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Articles 781 - 810 of 91485
Full-Text Articles in Entire DC Network
Phases And Dynamics Of An Impurity Immersed In One-Dimensional Quantum Droplets, Dimitrios Diplaris, Ilias A. Englezos, Friethjof Theel, Peter Schmelcher, Simeon I. Mistakidis
Phases And Dynamics Of An Impurity Immersed In One-Dimensional Quantum Droplets, Dimitrios Diplaris, Ilias A. Englezos, Friethjof Theel, Peter Schmelcher, Simeon I. Mistakidis
Physics Faculty Research & Creative Works
We explore the ground-state properties of a single impurity immersed in a one-dimensional quantum droplet medium formed by a two-component Bose mixture. Relying on ab initio simulations, we demonstrate that tuning the impurity–droplet interactions allows to controllably reshape the droplets' density profiles and associated correlation patterns. For attractive impurity-medium couplings, the impurity becomes localized within the droplet, which exhibits a density hump at the vicinity of the impurity, while repulsive interactions facilitate phase separation. Comparing our many-body results with the appropriate extended Gross–Pitaevskii description, we find adequate agreement for the droplet density profiles, with the effective field approach systematically overestimating …
High-Pressure Studies Of Magnetic Topological Materials, Greeshma Chireckal Jose
High-Pressure Studies Of Magnetic Topological Materials, Greeshma Chireckal Jose
ETDs from 2020-2029
Quantum technology leverages the principles of quantum mechanics to transform emerging fields such as quantum computing, spintronics, and next-generation electronics. A crucial step in advancing this frontier is the detailed understanding of fundamental quantum phenomena in materials that can drive quantum innovation. This research aims to systematically investigate quantum phase transitions and unconventional emergent behaviors in magnetic topological materials subjected to external pressure. This study focuses on three representative systems: EuCd2As2, EuMnBi2, and FeSn, each serving as a model for exploring intrinsic magnetic topological states. EuCd2As2, a candidate Weyl semimetal (WSM), is expected to exhibit pressure-induced topological phase transitions, making …
Inverse Modeling The Geo-Spread Of Covid-19 In Brazil, Cameron Keith Mills
Inverse Modeling The Geo-Spread Of Covid-19 In Brazil, Cameron Keith Mills
ETDs from 2020-2029
In 2021 Fitzgibbon, Morgan, Webb, and Wu used a modified SEIR (susceptible, exposed, infected, and recovered) model to predict how COVID-19 spread through Brazil [12]. For their model, six constant coefficients were used that were fitted, referenced, or assumed. In this thesis, we geo-spatially modify their SEIR model and formulate an inverse problem to recover the now spatial coefficients of the model. We first show there exists a unique solution to the modified model. To solve the inverse problem, we modify an inverse method [17] that focused on minimizing convex functionals. These recovered spatial coefficients can be used with Matlab’s …
“From Remembering To Shaping”: Narrating Shared Experiences By Co-Designing Cultural Heritage Artifacts In Collaborative Vr, Yushang Yang, Fanxu Meng, Fiona Fui-Hoon Nah, L. C. Ray
“From Remembering To Shaping”: Narrating Shared Experiences By Co-Designing Cultural Heritage Artifacts In Collaborative Vr, Yushang Yang, Fanxu Meng, Fiona Fui-Hoon Nah, L. C. Ray
Research Collection School Of Computing and Information Systems
The ways people remember and recall places reveal an invisible aspect of cultural heritage (CH), reflecting how individuals and communities relate to these places. Heritage is communal, emerging through collaboratively constructed narratives rather than individual records. To probe how people may share collective memories, we designed an immersive two-person workflow for collaboratively co-designing 3D artifacts and environments in virtual heritage locations, using Generative AI (GenAI) to instantiate these intangible memories. Observations of the co-creation process revealed that participants merged prompts and model placements when negotiating different perspectives. They used spatial operations to compose scenes, and also to express personal and …
Equitable Decompositions: A Gateway To Spectral Theory Through Graph Automorphisms, Daniel Ford
Equitable Decompositions: A Gateway To Spectral Theory Through Graph Automorphisms, Daniel Ford
Master's Theses
Graphs with symmetry appear throughout mathematics and its applications, from the structure of molecules and network design to combinatorial game theory. A central question in spectral graph theory is how to compute or characterise the eigenvalues of the matrices associated with such graphs. Classical decomposition methods, such as diagonalisation or Jordan normal form, accomplish this but only once some spectral information is already known. A different approach, introduced by Barrett et al. (2015), uses the automorphisms of a graph to block-diagonalise its adjacency matrix without any prior spectral information. Because one of the resulting summands is always the quotient matrix …
Determining K Clusters In K-Means Clustering With The Crab Algorithm, Jasmine Kristine S. Cabrera
Determining K Clusters In K-Means Clustering With The Crab Algorithm, Jasmine Kristine S. Cabrera
Master's Theses
Unsupervised clustering often faces the challenge of determining the correct number of clusters in the absence of a true target variable. Traditional methods such as the Elbow Method and the Silhouette Score can produce ambiguous results and rely on assumptions about cluster shape or separation. To address this, we created the Clustering Rivals and Buddies (CRAB) algorithm which evaluates clusters based on stability across multiple subsamples. CRAB uses pairwise classifications to identify points that consistently group together called “Buddies” and points that remain separated called “Rivals.” Applied with K-means, CRAB accurately recovers underlying cluster structures in both spherical and non-spherical …
(R2133) Analysis Of A Bulk Queue With Balking, Adaptive Overloading Service, Multiple Vacation, Inspection And Rework, S. Karpagam, R. Lokesh
(R2133) Analysis Of A Bulk Queue With Balking, Adaptive Overloading Service, Multiple Vacation, Inspection And Rework, S. Karpagam, R. Lokesh
Applications and Applied Mathematics: An International Journal (AAM)
We consider a queueing system that utilizes a single server to manage product flow through bulk and overload service modes, depending on queue length. Balking occurs when the queue length reaches ‘N’. After completion of service, products undergo quality inspection, with defective products sent for rework based on specific probabilities. If the product is non-defective, the server continues processing until the queue length exceeds a certain threshold; beyond this point, the server is either routed back to bulk service or directed to an overload service. Also, the server goes into a vacation mode when the queue size is below a …
The Implementation Of Scintillation Detectors With The Cuore/Cupid Collaboration In The Search For Neutrinoless Double Beta Decay, Reese Sandra Cormier
The Implementation Of Scintillation Detectors With The Cuore/Cupid Collaboration In The Search For Neutrinoless Double Beta Decay, Reese Sandra Cormier
Physics
CUORE (Cryogenic Underground Observatory for Rare Events) is an experiment at the Gran Sasso National Laboratory in Assergi, Italy, currently searching for an answer to the matter-antimatter asymmetry problem; the question: why do we exist? One proposed explanation is neutrinoless double beta decay, a theorized exotic decay that would prove that neutrinos are their own antiparticle, violating the current Standard Model for particle physics. However, current detection methods do not distinguish different types of particle interactions, resulting in alpha decays contributing to the background. Therefore, the experimental sensitivity is too limited to make confident determinations about the data. For this …
Incipient: Contemporary Wildfire Management In The American West, Carlyn A. Mcaleer
Incipient: Contemporary Wildfire Management In The American West, Carlyn A. Mcaleer
Environmental Studies Senior Theses
The frequency, severity, and total area burned by wildfires has escalated dramatically alongside a similar increase in federal suppression spending. However, contemporary management remains rooted in a suppression‑centric framework that originated in the early‑20th‑century. Our current wildfire management practices are unsustainable in the face of this growing threat. Using an approach that blends historical analysis and spatial analysis, this thesis asks how current spatial patterns of burn probability (BP) overlap with existing fire-response infrastructure and population in eight states (Arizona, Colorado, Idaho, Montana, New Mexico, Nevada, Utah, Wyoming) in the American West and which barriers inhibit the adoption of proactive …
Control And Entrainment Of Oscillatory Dynamics In An Oncolytic Virus–Tumor Model Under Periodic Therapy Forcing, Aya Salaheddin Shujrawi
Control And Entrainment Of Oscillatory Dynamics In An Oncolytic Virus–Tumor Model Under Periodic Therapy Forcing, Aya Salaheddin Shujrawi
Theses
This thesis investigates the dynamics of a tumour–virus interaction model under sinusoidal periodic viral injection, using the three-compartment ordinary differential equation framework of Baabdulla and Hillen (2024). The aim is to characterise how the frequency and amplitude of periodic injection interact with the system's intrinsic oscillatory dynamics, and to identify conditions for stable frequency entrainment. Equilibrium and Hopf bifurcation analysis of the autonomous system yields a supercritical bifurcation at θ_H^auto ≈ 338.45 with intrinsic frequency Ω0auto ≈ 0.7552. Introducing a constant baseline injection u0 = 0.05 raises the threshold to θHforced ≈ 364.85 and shifts …
Comparing The Sensitivity And Degree Of Boolean Functions Via The Hypercube, Anne-Caroline Rupp
Comparing The Sensitivity And Degree Of Boolean Functions Via The Hypercube, Anne-Caroline Rupp
University Honors Theses
This thesis studies three complexity measures of total Boolean functions f:{0,1}n → {0,1}: maximum sensitivity s(f), polynomial degree deg(f), and spectral sensitivity λ(f), where λ(f) is defined as the spectral norm of the adjacency matrix of the sensitivity graph. Building on the results of Aaronson et al., we examine the inequality chain √s(f) ≤ λ(f) ≤ deg(f) and investigate whether all three quantities can be simultaneously equal.
The first part of the thesis reverse engineers the equality cases of the two known inequalities to isolate necessary extremal conditions on both the Fourier structure of f and the local geometry …
The Security Of Llm-Generated Code, Christopher Brian Gonzalez Ayala
The Security Of Llm-Generated Code, Christopher Brian Gonzalez Ayala
Student Theses
The rapid adoption of Large Language Models (LLMs) in software development has transformed coding practices by enabling automated code generation, completion, and optimization. Despite these advantages, concerns persist regarding the security and reliability of LLM-generated code. This study presents a comprehensive evaluation of both the functional correctness and security of code produced by three prominent LLMs as of early 2026. A total of 4,800 code snippets were generated using 100 security-focused programming prompts derived from the OWASP Top 10:2025, translated across eight natural languages and two phrasing styles (literal and natural developer-oriented prompts). To assess performance, a multi-stage experimental framework …
Forensic Analysis Of Temporary Tattoo Markers And Inks, Daniel J. G. Chasse Jr
Forensic Analysis Of Temporary Tattoo Markers And Inks, Daniel J. G. Chasse Jr
Student Theses
As tattoos rise in popularity, some marker manufacturers have created temporary tattoo markers so that children and adults can experience tattoos without the permanence of a regular tattoo. These new products are marketed explicitly as ‘temporary tattoo markers’ and intended for direct application to the skin. This research aims to scientifically evaluate the inks from these temporary tattoo markers to elucidate their physical and chemical properties using wet chemistry, visual examination, ultraviolet-visible spectroscopy (UV/Vis), Fourier-transform infrared spectroscopy (FT-IR), attenuated total reflectance infrared spectroscopy (ATR-IR), thin layer chromatography (TLC), and diffuse reflectance infrared spectroscopy (DRIFTS) to analyze temporary tattoo markers and …
Adversarial Robustness Of Perceptual Hashing Systems: A Unified Security Evaluation Framework, Avijit Roy
Adversarial Robustness Of Perceptual Hashing Systems: A Unified Security Evaluation Framework, Avijit Roy
Student Theses
Social network platforms, child safety organizations, and image provenance systems use perceptual hashing to identify known child sexual abuse material (CSAM), support content moderation and reverse image search, and verify image integrity. Perceptual hashing works by producing similar fingerprints for visually similar images, even after common transformations such as compression, resizing, or minor brightness changes. This useful similarity-preserving property also creates an adversarial attack surface, as attackers can use AI-assisted or conventional image manipulation techniques to move a hash across a matching threshold while maintaining visual similarity, often without access to specialized hardware.
The security failures produced by adversarial attacks …
The Comparative Chemical Analysis Of Colored Henna, Vani D. Bhagwandeen
The Comparative Chemical Analysis Of Colored Henna, Vani D. Bhagwandeen
Student Theses
Henna, a natural dye derived from Lawsonia inermis, is widely used for temporary body art, hair coloring, and cultural decorative practices such as Mehendi. Traditional henna produces a reddish-brown stain through lawsone, a naphthoquinone chromophore that binds to keratin in skin, hair, and nails (Badoni Semwal et al., 2014; de Groot, 2013; Kumar Singh et al., 2015). Commercial henna products have increasingly incorporated synthetic dyes, pigments, and glitter additives to produce a broader range of colors and effects (Blair et al., 2004; Manso et al., 2017; Blackledge & Jones, 2007). Despite their prevalence, limited forensic research has examined the …
When Saying "No" Is Not Enough: Cognitive-Action Decoupling And The Illusion Of Safety In Llm Agents, Shasha Yu
When Saying "No" Is Not Enough: Cognitive-Action Decoupling And The Illusion Of Safety In Llm Agents, Shasha Yu
School of Professional Studies
Current safety evaluations of large language models (LLMs) predominantly rely on textual compliance, implicitly assuming that refusal-style responses correspond to safe behavior. This assumption becomes fragile when LLMs are embedded in agentic systems with the ability to execute state-changing actions. In this paper, we present an empirical critique of text-centric safety evaluation through an action-aware study of LLM agents under controlled conditions. Across multiple state-of-the-art models, we observe a recurring cognitive-action decoupling: agents generate policy-aligned refusal language while still producing unsafe tool-mediated action proposals. This produces an illusion of safety, where conversational audits indicate compliance even as operational risk persists. …
Trace: Temporal Rhetorical Analysis And Consistency Evaluation For Legislative Speech, David Hernandez
Trace: Temporal Rhetorical Analysis And Consistency Evaluation For Legislative Speech, David Hernandez
Master's Theses
Legislators frequently discuss the same policy issues across multiple hearings and legislative sessions, sometimes maintaining consistent positions and other times modifying or reframing their stance over time. Understanding how these positions evolve is important for analyzing political discourse and democratic accountability, yet identifying such shifts at scale remains difficult.
We introduce TRACE (Temporal Rhetorical Analysis and Consistency Evaluation), a system built on the Digital Democracy Database (DDDB) for detecting rhetorical inconsistency in California legislative hearing testimony. TRACE organizes utterances into speaker-anchored timelines indexed by bill and session, then applies hybrid semantic retrieval — combining dense BGE embeddings with BM25 lexical …
Spatiospectral Lobes And Radiation Modeling Of Partially Coherent Supersonic Jet Noise, Tyce Wayne Olaveson
Spatiospectral Lobes And Radiation Modeling Of Partially Coherent Supersonic Jet Noise, Tyce Wayne Olaveson
Theses and Dissertations
Noise fields generated by high-performance military jets are known to contain acoustic structures that differ from their simulated and lab-scale counterparts. These differences may limit current noise control efforts, which are designed and tested at scale before being considered for full-scale aircraft. One such noise structure is the presence of spatiospectral lobes, which appear as multiple spectral peaks at single microphone locations and multiple radiation lobes in field reconstructions. This dissertation uses data collected from the T-7A jet noise measurement to characterize the spatial behavior of the spatiospectral lobes as well as their first time-domain description. A multiple wavepacket decomposition …
Daily Rainfall Forecasting Over West Bengal With Spatio-Temporal Graph Networks, Risheek Ghosh
Daily Rainfall Forecasting Over West Bengal With Spatio-Temporal Graph Networks, Risheek Ghosh
Master’s Dissertations
Daily rainfall is hard to forecast where most days are dry, a few days are very wet, and almost all of the rain arrives in one season. This dissertation studies day-ahead rainfall forecasting over West Bengal, India, using models that learn from both the temporal and the spatial layout of measuring stations. We first build up a forecasting model in stages, from simple models that look at one station’s past to a graph-based model that links nearby stations, and we identify the strongest deterministic forecaster among them. We then ask whether the choice of input data changes the story, by …
Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn
Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn
Department of Agricultural and Biological Systems Engineering: Faculty Publications
The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …
Mathematical Models Of Multisensory Detection And Decision-Making, Rebecca M. Brady
Mathematical Models Of Multisensory Detection And Decision-Making, Rebecca M. Brady
Doctoral
The brain seamlessly integrates signals from multiple sensory modalities to interpret the world efficiently. By using information from various senses, the brain can enhance its ability to detect and respond to stimuli more quickly and accurately. However, combining sensory cues from multiple modalities is only sometimes beneficial as it may lead to illusions and reduced behavioural performance. Behavioural and electrophysiological experiments have revealed that detection and decision-making strategies for multisensory cues evolve throughout human development and ageing. Additionally, studies have demonstrated that maladaptive multisensory processing is a key indicator of a proclivity to falls in older adults and individuals with …
Ai, Medicine, And Social Determinants Of Health Data, Ryan Doyloo, Nicholson Price
Ai, Medicine, And Social Determinants Of Health Data, Ryan Doyloo, Nicholson Price
Articles
This article examines how medical AI systems are incorporating SDoH data and the governance challenges that follow. The authors show that while SDoH integration can enhance clinical workflows and predictive accuracy — potentially improving outcomes for underserved populations — it also introduces acute risks of proxy discrimination, where facially neutral variables replicate protected characteristics. Surveying U.S., EU, and international frameworks, the authors argue that existing regimes lack clear ex ante guidance to distinguish beneficial from harmful uses of SDoH data. In response, they advance post-market monitoring as a pragmatic and scalable pathway: generating real-world, SDoH-stratified evidence that can support enforcement, …
On-The-Fly Generation-Quality Enhancement Of Deep Code Models Via Model Collaboration, Weifeng Sun, Naiqi Huang, Meng Yan, Zhongxin Liu, Hongyan Li, Yan Lei, David Lo
On-The-Fly Generation-Quality Enhancement Of Deep Code Models Via Model Collaboration, Weifeng Sun, Naiqi Huang, Meng Yan, Zhongxin Liu, Hongyan Li, Yan Lei, David Lo
Research Collection School Of Computing and Information Systems
The growing prominence of deep code models in automating software engineering tasks is undeniable. However, their deployment encounters significant challenges in on-the-fly performance enhancement, which refers to dynamically improving the performance of deep code models during real-time execution. Conventional techniques, such as retraining or fine-tuning, are effective in controlled pre-deployment scenarios but fall short when adapting to on-the-fly adjustments post-deployment. CodeDenoise, a notable on-the-fly performance enhancement technology, leverages uncertainty-based methods to identify misclassified inputs and applies an input modification strategy to rectify classification errors. While effective for classification tasks, this approach is inapplicable to generative tasks due to two key …
Sam3-Litetext: An Anatomical Study Of The Sam3 Text Encoder For Efficient Vision-Language Segmentation, Chengxi Zeng, Yuxuan Jiang, Ge Gao, Shuai Wang, Duolikun Danier, Bin Zhu, Stevan Rudinac, David Bull, Fan Zhang
Sam3-Litetext: An Anatomical Study Of The Sam3 Text Encoder For Efficient Vision-Language Segmentation, Chengxi Zeng, Yuxuan Jiang, Ge Gao, Shuai Wang, Duolikun Danier, Bin Zhu, Stevan Rudinac, David Bull, Fan Zhang
Research Collection School Of Computing and Information Systems
Vision-language segmentation models such as SAM3 enable flexible, prompt-driven visual grounding, but inherit large, general-purpose text encoders originally designed for open-ended language understanding. In practice, segmentation prompts are short, structured, and semantically constrained, leading to substantial over-provisioning in text encoder capacity and persistent computational and memory overhead. In this paper, we perform a large-scale anatomical analysis of text prompting in vision–language segmentation, covering 404,796 real prompts across multiple benchmarks. Our analysis reveals severe redundancy: most context windows are underutilized, vocabulary usage is highly sparse, and text embeddings lie on a low-dimensional manifold despite high-dimensional representations. Motivated by these findings, we …
Co-Designing With Autistic Livestreamers: Care, Constraints, And Trade-Offs In Livestreaming, Terrance Mok, Anthony Tang, Lora Oehlberg
Co-Designing With Autistic Livestreamers: Care, Constraints, And Trade-Offs In Livestreaming, Terrance Mok, Anthony Tang, Lora Oehlberg
Research Collection School Of Computing and Information Systems
Autistic livestreamers use platforms like Twitch for social connection, self-expression, and community, but these spaces also impose ongoing social and emotional demands. Prior work has documented these experiences, but less is known about what autistic creators themselves envision for the tools and platforms they use. We address this gap through a Research through Design (RtD) co-design study with three autistic Twitch streamers, using speculative artefacts as discussion prompts to explore how participants reasoned about potential livestreaming technologies. Across three co-design activities, we identify three overarching tensions shaping autistic streaming practice: Expression versus Misinterpretation and Harm; Public Participation versus Control and …
“Grandpa, Can You Speak Nicer?”: Envisioned Chatbot Roles And Design Tensions In Intergenerational Communication Conflicts, Tianyi Zhang, Emran Bin Elias Poh, Yueyue Hou, Yi-Chieh Lee, Renwen Zhang, Jiannan Li, Anthony Tang
“Grandpa, Can You Speak Nicer?”: Envisioned Chatbot Roles And Design Tensions In Intergenerational Communication Conflicts, Tianyi Zhang, Emran Bin Elias Poh, Yueyue Hou, Yi-Chieh Lee, Renwen Zhang, Jiannan Li, Anthony Tang
Research Collection School Of Computing and Information Systems
Intergenerational conversations often break down when differences in tone, language, or expectations lead participants to feel dismissed or misunderstood. In this work, we explore how people envision AI-driven chatbot interventions for addressing communication problems in text-based intergenerational family chat. We conducted a scenario-based design interview with 10 pairs of family members from different generations, in which participants designed chatbot interventions that varied in intervention target and timing. Our findings show that participants expect chatbots to perform multiple themes of intervention, including mediating understanding, providing emotional support, offering evaluative commentary, and guiding interaction through behavioral suggestions. These expectations varied systematically across …
Towards Auto-Evaluation For Large Language Models, Jiahao Ying
Towards Auto-Evaluation For Large Language Models, Jiahao Ying
Dissertations and Theses Collection (Open Access)
The rapid advancement of large language models (LLMs) has created an urgent need for evaluation methodologies that are timely, scalable, reliable, and informative. Conventional evaluation benchmarks, although essential for measuring model capabilities and guiding model development, are often constructed and maintained through labor-intensive human annotation. As LLMs continue to improve through increases in model scale, training data, and computational resources, static benchmarks may quickly lose discriminative power. Moreover, the growing use of large and diverse training corpora increases the risk of benchmark leakage, which can inflate evaluation results and obscure the true capabilities of models. These challenges call for a …
Crab: A Novel Clustering Score Using Clustering With Rivals And Buddies For Unsupervised Learning, Allen Choi
Crab: A Novel Clustering Score Using Clustering With Rivals And Buddies For Unsupervised Learning, Allen Choi
Master's Theses
Unsupervised clustering algorithms today are used across a wide variety of fields such as biology, engineering, and industry in order to classify observations into groups where labels are not provided. This can provide important latent information regarding the observations within groups, as well as insight regarding the groups themselves. In order to judge the optimal number of clusters for an unsupervised clustering algorithm, many methods exist such as the Elbow Method and Silhouette Score; however, these methods come with drawbacks and are not necessarily flexible across many unsupervised methods. We present a novel clustering score framework relying on a resampling-based …
Of Climate Justice And Magical Realism, Sonya Ziaja
Of Climate Justice And Magical Realism, Sonya Ziaja
Michigan Law Review
A review of Climate Justice: What Rich Nations Owe the World—and the Future. By Cass R. Sunstein.
50,000 Spectra And Counting: Preparing For A Roman Spectral Atlas, Maya Jordan Seagraves
50,000 Spectra And Counting: Preparing For A Roman Spectral Atlas, Maya Jordan Seagraves
Master's Theses
Slitless spectroscopy with the Hubble Space Telescope's Wide Field Camera 3 \linebreak (WFC3/IR) enables simultaneous spectral coverage of all sources in a field, but large-scale single-orientation datasets remain challenging to process. We developed a pipeline that automates HSTaXe spectral extraction across hundreds of Hubble Space Telescope observations, enabling efficient processing of 84 fields and producing over 50,000 spectra from three filters (F110W, F125W, and F160W) and two grisms (G102 and G141). This was achieved by creating a companion Python package, the Module for Infrared Label Analysis (MILA), that integrates data calibration, extraction, and visualization. To assess the scientific utility of …