in order to use them as a cosmological tool.
In this thesis, we use simulations to study how the structure of remnant systems evolves during mergers. These simulations consider the merger of two isolated components, each represented by truncated Navarro-Frenk-White (NFW) profiles. We find that mergers produce oscillations in structural parameters for both the overall remnant and the host system. For example, the host halo's concentration experiences one of two types of responses to the satellite's motion depending primarily on the pericentric passage distance of the orbit. Given the simulation results, we present a semi-analytic model for the evolution of structure in remnant systems due to isolated, binary mergers. The model consists of two components, a treatment for the orbital evolution of the satellite and a prescription for changes in the host halo's potential. This second component is often neglected when modeling satellite orbits in minor mergers. Interestingly, we find that adding a host halo response model has little impact on the orbital evolution of the satellite and its mass loss. In contrast, this model must be incorporated in order to accurately predict how the remnant's structure changes after the satellite first passes pericentre. While our model generally works well at replicating the median concentration for the first two orbits, it is unable to recreate any of the remnant's anisotropy properties (i.e. shape, spin, and asymmetry). Overall, our results provide a framework for analyzing the response of cluster halo properties to mergers in more realistic scenarios.
2024-10-17T00:00:00ZCharacterization and First Results of an Inverse Photoemission SpectrometerBouliane, Michaelhttps://hdl.handle.net/10012/211122024-09-27T07:01:24Z2024-09-26T00:00:00Zdc.title: Characterization and First Results of an Inverse Photoemission Spectrometer
dc.contributor.author: Bouliane, Michael
dc.description.abstract: This thesis discusses our efforts to characterize our home built inverse photoemission spectrometer. We review the relevant theoretical and practical considerations for the technique of inverse photoemssion spectroscopy. We then detail our efforts to characterize our low energy electron gun, presenting a method for determining the total current delivered by the beam using just a Faraday cup. Measurements of the beam’s profile are presented and are used to calculate the parallel momentum resolution of the beam. Equally important is the characterization of our photon detectors, which we show are operating in the proportional region with a minimal dark count rate. We ascertained a spectrometer energy resolution of 415(55) meV by performing inverse photoemission measurements on polycrystalline gold foil, single crystal Cu (111), and pyrolytic graphite. As a final demonstration of our spectrometer’s capabilities we provide a full unoccupied band mapping for pyrolytic graphite showing its ability to resolve dispersive electronic features in reciprocal space.
2024-09-26T00:00:00ZTowards Large Scale Quantum Simulations with Trapped Ions: Programmable XY model, Precise Light Sensing, and Extreme High VacuumKotibhaskar, Nikhilhttps://hdl.handle.net/10012/210902024-09-25T07:01:47Z2024-09-24T00:00:00Zdc.title: Towards Large Scale Quantum Simulations with Trapped Ions: Programmable XY model, Precise Light Sensing, and Extreme High Vacuum
dc.contributor.author: Kotibhaskar, Nikhil
dc.description.abstract: We are currently witnessing a revolution in quantum technologies. Today's controllable quantum devices have reached a complexity that makes it practically intractable to fully simulate their dynamics using current classical supercomputers.
Decades of fundamental research and development have led us to this point. In the coming years, billions of dollars in investments from governments and private entities are expected worldwide. Although general-purpose fault-tolerant quantum computers are expected to impact computing profoundly, today's quantum devices are best suited for their analog quantum operation, where a well-controlled quantum simulator mimics the dynamics of the other quantum system being studied. This affords an advantage over classical simulators at the cost of a restricted set of physical phenomena that can be studied. Today's quantum devices are already providing insights into large-scale entanglement, the underlying physics of high-temperature superconductivity, disordered quantum systems, and much more. Enhancing the capabilities of today's analog quantum simulators requires adding more classes of interactions, reducing errors due to calibration and noise, and increasing the system size to allow larger-scale simulations.
The work described in this thesis directly addresses these core points for a system of trapped ions, which are ideal quantum simulators of the coupled dynamics of a large number of magnetic spins. First, the theory and experiment pertaining to the simulation of the anisotropic XY model on trapped ions has been presented. The theoretical proposal does not require added technical improvements over what has existed in the field for over a decade.
The experimental validation is performed on a system with two 171Yb+ ions. This directly enhances the repertoire of trapped ions simulators and opens avenues to the exploration of high-temperature superconductivity, superfluidity, and spin liquids. The second result is the demonstration of the highest resolution readout of optical intensity and polarization using a single 171Yb+ ion as the field probe. The technique utilized the intensity- and polarization-dependent optical pumping of the ions as a signature to detect light parameters. This will be useful for the characterization of the optical addressing fields in trapped ion quantum simulators and hence for the calibration of large-scale quantum devices.
Finally, the design and construction of a large-scale ion trapping apparatus for quantum simulation are described.
The ion trap allows for the trapping of more than 50 ions, and the vacuum chamber used to house the trap with pressure below 1.5E-12 mbar (measurement limited by pressure gauge saturation) likely sets a record for the lowest pressure achieved on a room-temperature trapped ions system. This increases the useful simulation time of large-scale trapped-ion devices and paves the way for further enhancement of the scale of the simulations performed. Together, these results are another step in advancing the capabilities of today's quantum devices to explore physical phenomena far beyond the capability of classical supercomputers.
2024-09-24T00:00:00ZDevelopment of the CHORD Galaxy Search StrategyHopkins, Hanshttps://hdl.handle.net/10012/210892024-09-25T07:01:53Z2024-09-24T00:00:00Zdc.title: Development of the CHORD Galaxy Search Strategy
dc.contributor.author: Hopkins, Hans
dc.description.abstract: This thesis presents my contribution to the CHORD galaxies science case. I helped develop an algorithm that can automatically pick out galaxies from CHORD driftscan data. The method used is a matched filter, and it acts on spatial data and spectral data.
On the spatial side, it searches for point sources. Because CHORD is a highly redundant interferometer, it suffers from spatial aliasing. I present a program that is able to predict the severity of spatial aliasing. It predicts that integrating over periods of time is required to break the alias degeneracy, and that "dithering" CHORD (rotating it by a couple degrees) further helps in reducing the alias issue. I offer a framework for estimating the probability of spatial alias confusion.
On the frequency side, I present a method of running the matched filter quickly. CHORD frequency data undergoes a process called upchannelization, which would distort the shape of a galaxy profile. I show how this can be accounted for without incurring a large time-cost penalty.
Lastly, I discuss how a full matched filter program would be put together, and implications that my research has on selecting search parameters for a future CHORD galaxy survey.
2024-09-24T00:00:00ZStudying Unmodeled Physics from Gravitational Wave DataDideron, Guillaumehttps://hdl.handle.net/10012/210772024-09-25T07:00:12Z2024-09-24T00:00:00Zdc.title: Studying Unmodeled Physics from Gravitational Wave Data
dc.contributor.author: Dideron, Guillaume
dc.description.abstract: This thesis explores the detection and analysis of unmodeled physics in Gravitational Wave (GW) data. To this end, we develop the SCoRe framework, which uses the Correlated Residual Power Spectrum (CRPS) between pairs of detectors to identify deviations from our Standard Model (SM) of GW. This model includes General Relativity (GR) as the theory describing gravity, binary Black Holes (BHs) and Neutron Star (NS) merging as the sources of GWs, our model of the noise in the detectors, and the template waveform models used for data analysis.
The thesis starts with a theoretical overview of GW physics, including an overview of GR, and how it describes the way GWs are generated and how they propagate and interact with matter. We then discuss the practical aspects of GW detection: the modelling of the noise in the detectors and the data analysis techniques used to extract and interpret GW signals.
Next, we describe the SCoRe framework in Chapter 2, which is designed to distinguish between noise and deviations from the SM, while also shedding light on the underlying physics of the deviation. We detail its three main components: cross-correlating residual power between detectors, projecting onto physically motivated or agnostic bases, and combining information from multiple events by assuming a dependence of the unmodeled physics on the source parameters.
To illustrate the method, we apply the SCoRe framework to toy models in Chapter 3. We demonstrate how the method can recover unmodeled signals without prior assumptions about their form, how to choose the timescale of cross-correlation, and how the method can be used to perform a null test of the SM. In Chapter 4, we then forecast the precision with which the SCoRe method can recover a deviation from the SM from a population of Binary Black Hole (BBH) mergers observed by a network of third-generation GW detectors. As the method leverages the dependence of the deviation from the SM on the source parameters, we investigate the effect the distribution of these parameters has on the method. For a model where the deviation scales with the chirp mass as a decaying power law, we show that the precision of the constraints on the deviation decreases as the power law becomes steeper. This has implications for constraining higher-dimensional operators in Effective Field Theories (EFTs) of gravity: higher dimensional operators correspond to steeper power laws and are, therefore, harder to constrain with the method.
Finally, in Chapter 5, we illustrate another approach to testing the SM of GWs, where the GW signal in an alternative theory of gravity is numerically computed. We give an overview of the mathematical challenges and describe a method, the “fixing the equations”
method, which aims to reduce pathologies in evolving EFTs of gravity by controlling energy flow to high frequencies.
2024-09-24T00:00:00ZPath Integral Monte Carlo simulations of solid parahydrogen using many-body interaction potentialsIbrahim, Alexanderhttps://hdl.handle.net/10012/210732024-09-24T07:01:24Z2024-09-23T00:00:00Zdc.title: Path Integral Monte Carlo simulations of solid parahydrogen using many-body interaction potentials
dc.contributor.author: Ibrahim, Alexander
dc.description.abstract: We construct ab initio many-body potential energy surfaces (PES) and use them to perform high-accuracy path integral Monte Carlo (PIMC) simulations of solid parahydrogen.
We first perform PIMC simulations of solid parahydrogen using the Faruk-Schmidt-Hinde (FSH) potential, an ab initio 1D two-body PES for parahydrogen constructed by the Roy group in 2015. The simulations are successful at reproducing experimental results for the equilibrium density and for the vibrational matrix shift for solid parahydrogen. However, we find that the two-body PES on its own is too energetically repulsive at higher densities, and greatly overestimates the pressure as a function of density. To improve the accuracy of our simulations, we must include higher-order many-body interactions, such as the three-body and four-body interactions.
We then construct an isotropic ab initio three-body PES for parahydrogen. The energies are calculated using the coupled cluster method with singles, doubles, and perturbative triples excitations (CCSD(T)). The calculations are performed using an AVTZ atom-centred basis set, with additional (3s3p2d) midbond functions. We use a machine learning method called the reproducing kernel Hilbert space (RKHS) method to construct a PES from the ab initio energies. The three-body PES is attractive at short distances. We perform PIMC simulations of solid parahydrogen using both the two-body FSH potential and the new three-body PES. The inclusion of the three-body PES improves the agreement with experiment at lower densities. However, at higher densities, the attractive interaction of the three-body PES overcorrects for the repulsive wall of the two-body PES, resulting in a severe underestimation of the pressure-density curve.
Next, we construct an isotropic ab initio four-body PES for parahydrogen. The energies are calculated using the CCSD(T) method, using an AVDZ atom-centred basis set with additional (3s3p2d) midbond functions. We use a multilayer perceptron (MLP) to construct a PES from the ab initio energies. We find that the four-body PES is repulsive at short distances. We anticipate that the inclusion of the four-body PES alongside the aforementioned two-body and three-body PESs will improve the agreement of the PIMC simulations of solid parahydrogen with experiment to higher densities than previously found.
2024-09-23T00:00:00ZSpectral, information-theoretic, and perturbative methods for quantum learning and error mitigationPeters, Evanhttps://hdl.handle.net/10012/210292024-09-18T07:00:37Z2024-09-17T00:00:00Zdc.title: Spectral, information-theoretic, and perturbative methods for quantum learning and error mitigation
dc.contributor.author: Peters, Evan
dc.description.abstract: We present spectral and information-theoretic characterizations of learning tasks involving
quantum systems, and develop new perturbative error mitigation techniques for
near-term devices. In the first part of this thesis, we explore connections between quantum
information and learning theory. We demonstrate theoretically that kernel bandwidth enables
quantum kernel methods associated with a high dimensional quantum feature space
to generalize. We then characterize quantum machine learning models that generalize
despite overfitting their training data, contradicting standard expectations from learning
theory. In such learning tasks, the learner may fail due to noise in the input data. So
we next consider a setting where the learner has access to correlated auxiliary noise, a
resource that contains information about an otherwise unknown noise source corrupting
input data. We use classical Shannon theory to relate the strength of these correlations to
the classical capacity of a bit flip channel with correlated auxiliary noise, and we extend
this analysis to derive the quantum capacity of a quantum bit flip channel given access
to an auxiliary system entangled with the environmental source of the noise. Finally,
we derive an information-theoretic guarantee for the learnability of data by an optimal
learner and, extending this technique to a quantum setting, we introduce and characterize
an entanglement manipulation task that generalizes the notion of classical learning.
The second part of this thesis introduces techniques for error mitigation on near-term
quantum processors and provides guarantees in the perturbative limit. We introduce a
technique for mitigating measurement errors using truncated matrix operations. We then
propose and characterize a technique that uses the time-reversibility of a quantum circuit
to measure the quality of a subset of qubits, and we apply this technique to assign logical
circuits to qubits on a physical device in a nearly optimal manner using a simulated
annealing optimization algorithm.
2024-09-17T00:00:00ZAutomated Tuning and Optimal Control of Spin Qubits in Quantum Dot DevicesPaurevic, Andrijahttps://hdl.handle.net/10012/210212024-09-18T07:00:56Z2024-09-17T00:00:00Zdc.title: Automated Tuning and Optimal Control of Spin Qubits in Quantum Dot Devices
dc.contributor.author: Paurevic, Andrija
dc.description.abstract: Silicon quantum dots present a promising foundation for realizing scalable quantum processors, leveraging the advantages of a mature semiconductor industry. Two significant challenges hinder their development: the laborious tuning of these devices and the coherent control of their spin qubits. This thesis presents contributions towards addressing these challenges by harnessing physics-informed machine learning.
Tuning these devices involves navigating complex parameter spaces, plagued with variability and fabrication imperfections, to identify optimal operating conditions. This process demands extensive time and resources by a researcher to perform large amounts of data collection and analysis. My work takes steps towards on achieving fully autonomous tuning of these devices, with the automated formation of a single quantum dot. This work involves the application of data analysis and computer vision techniques to extract relevant features from data, guiding the tuning process in real-time. This tool allows single quantum dots to be formed autonomously, freeing researchers to focus on investigating the physics of the device. Progress in multi-dot systems was also made by developing a data segmentation model that successfully identifies and segments charge and dot configurations in charge stability diagram data. This enables rapid data analysis to determine optimal voltage settings for achieving the desired device state.
Optimal control is crucial for guiding quantum systems through unitary operations while minimizing decoherence. Using a simulated open quantum system Hamiltonian for spin qubits, I developed a protocol to optimize experimental control signals, allowing for the implementation of unitary gate operations with arbitrary fidelity. The protocol designed experimental pulses for single-qubit rotations and entangling gates in a two-qubit system, achieving fidelities above the error correction threshold. Additionally, it utilizes modern machine learning frameworks, making it scalable to multi-qubit systems.
The work presented in this thesis serves as an important foundation for future advancements in our research group.
2024-09-17T00:00:00ZPractical design and demonstration of algorithms for quantum devicesRay, Anniehttps://hdl.handle.net/10012/210162024-09-18T07:01:34Z2024-09-17T00:00:00Zdc.title: Practical design and demonstration of algorithms for quantum devices
dc.contributor.author: Ray, Annie
dc.description.abstract: The emergence of noisy intermediate-scale quantum (NISQ) devices represents a significant milestone in the journey towards the development of large-scale fault tolerant quantum computers. These devices have not only opened avenues for demonstrating a quantum advantage but have also advanced the practical development of quantum algorithms for solving challenging problems in physics, chemistry, and computer science. Most notably, this progress has necessitated a tailored approach to algorithm development that considers the specific architecture and hardware constraints of these quantum devices in order to effectively use them. However, the most useful instances of problems that we hope to solve with quantum computers require significant hardware improvements over the state-of-the-art, including at least a hundred fold increase in the number of qubits. The transition from intermediate-scale to large-scale quantum computers also presents other formidable challenges, particularly for engineering precise quantum control at scale. This thesis attempts to narrow the gap between intermediate and large-scale devices by proposing methods to mitigate noise effects on NISQ devices and by enhancing standard quantum algorithms to minimize resource overhead. One focus is on error correction strategies capable of managing noise on quantum devices. Specifically, we demonstrate the robustness of the sweep rule (a decoder for topological quantum codes) against measurement errors in quantum codes. Additionally, we experimentally demonstrate the improvement in performance of entangling non-Clifford operations when encoded in the [[8,3,2]] code, strengthening the case for error correction. Furthermore, we improve a well-known technique known as imaginary time evolution to reduce the associated qubit and entangling gate overhead, making it more amenable to implementation on NISQ devices. By exploring these avenues, we aim to strike a balance, leveraging NISQ devices to expand their computational capabilities in the short term while serving as a sandbox for the development of future large-scale fault-tolerant quantum computers.
2024-09-17T00:00:00ZAnalytical and Computational Studies of Quasi-1D Spin ModelsChen, Yushaohttps://hdl.handle.net/10012/210012024-09-17T07:01:13Z2024-09-16T00:00:00Zdc.title: Analytical and Computational Studies of Quasi-1D Spin Models
dc.contributor.author: Chen, Yushao
dc.description.abstract: This thesis explores quasi one-dimensional (quasi-1D) quantum spin systems, specifically focusing on Kitaev ladders, Heisenberg ladders, and Motzkin chains. The research employs a combination of analytical and numerical tools to systematically study the phase diagrams of these low-dimensional spin lattices, developing a standardized pipeline for analyzing future models of interest within the field of quantum physics.
At the core of this investigation is the deep interconnection between low-dimensional quantum systems and their corresponding tensor network structures. Utilizing Matrix Product States (MPS) and the Density Matrix Renormalization Group (DMRG) methodologies, the thesis provides detailed insights into the phase behaviors of these quasi-1D systems. This includes examining novel phenomena such as quantum spin liquids, various magnetic orderings, and symmetry-protected topological orders. These findings not only enhance our understanding of quantum physics but also highlight the effectiveness and adaptability of tensor network approaches in tackling complex theoretical problems.
2024-09-16T00:00:00Z