Alumni Projects - Graduation Year: 2024
Hydrodynamic Quantum Field Theory Analogs
We explore the hydrodynamic quantum field theory, a model of quantum dynamics inspired by Louis de Broglie’s double-solution pilot wave theory and informed by the hydrodynamic pilot-wave system discovered by Couder and Fort in 2005. de Broglie originally proposed that every quantum particle contains an internal oscillation at the Compton frequency,... read more
Exploring Geometrical Properties of Chaotic Systems Through an Analysis of the Rulkov Neuron Maps
Dynamical systems theory is a branch of mathematical physics with countless applications to numerous fields. Some dynamical systems exhibit chaotic behavior, characterized by a sensitive dependence on initial conditions commonly known as the "butterfly effect." While extensive research has been conducted on chaos emerging from a dynamical system's ... read more
Chaos Modeling: A Comparison of Classical and Quantum Reservoir Computer Capabilities
Dynamic systems have always been an integral part of our world. Computational models are being explored for their potential of modeling dynamic systems ranging from storm development and wildfire behavior to natural language understanding and stock market prediction. The development of an RNN subfield known as Reservoir Computing (RC) has received ... read more
Development of a Scalable Silicon Photonic On-Chip Memory Architecture
Over the past decade, there has been a dramatic increase in the parameter count of neural networks, driven by advances in machine learning algorithms, hardware, and data availability. This increase has enabled significant improvements in performance on a wide range of tasks, from image classification to natural language processing. In 2012, the sta... read more
Simulating Self-Gravitating Dark Matter with Variational Quantum Computing
Galaxies have far too little observable matter for them to be gravitationally bound. Thus, there must be a theoretical, unobservable from of matter that makes up this missing mass: dark matter. Dark matter does not interact with light and we can only see its effects through gravitational lensing. The current leading candidates for dark matter are w... read more
Exploring Quantum Finance
Quantum Computing is unquestionably the future. There are 2 general architectures behind any quantum computer, quantum annealing or a gate based approach. Quantum annealing is a way to solve an incredible spectrum of optimization problems. Even better, there is only 1 company actually generating a profit using quantum computing, and that is DWAVE, ... read more
Tracking Microplastics with Quantum Machine Learning and Dynamics
Plastic pollution in the ocean has become a major concern in recent years. Approximately 400 million tons of plastic waste are generated annually, and when this plastic enters the ocean, it poses a threat to marine life. Microplastics, which are small plastic particles that break off from larger plastic clumps, are particularly hazardous. Thes... read more
Implementing Quantum Key Distribution using Photonics
Quantum Key Distribution (QKD) is a revolutionary cryptographic protocol that leverages the principles of quantum mechanics to establish secure communication channels. Unlike classical encryption methods, QKD relies on the fundamental properties of quantum states and ensures that any attempt to eavesdrop on the key exchange introduces detectable di... read more
Exploring a Model of Quantum Cognition
Math is useful because it creates and derivates quantifiable expressions to explain events that occur in reality. In this case, the amalgamation of Quantum theory into Cognitive Science attempts to patch holes inside the latter, such as the Disjunction Effect illustrated in the Prisoner's Dilemma, as a new branch known as Quantum Cognition. However... read more
Using Quantum ML and Analyzing Electro-Optical vs SAR Image Classification Through Polarizati
Intelligence agencies aim to find the most efficient methods to combat adversaries. The efficiency of image processing from satellite images is essential to ensure information about the world is being recorded. Two types of images, SAR and Electro-Optical Images, have different purposes, advantages, and disadvantages. SAR Images are reliable during... read more
Using Physics-Informed Neural Networks to Model the 2D Heat Equation
Partial differential equations (PDEs) are essential tools in various fields, but lack closed-form solutions, requiring approximation methods. Recent advancements like the Adomian domain decomposition method and the optimal auxiliary function method (OAFM) have improved PDE solution techniques, with OAFM offering linearization and efficient converge... read more
Exploring Fischer Koch S as a Photonic Crystal
Photonic crystals are nanomaterials with periodic refractive indices. Their periodic properties create photonic band gaps, which prohibit certain wavelengths from propagating through the material, such that it iridesces a specific range of colors when exposed to light. Recently, triply periodic minimal surfaces (TPMS) have been targeted as viable c... read more
Teaching Bell's Theorem and Entanglement Through Online Simulations
The recent Nobel Prize in physics was awarded to Alain Aspect, John Clauser, and Anton Zeilinger for their experiments with entangled photons, which showed a violation of Bell inequalities. One method of describing entanglement is quantum coin flipping, an idea that allows us to explore the connections to classical coin flipping. It uses qubit meas... read more
Building and Entangled Photon Pair Source
Photon pair sources are fundamental for quantum computing, optics, instrumentation, and experimentation, with numerous applications such as imaging cells and quantum key distribution. Spontaneous Parametric Down-Conversion (SPDC) is the most common and mature process used today to generate entangled photon pairs. It uses a non-linear crystal to pro... read more
Constrained Deep Learning Methods for Optimization of Autonomous Systems
The last few decades have led to the rise of research focused on propulsion and control systems for bio-inspired unmanned underwater vehicles (UUVs), which provide more maneuverable alternatives to traditional UUVs in underwater missions. Recent work has explored the use of time-series neural network surrogate models to predict thrust and power f... read more
Quantum Holography
Holography is a method of representing a 3D object in a 2D way. Classical holography exists in many forms, from transmission to rainbow. However, quantum holography is much rarer, in which it uses quantum entanglement, where the state of one particle becomes inextricably linked with another's, regardless of spatial separation, to create a hologram.... read more
Using Quantum Agents to Model Simple Economies
Agent-based modeling can study any social behavior and decision-making process, as agents make decisions based on an internal logic network and try to imitate human behavior. Proponents say that models based on agent interactions can inspire insight into policy and predict aggregate human behavior. Detractors concern themselves with the applicabili... read more
Generative Modeling with the Yukawa Potential
Diffusion models, the current state-of-the-art in image generation, have led the charge in generative modeling for several years. We provide a theoretical derivation and implementation of a new generative model based on the Yukawa potential. This model is the first of a new generation of models with nonzero birth rates, offering for more creative, ... read more
Engineering Artificial Muscles
Long title: SPARK’EM: Simulating (nanocomposite) Polymers via Ab-Initio methods to realize to Realize high-(K)apacitance Elastomeric Artificial Muscles
Hydraulically amplified self-healing electrostatic actuators, or HASELs, are an emerging class of dielectric elastomeric actuators that mimic the behavior of human muscular systems. By permeating... read more
Detecting and Identifying Floor Vibrations through Interferometers
Interferometers are laser-based investigative tools that are highly sensitive to vibrations. Because of this, when placed on the floor, they can detect the small differences between the walking styles of different people, meaning that, if attached to a sufficiently trained neural network, we can discern the identity of a person who is walking witho... read more
An Exploration into Dynamic Spin Chemistry: Improving NMR Resolution
Nuclear magnetic resonance(NMR) is a powerful technique to resolve structural information about molecules. Of particular interest is NMR of proteins, where understanding the structural properties takes an especial importance. However, NMR techniques are limited by resolution. In proteins with potential molar masses in the multiple thousands, reso... read more
Using Quantum Control to Achieve Spectral Super-resolution
Quantum systems have long shown promise for detecting low magnitude environmental effects such as electric and magnetic fields. We consider the use of quantum systems to detect time-varying electromagnetic signals. Expanding on a recent application of quantum sensing obtaining spatial super-resolution in optical imaging, we aim to apply super-resol... read more
Analyzing Complexity in Variational Quantum Algorithms
Variational quantum algorithms are a class of algorithms which make use of both classical and quantum techniques to solve a problem. The quantum approximation optimization algorithm (QAOA) is one such algorithm which focuses on solving combinatorial optimization problems. In this study, we numerically approximate the computational complexity of the... read more
Optimization of Traffic Lights Using Quantum Behaving Particles
Particle swarm optimization (PSO) is an optimization algorithm that mimics the flocking behavior of birds, ants, and other animals in order to discover the minimum of a cost function. We implemented and improved quantum particle swarm optimization (QPSO), a variation of PSO representing each particle as a quantum wave-function. We tested various po... read more
Implementing QKD-Encrypted Hybrid Quantum Machine Learning for Dementia Detection
Magnetic resonance imaging (MRI) is a common technique to scan brains for strokes, tumors, and other abnormalities that cause forms of dementia. However, correctly diagnosing forms of dementia from MRIs is difficult, leading to misdiagnoses, an issue neural networks can rectify. The performance of these neural networks has been shown to be improved... read more
BlochAR: Developing a Manipulative Bloch Sphere Implemented as an Augmented Reality (AR) Application
The Bloch sphere is a geometrical representation of the pure state space of a two-level quantum mechanical system. The realistic visualization of quantum states through the Bloch sphere will provide an intuitive understanding of complex quantum phenomena, which can often seem abstract and counterintuitive. Our project aims to revolutionize educatio... read more
Building a Magneto-Optical Trap
A Magneto-Optical Trap (MOT) uses lasers to slow ions down to extremely low speeds in a millikelvin temperature range so their quantum properties can be studied. Existing MOTs have thus far been used to cool and slow down twenty elements, with the creators receiving the Nobel Prize in Physics in 1997. Using the MOT to study atoms can reveal insight... read more
On Optimizing Quantum Cosmological Simulations of Self-Gravitating Dark Matter
Today, visible matter makes up less than 5% of the total mass in the universe. The rest of the mass can be largely attributed to an invisible matter known as dark matter. Although dark matter is invisible, it is integral to the structure of the universe, as galaxies, clusters, and other deep sky objects are primarily composed of dark matter. Becaus... read more
Partial Least-Squares Quantum Optimization
Previously, I used a partial least squares (PLS) implementation to predict March Madness brackets, called the Massey Method. I learned that, although accurate, it was a very slow algorithm. My ultimate goal for this project is to optimize the classical implementation of a least squares algorithm using the Quantum Approximate Optimization Algorithm ... read more
Transferring Quantum Populations Using STIRAP
One of the biggest hurdles in modern-day quantum physics is figuring out how to transfer quantum populations from one state to another. Stimulated Raman Adiabatic Passage (STIRAP) aims to solve this problem by creating an efficient, active method of transfer. STIRAP relies on three-state pulsed stimulated Raman scattering (SRS). Raman scattering in... read more