Physical Sciences and Mathematics Commons^™

Probing Central Spin Decoherence Dynamics Of Electronic Point Defects In Diamond And Silicon, Ethan Que Williams

Dartmouth College Ph.D Dissertations

Electron spins of point defects in diamond and silicon can exhibit long coherence times, making them attractive platforms for the physical implementation of qubits for quantum sensing and quantum computing. To realize these technologies, it is essential to understand the mechanisms that limit their coherence. Decoherence of these systems is well described by the central spin model, wherein the central electron spin weakly interacts with numerous electron and nuclear spins in its environment. The dynamics of the resultant dephasing can be probed with pulse electron paramagnetic resonance (pEPR) experiments.

Using a 2.5 GHz pEPR spectrometer built in-house, we performed multi-pulse …

The Shifting Landscape Of Adolescent Wellness In Boarding Schools: Can Time Spent Off Screens And Outdoors Improve Adolescent Wellbeing?, Kristen H. Peterson

Dartmouth College Master’s Theses

For nearly twenty years I have worked directly with adolescents as an independent school educator. Whether in the classroom, on the field, or in the dorm, I have observed and supported students through their middle and high school experiences. During this time, I have witnessed an alarming shift in adolescent physical, emotional, and social wellbeing. Concurrently, I have observed a dramatic increase in the amount of time students spend using screen-based devices, and a decrease in their time spent outdoors.

Using research to ground my anecdotal accounts in empirical understanding, my thesis examines whether or not screen use might help …

Poster, Performed: Understanding Public Opinions Of Authorship In Generative Artificial Intelligence Models Via Analogy, Wylie Z. Kasai

Dartmouth College Master’s Theses

Over the last decade, generative artificial intelligence models have advanced significantly and provided the public with several tools to create new works of art. However, the true authorship of these works has been debated due to their training on web-scraped data. Serving as an analogy to these larger models, Poster, Performed is an interactive artificial intelligence exhibition project that uses image assets submitted by the public to create poster compositions with custom image processing algorithms. During the course of a four-day exhibition, visitors were asked to identify the exhibition’s primary artist from five options: (1) participants who submitted image assets, …

(Meta-)Physical Artworks: Digital Augmentation In Art Observation, Macy A. Toppan

Dartmouth College Master’s Theses

Augmented art— the subgenre of art that incorporates physical and digital artwork— is a rapidly growing field driven by advancing technology and a new generation for whom that tech is a given. Yet the presence of media like augmented and virtual reality in exhibition remains a controversial subject. Rather than focusing on the many theoretical debates about whether digital pieces can qualify as "good" art, we study it in practice through the eyes of the casual art observer. This paper highlights the audience in a within-participant study that asked viewers to take in a physical sculpture intentionally built with virtual …

A Bayesian Inversion For Emissions And Export Productivity Across The End-Cretaceous Boundary, Alexander A. Cox

Dartmouth College Master’s Theses

The end-Cretaceous mass extinction was marked by both the Chicxulub impact and the ongoing emplacement of the Deccan Traps flood basalt province. Both of these events perturbed the environment by the emission of climate-active volatiles, primarily CO2 and SO2. To understand the mechanism of extinction, we must disentangle the timing, duration, and intensity of volcanic and meteoritic environmental forcings. In this thesis, we used a parallel Markov chain Monte Carlo approach to invert for the aforementioned volatile emissions, export productivity, and remineralization from 67 to 65 million years ago using the LOSCAR (Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir) model. The parallel …

Probing And Enhancing The Reliance Of Transformer Models On Poetic Information, Almas Abdibayev

Dartmouth College Ph.D Dissertations

Transformer models have achieved remarkable success in the widest variety of domains, spanning not just a multitude of tasks within natural language processing, but also those in computer vision, speech, and reinforcement learning. The key to this success is largely attributed to the self-attention mechanism, particularly its ability to scale in performance as it grows in the number of parameters. Extensive effort has been underway to study the major linguistic properties learned by these models during the course of their pretraining. However, the role of certain finer linguistic phenomena present in language and their utilization by Transformers has not been …

Triple Helix: Ai-Artist-Audience Collaboration In A Performative Art Experience, Xuedan Zou

Dartmouth College Master’s Theses

Imagine an art exhibition that morphs its content according to the audience’s experience like a chameleon, reflecting the audience’s mind and culture and turning the artist’s exhibition into the viewer’s. But when the viewers leave, the work fades back to the creator’s original work and waits for the next audience. In this project, my team introduced an interactive exhibition called "Triple Helix," where audience members were provided the opportunity to alter the artworks created by the artist, thus imbuing them with their own perspectives. This interactive exhibition was held at three physical-locations and online, and a comprehensive user study was …

Equilibrium And Quench-Dynamical Studies Of Ultracold Fermions In Ring-Shaped Optical Traps, Daniel Gordon Allman

Dartmouth College Ph.D Dissertations

The unique capability to precisely tune the few and many-body configurations of
ultracold Fermi gases provides a multi-dimensional platform for studying novel, ex-
otic aspects of quantum systems. These aspects include superfluid/superconducting
phenomena supported by potentially exotic pairing mechanisms, non-equilibrium and
critical dynamics, and proposed quantum sensing or computing applications based on
atomtronics.
Ring geometries provide natural arenas for probing transport properties of super-
fluids. Metastable states of quantized superfluid flow —persistent currents— exhibit
remarkable properties, and the manner in which they form is an incredibly rich sub-
ject. Studies of quenched superfluids demonstrate that persistent currents can form
from …

Rough Numbers And Variations On The Erdős--Kac Theorem, Kai Fan

Dartmouth College Ph.D Dissertations

The study of arithmetic functions, functions with domain N and codomain C, has been a central topic in number theory. This work is dedicated to the study of the distribution of arithmetic functions of great interest in analytic and probabilistic number theory.

In the first part, we study the distribution of positive integers free of prime factors less than or equal to any given real number y>=1. Denoting by Phi(x,y) the count of these numbers up to any given x>=y, we show, by a combination of analytic methods and sieves, that Phi(x,y)<0.6x/\log y holds uniformly for all 3<=y<=sqrt{x}, improving upon an earlier result of the author in the same range. We also prove numerically explicit estimates of the de Bruijn type for Phi(x,y) which are applicable in wide ranges.

In the second part, we turn …

Energy-Aware Path Planning For Fixed-Wing Seaplane Uavs, Benjamin Atkinson Wolsieffer

Dartmouth College Master’s Theses

Fixed-wing unmanned aerial vehicles (UAVs) are commonly used for remote sensing applications over water bodies, such as monitoring water quality or tracking harmful algal blooms. However, there are some types of measurements that are difficult to accurately obtain from the air. In existing work, water samples have been collected in situ either by hand, with an unmanned surface vehicle (USV), or with a vertical takeoff and landing (VTOL) UAV such as a multirotor. We propose a path planner, landing control algorithm, and energy estimator that will allow a low-cost and energy efficient fixed-wing UAV to carry out a combined remote …

Development Of Single-Crystalline And 3d-Printable Porous Organic Materials, Mingshi Zhang

Dartmouth College Ph.D Dissertations

Porous organic materials with designable structures, large surface areas, low densities, and unique electronic and optical properties have found widespread applications in adsorption, separation, energy storage, and catalysis. However, the majority of organic porous materials are synthesized as fluffy powders, which poses two fundamental challenges for them. Firstly, they lack a single-crystal structure at the microscopic scale, making it difficult to study the specific pore size, shape, and potential substrate binding sites at the atomic level and further establish the structure-property relationship. Secondly, they lack the general processing method and macroscopic shape design, making it difficult to manufacture suitable components …

Predictive Ai For The S&P 500 Index, Jacqueline Rose Perry

Computer Science Senior Theses

Artificial intelligence has powerful applications in virtually every field, and the financial world is no exception. Utilizing various elements of artificial intelligence, this research aims to predict the future value of the S&P 500 index using numerous models, and in doing so, identify relevant features. More specifically, models that include combinations of historical data, public sentiment, and technical indicators were employed to predict the stock price one day and three days forward. To account for public opinion, the sentiment of tweets and news headlines from the beginning of 2015 through the end of 2019 was calculated using FinBERT, a pre-trained …

Self-Supervised Pretraining And Transfer Learning On Fmri Data With Transformers, Sean Paulsen

Dartmouth College Ph.D Dissertations

Transfer learning is a machine learning technique founded on the idea that knowledge acquired by a model during “pretraining” on a source task can be transferred to the learning of a target task. Successful transfer learning can result in improved performance, faster convergence, and reduced demand for data. This technique is particularly desirable for the task of brain decoding in the domain of functional magnetic resonance imaging (fMRI), wherein even the most modern machine learning methods can struggle to decode labelled features of brain images. This challenge is due to the highly complex underlying signal, physical and neurological differences between …

Anatoview: Using Interactive 3d Visualizations With Augmented Reality Support For Laypersons’ Medical Education In Informed Consent Processes, Michelle Chen

Dartmouth College Master’s Theses

AnatoView is an interactive multimedia educational application that visualizes medical procedures in three-dimensional (3D), augmented reality (AR) space. By providing visual and spatial information of medical procedures, AnatoView acts as a learning supplement for laypersons/patients in informed consent (IC) processes — wherein instructional content is traditionally limited to purely spoken explanations that lead to poor patient comprehension. We design a mixed study and conduct a randomized, controlled trial with 15 laypersons as participants: administering a traditional IC process to a control group, and an IC process supplemented by the use of AnatoView to experimental groups. As a primary outcome, medical …

Rhodium-Catalyzed Asymmetric Synthesis Of P-P And P-C Bonds, Sarah T. Chachula

Dartmouth College Ph.D Dissertations

Chapter 1: Synthesis, Structure, Dynamics, and Enantioface-Selective η3-Benzyl Coordination in the Chiral Rhodium Complexes Rh(diphos*)(η3-CH2Ph) Abstract: The rhodium benzyl complexes Rh(diphos*)(η3-CH2Ph) (1-14, diphos* = chiral bis(phosphine)) were prepared either by treatment of Rh(COD)(η3-CH2Ph) (15, COD = 1,5-cyclooctadiene) with diphos*, or from the reaction of [Rh(diphos*)(Cl)]2 (16- 20) with PhCH2MgCl. For C2-symmetric diphos*, observation of one set of NMR signals for complexes 1-12 suggested that the two diastereomers in which different 3-benzyl enantiofaces were coordinated to rhodium interconverted rapidly on the NMR time scale via suprafacial shifts; observation of five inequivalent aryl 1H NMR signals showed that antarafacial shifts were slow …

System-Characterized Artificial Intelligence Approaches For Cardiac Cellular Systems And Molecular Signature Analysis, Ziqian Wu

Dartmouth College Ph.D Dissertations

The dissertation presents a significant advancement in the field of cardiac cellular systems and molecular signature systems by employing machine learning and generative artificial intelligence techniques. These methodologies are systematically characterized and applied to address critical challenges in these domains. A novel computational model is developed, which combines machine learning tools and multi-physics models. The main objective of this model is to accurately predict complex cellular dynamics, taking into account the intricate interactions within the cardiac cellular system. Furthermore, a comprehensive framework based on generative adversarial networks (GANs) is proposed. This framework is designed to generate synthetic data that faithfully …

Say That Again: The Role Of Multimodal Redundancy In Communication And Context, Brandon Javier Dormes

Cognitive Science Senior Theses

With several modes of expression, such as facial expressions, body language, and speech working together to convey meaning, social communication is rich in redundancy. While typically relegated to signal preservation, this study investigates the role of cross-modal redundancies in establishing performance context, focusing on unaided, solo performances. Drawing on information theory, I operationalize redundancy as predictability and use an array of machine learning models to featurize speakers' facial expressions, body poses, movement speeds, acoustic features, and spoken language from 24 TEDTalks and 16 episodes of Comedy Central Stand-Up Presents. This analysis demonstrates that it is possible to distinguish between these …

The Dilemma Of Disclosure: Designing Interpersonal Informatics Tools For Mood Tracking, Daniel Earl Westphal

Computer Science Senior Theses

Mental health is a serious issue that affects people of all ages, but is especially prevalent amongst college age youth. In the 2020-2021 school year, researchers found that around 60% of college students met the criteria for at least one mental health condition, such as major depression or generalized anxiety disorder. Many digital interventions have been innovated in order to help address this issue. These range in type and functionality from teletherapy to medication tracking applications. Some of these digital interventions include social features that allow users to interact with other users, friends, family, or doctors; however, having social features …

Parameterization Of Cryosat-2 Radar Waveforms Across The Greenland Ice Sheet, Alexander Clark Ronan

Dartmouth College Master’s Theses

Geodetic surface mass balance calculations regularly rely on satellite radar altimeters such as CryoSat-2 to understand elevation and volume changes of the Greenland Ice Sheet (GrIS). However, the impact of changing GrIS shallow subsurface stratigraphic conditions on CryoSat-2 elevation products is poorly understood. We seek to investigate the long-term impacts of changing surface and shallow subsurface conditions on CryoSat-2 Level 2 elevation products derived from the Offset Center of Gravity (OCOG), Ocean - Customer Furnished Item (CFI), and University College London (UCL) Land-Ice retracking algorithms through the analysis of radar waveform characteristics. We further investigate time series from 2010 to …

Cosmological Vector Fields And Constraining The Neutrino Masses, Avery J. Tishue

Dartmouth College Ph.D Dissertations

In this thesis I explore two main topics: the role and consequences of cosmological vector fields, and new ideas for constraining fundamental physics with state-of-the-art experiments. These topics are disparate in content and technique but unified in their attempt to leverage novel approaches to better understand longstanding questions in cosmology. These questions, such as ``What is causing the universe to accelerate today?'' and ``What are the neutrino masses?'', underpin the modern cosmological paradigm. They play a key role in our understanding of cosmic history, the formation of structure, and the fate of our universe. Answers to or hints about these …

Information Diffusion In Online Social Networks: A Simulation Experiment, Maxwell Jacob Blum

Quantitative Social Science Undergraduate Senior Theses

The advent of online social networks has completely transformed the way we communicate, with news, opinions, and ideas now spreading faster than ever before (Guille et al., 2013; Lee et al., 2022). That online social networks have a profound impact on the spread of information suggests further investigation of the relationship between network structure and information diffusion (Light & Moody, 2020). This honors thesis investigates degree assortativity – a measure of large-scale network structure that has often only been a footnote in relevant literature on infor- mation diffusion in online social networks – and its effect on the speed of …

The Flow Of Power: Addressing Asymmetric Flood Risk In The Upper Valley, Eric Vr Hryniewicz

Geography Undergraduate Senior Theses

Floods are the most damaging natural disasters in America. Land use change in upland watersheds can increase the probability and severity of floods (Bronstert, Niehoff, & Burger, 2002). When watersheds are divided by political and private property boundaries it leads to a misalignment of incentives in which downstream users lack recourse for upstream land use decisions contributing to flood risk. In this thesis, researchers interrogate the attributes of town officials and towns that determine what motivates town governments to act on flooding and what motivates and enables town officials to collaborate on planning and how do they collaborate in practice. …

Sarcasm Detection In English And Arabic Tweets Using Transformer Models, Rishik Lad

Computer Science Senior Theses

This thesis describes our approach toward the detection of sarcasm and its various types in English and Arabic Tweets through methods in deep learning. There are five problems we attempted: (1) detection of sarcasm in English Tweets, (2) detection of sarcasm in Arabic Tweets, (3) determining the type of sarcastic speech subcategory for English Tweets, (4) determining which of two semantically equivalent English Tweets is sarcastic, and (5) determining which of two semantically equivalent Arabic Tweets is sarcastic. All tasks were framed as classification problems, and our contributions are threefold: (a) we developed an English binary classifier system with RoBERTa, …

Counterfactual Replacement Analysis For Interpretation Of Blackbox Sexism Classification Models, Anders Knospe

Computer Science Senior Theses

This paper describes the AKD team’s system designed for SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). We implement a simple fine-tuned GPT-3 model, ranking 26 on the leaderboard for task A. We also discuss different approaches to interpretability in the context of critiquing the EDOS task’s sub-category oriented approach. Finally, we propose counterfactual replacement analysis, a novel prototype technique for approaching explainability.

Jones Polynomial Obstructions For Positivity Of Knots, Lizzie Buchanan

Dartmouth College Ph.D Dissertations

The fundamental problem in knot theory is distinguishing one knot from another. We accomplish this by looking at knot invariants. One such invariant is positivity. A knot is positive if it has a diagram in which all crossings are positive. A knot is almost-positive if it does not have a diagram where all crossings are positive, but it does have a diagram in which all but one crossings are positive. Given a knot with an almost-positive diagram, it is in general very hard to determine whether it might also have a positive diagram. This work provides positivity obstructions for three …

Utilizing Mixed Graphical Network Models To Explore Parent Psychological Symptoms And Their Centrality To Parent Mental Health In Households With High Child Screen Usage, Piper F. Stacey, Nicholas C. Jacobson, Damien Lekkas

Computer Science Senior Theses

Especially among adolescents, screens are being used more than ever. In conjunction with this trend, mental illness is increasingly prevalent among both adults and children, and parental psychological problems are shown to be associated with children's TV watching, video watching, and gaming (Pulkki-Råback et al., 2022). This study aims to approach parent mental illness symptom by symptom to explore which specific symptoms are most central to parent psychological problems in households where children show high screen time behaviors. We draw from the Adolescent Brain Cognitive Development Study (ABCD Study®), a nationwide sample of 11,875 children aged 10-13 collected by …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Exploring Improvements To Space-Bounded Derandomization From Better Pseudorandom Generators, Boxian Wang

Computer Science Senior Theses

Saks and Zhou used Nisan’s PRG in a recursive manner to obtain BPL ⊆ L^(3/2). We describe how this framework could be generalized to use arbitrary PRGs following Armoni’s sampler idea. We then give a theorem relating the seed length of a better PRG to the implied improvements in derandomizing BPL. Recently, Hoza used Armoni’s PRG in the Saks-Zhou framework to obtain an even better derandomization. We describe the construction of Armoni’s PRG and conjecture that by using basic components other than extractors, parameters in that construction could be improved. Under some assumptions, we calculate the extent to which such …

Deep Learning For Skin Photoaging, Gokul Srinivasan

Computer Science Senior Theses

Skin photoaging is the premature aging of skin that results from ultraviolet light exposure. It is a major risk factor for the development of skin cancer, among other malignant skin pathologies. Accordingly, understanding its etiology is important for both preventative and reparative clinical action. In this study, skin samples obtained from patients with ranging solar elastosis grades – a proxy for skin photoaging – were sequenced using next-generation sequencing techniques to further understand the genomic, epigenomic, and histological signs and signals of skin photoaging. The results of this study suggest that tissues with severe photoaging exhibit increases in the frequency …

Interpreting Business Strategy And Market Dynamics: A Multi-Method Ai Approach, Lobna Jbeniani

Computer Science Senior Theses

This research paper presents an integrated approach that combines Long Short-Term Memory (LSTM), Q-Learning, Monte Carlo methods, and Text-to-Text Transfer Transformer (T5) to analyze and evaluate the business strategies of public companies. Leveraging a large and diverse dataset sourced from multiple reliable sources, the study examines corporate strategies and their impact on market dynamics. LSTM and Q-Learning are employed to process sequential data, enabling informed decision-making in simulated market environments and providing insights into potential outcomes of different strategies. The Monte Carlo method manages uncertainty, allowing for a comprehensive analysis of risks and rewards associated with specific strategies. T5 interprets …