150813 research outputs found
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Quantum Gas Microscopy of Bosonic Correlations in the Continuum
No full textThis thesis details the complete upgrade and renovation of an existing experimental platform into a high-resolution quantum gas microscope for ultracold 87Rb atoms. Quantum gas microscopes enable site-resolved imaging, providing unprecedented access to quantum statistical effects and many-body phenomena. While such instruments are often employed to study physics in optical lattices, we have innovatively adapted our apparatus to investigate bulk system behavior. A major part of this project involved upgrading the scientific apparatus and retrofitting the previous system. We introduced new optical components, including a high-NA objective, and improved the vacuum system for better optical access. Extensive lab renovations, from upgrading the optical table to reorganizing the laser and imaging setups, were carried out to enhance mechanical and thermal stability. Rigorous optical benchmarking confirmed that the objective achieves diffractionlimited imaging, which is critical for resolving single atoms. This capability allowed us to detect density fluctuations at the scale of the thermal de Broglie wavelength in a quasi-two-dimensional gas of 87Rb atoms. In an experiment resembling Hanbury Brown and Twiss interferometry, we measured a 30% enhancement in the second-order correlation function in situ, demonstrating strong bosonic bunching. This outcome underscores the microscope’s precision and the importance of high-resolution imaging in capturing subtle quantum statistical effects. The successful realization of this apparatus demonstrates the utility of quantum gas microscopes in probing bulk systems. With this new platform in place, future studies can explore critical phenomena, many-body correlations, matter-wave emission, and quantum simulations with cold atoms.Ph.D
DisViz: Visualizing real-world distributed system logs with space time diagrams
No full textThis thesis aims to provide an intuitive debugging and learning tool for distributed systems that communicate by message passing. Understanding and debugging distributed systems can be challenging and slow to iterate on, so there is a need for tools that can speed up the time it takes to diagnose the root cause of a bug. There exists significant prior work in creating tools that can aid in the visualization and debugging of distributed system executions, such as the ShiViz log visualizer [13]. This work builds on top of these tools to provide more debugging information, handle large log files, and be easily instrumented in existing systems. We demonstrate using the tool to debug issues in an implementation of the Raft consensus algorithm [34].M.Eng
Report to the President for year ended June 30, 2025, MIT Alumni Association
No full textThis report contains the following sections: Overview, FY25 MIT Alumni Association Highlights - Events, Philanthropy, Programs, Communications, and Benefits, MITAA Board and Volunteer Leadership, Institute Partnerships, and Organizational Infrastructure; and The MIT Alumni Community by the Numbers (Data as of July 1, 2025)
Design and Commercialization Strategy of a Gantry-Based Automation Platform for High-Throughput Raman Spectroscopy
No full textRaman spectroscopy is a powerful optical technique that enables rapid, label-free molecular analysis. This offers significant potential to be used across pharmaceutical development, microbiome research, and food diagnostics. However, the utility of Raman spectroscopy in high-throughput applications has been limited by the lack of cost-effective, modular automation platforms capable of handling large volumes of samples with precision and repeatability. Conventional Raman workflows are constrained by manual sample handling, slow throughput, and high user variability, limiting their applicability in high-volume testing environments. To address these challenges, this thesis presents the development and initial validation of a custom two-axis (XY) gantry and a robotic well plate stacker automation platform designed to streamline the sample handling workflow in Raman spectroscopy systems, facilitating high-throughput, precise, and reproducible positioning of microplate samples under a Raman microscope. This thesis also provides a commercialization framework for the system as a standalone automation product, targeting pharmaceutical high-throughput screening, microbiome analysis, and food safety testing. The platform serves the unmet needs in these industries, where labor-intensive and inconsistent sample positioning limits scalability. The commercialization analysis includes an evaluation of market sizing, competitive benchmarking, pricing models, and go-to-market strategies. The modular platform has the potential to enable broader adoption of Raman-based analysis tools by reducing labor intensity and improving repeatability in sample positioning workflows. This work lays the foundation for the future integration of optical feedback and automated analysis, with the goal of transforming how Raman-based diagnostics are conducted at scale.S.M
SoK: Acoustic Side Channels
No full textAcoustic side channels (ASCs) have been discovered for several decades, highlighting the tangible security risks posed by unintended sound emissions from computing and electronic systems. Their existence has drawn considerable attention from researchers, driving rapid progress in both attack methodologies and defense mechanisms across a wide range of scenarios. In this paper, we provide a state-of-the-art analysis of ASCs, covering all the significant academic research in the area. First, we clarify existing ambiguities and conceptual confusion, proposing a clear definition of ASC. Second, we analyse the characteristics of known ASCs, discuss their security implications, and propose the first taxonomy. Next, we summarize attack techniques, discuss countermeasures, and identify areas for future research. We also link side channels and inverse problems, two fields that appear to be completely isolated from each other but have deep connections
Modeling the Sit-to-Stand Transition using Koopman Lifting Linearization and Human State Estimation
No full textThe Sit-to-Stand (STS) transition is one of the most dangerous daily activities for the elderly population, as it is one of the situations in which falls occur most often. Despite its risks, STS dynamics remain poorly understood, and current STS assistance devices fail to utilize knowledge of STS dynamics to effect their support. This thesis presents contributions to the dynamic modeling of STS and to human-robot collaboration for improving robotic assistance of STS. To coherently capture the multi-phase nature of STS, lifting linearization, a dynamic modeling methodology inspired by Koopman operator theory, to subsume segmented local dynamics in a globally linear dynamic model. A novel class of lifting linearization basis functions, termed “State-Membership Product (SMP)” observables, enables both the seamless blending of local dynamics into a global model, and the direct extraction of phase-specific behaviors from the global model. It is shown that an SMP-Koopman linear model tuned to published data of STS experiments is capable of reproducing the multi-phase STS dynamics with a single linear model. Building on this framework, STS is additionally modeled as a lifted linear feedback control system, composed of an SMP-Koopman-based open-loop biomechanical model of the human body and a linear quadratic regulator (LQR) which guides the body to stand up. The LQR controller, tuned to replicate STS motion, guides the human body model through the phases of STS without explicit phase-switches, improving system robustness. To enhance human-robot collaboration in STS assistance, a framework for estimating patient cooperativeness is also introduced, leveraging a simplified dynamic model and an Extended Kalman Filter. By analyzing a human’s initial response to applied physical and verbal cues, the estimation framework assesses willingness to engage in assisted STS. Together, these contributions advance both the modeling and estimation of STS, offering insights crucial for the development of safe, effective robotic assistance.Ph.D
Topology optimization of buildings-scale structures with material and fabrication constraints
No full textThe construction industry releases about 10% of anthropogenic Carbon Dioxide every year, primarily due to the manufacturing of construction materials. Structural optimization has been proposed as means of improving material efficiency in buildings, and thus reducing material demand for construction projects. Topology optimization has great potential for materially-efficient design because it is a free-form optimization method, allowing for performant geometries to be computationally derived with minimal input from the user. However, topology optimization algorithms must be modified to account for the specific fabrication and material constraints that are inherent in construction practices. This thesis shares a collection of research projects related to the use of topology optimization for large-scale structures relevant to the construction industry. First, a novel algorithm is proposed for large-scale 3D printed structures. The work focuses on the limitations presented by the printing nozzle, and the anisotropies that arise in 3D printed systems. Second, topology optimization is modified for design of structural glass. Several algorithms are developed, which are then used to design, fabricate, and test physical specimen to evaluate their real-world performance. Third, a framework is presented to design low-weight reinforced concrete structures. This system is used to design, build, and test reinforced concrete beams, so their performance can be compared to conventionally designed specimen. This thesis considers the diverse ways that topology optimization could be applied to design large-scale structures of various construction materials. The results demonstrate the types of computational techniques that can be used for generative design in the built environment.Ph.D
EI-Lite: Electrical Impedance Sensing for Micro-gesture Recognition and Pinch Force Estimation
No full textUIST ’25, Busan, Republic of KoreaMicro-gesture recognition and fine-grain pinch press enables intuitive and discreet control of devices, offering significant potential for enhancing human-computer interaction (HCI). In this paper, we present EI-Lite, a lightweight wrist-worn electrical impedance sensing device for micro-gesture recognition and continuous pinch force estimation. We elicit an optimal and simplified device architecture through an ablation study on electrode placement with 13 users, and implement the elicited designs through 3D printing. We capture data on 15 participants on (1) six common micro-gestures (plus idle state) and (2) index finger pinch forces, then develop machine learning models that interpret the impedance signals generated by these micro-gestures and pinch forces. Our system is capable of accurate recognition of micro-gesture events (96.33% accuracy), as well as continuously estimating the pinch force of the index finger in physical units (Newton), with the mean-squared-error (MSE) of 0.3071 (or mean-force-variance of 0.55 Newtons) over 15 participants. Finally, we demonstrate EI-Lite’s applicability via three applications in AR/VR, gaming, and assistive technologies
Analyzing Inconsistent Results of Table Transformer for Improved Data Extraction in Childhood Obesity Intervention Literature
No full textTables in scientific literature are rich sources of structured data, yet their complex and variable formats pose challenges for automated extraction. This thesis focuses on improving the reliability of Table Structure Recognition (TSR) using the Table Transformer (TATR) model, with a specific application to childhood obesity intervention studies. While fine-tuning TATR on a domain-specific dataset improves detection metrics, persistent errors such as overlapping rows and misclassified header columns remain. Through a systematic post-hoc error analysis of 175 scientific tables, we identify these dominant failure modes and develop lightweight post-processing modules: an overlap-aware row filtering algorithm and an OCR-enhanced column boundary correction method. Importantly, instead of relying on computationally expensive large language models (LLMs), this approach leverages efficient, interpretable techniques tailored to the domain-specific structure of public health tables. Our combined method reduces the proportion of structurally erroneous tables from 46.3% to an estimated 9.7–12.6%, improving the semantic alignment and interpretability of model outputs. This work contributes a transparent and scalable pipeline that enhances the trustworthiness of automated table extraction systems, with direct relevance to evidence-based decision-making in public health.S.M.S.M
The Objectiles Guide to Time Travel: Re-Envisioning Building Materials as Narrative-Collecting Object-Projectiles on a Trajectory Through Space-Time
No full textAs the architectural discipline grapples with its role in resource depletion, carbon emissions, and waste generation, there is a growing urgency to stop sourcing new materials and to reuse materials from existing buildings instead. One challenge to integrating reused materials into current building practices is technical: inventorying, deconstructing, reconditioning, and designing with reused materials is slower and more labor-intensive than with new ones. But another challenge is cultural: the materials that make up architecture are currently perceived as unmoving and single-use, with little consideration for their trajectories from raw resource to landfill. This thesis is focused on developing an aesthetic sensibility and design methodology that helps us re-envision materials as objects on a trajectory instead: Objectiles, or object-projectiles. Objectiles are objects on an adventure across space-time to collect as many uses as possible. Rather than remaining associated with one primary use, Objectiles are impressionable, bearing ambiguous traces of all the uses they encounter as they re-circulate. Through the aesthetic qualities that hint at their many uses, Objectiles invite us to time travel - to imagine the potential past and future narratives that may precede or follow their present physical state. Embedding the aesthetics of Objectiles into architecture can lead to the development of a new collective consciousness of the materials that surround us. They can make us aware that all the objects around us have trajectories that extend beyond their present state, and lead to an alternative material culture of greater care in how we use, re-circulate, and dispose of all objects.S.M