VictorJuiz/thesis huggingface dataset:
A scanning quantum cryogenic atom microscope at 6 Kelvin

The Scanning Quantum Cryogenic Atom Microscope (SQCRAMscope) is a quantum sensor capable of imaging electromagnetic fields emitted from a nearby sample. Here we streamline and improve the capabilities of the SQCRAMscope for studying quantum materials. We upgrade the cryogenics system by replacing the liquid cryostat with a closed-cycle system and adding a radiation shield. The minimum accessible sample temperature is thereby reduced to 5.7~K while maintaining suitably low sample vibrations. Sample loading and cold atom preparation are both additionally simplified. An improved sample mount allows more reliable and rapid exchange of samples, while simplified atom trapping requires less instrumentation without loss of trapping efficiency. One major application of the SQCRAMscope is imaging electric currents by measuring local variations in magnetic field. We discuss the theoretical grounding of this technique, as well as experimental preparation of samples for measurement. Data from iron-pnictide superconductors is used to demonstrate the technique

Keywords: Applied Physics.
Advisor: Lev Benjamin L. 
Kivelson Steven
Suzuki Yuri (Applied physicist)
Scattering in structured photonic media for classical and quantum light manipulation

Understanding and controlling the light scattering properties of nanophotonic structures is crucial for various applications. As a few examples, one can manipulate the color of nanoparticles, design invisibility cloaks, and create band gaps in periodic structures via suitable engineering of scattering properties. The light-scattering properties of an object depend on its own electromagnetic properties as well as on the dielectric properties of the environment it is placed in. In this thesis, we start with a detailed investigation of the scattering of classical or "coherent" light from a dielectric scatterer placed inside an otherwise uniform uniaxial hyperbolic medium. The dielectric object placed in a hyperbolic medium exhibits very different scattering properties as compared to its usual scattering behavior in an isotropic medium such as air. This points us to exciting opportunities for controlling scattering response by co-engineering both the scattering object and the environment it is placed in. Moving on, for the remainder of the thesis, we explore the scattering of single surface plasmon polariton (SPP) by atoms based on a proposed fully quantum mechanical model. SPPs are hybrid oscillations of electromagnetic fields and free electrons in metals and are known to significantly enhance light-matter interaction providing unique advantages. We first discuss the scattering of a single SPP by an atom and show a novel resonance arising from the strong interaction with small wavelength plasmons. Next, we present a proposal of electromagnetically induced transparency (EIT) like response realized using only two-level atoms. We also show the possibility of realizing mirrors and other optical devices using only hundreds of atoms. Finally, we discuss two-dimensional periodic atomic lattices interacting with a single SPP. Here, we propose various applications including slowing light to extremely small group velocities in atomic lattices, design of atomic lattice-based metamaterials, and design of a broad class of photonic Chern insulators

Keywords: Electrical Engineering.
Advisor: Fan Shanhui
Miller D. A. B.
Vuckovic Jelena
See, act, and conceptualize : a learning system for robots to interact with the world

Building intelligent systems for robots to interact with the world is a challenging problem due to many factors, such as the high dimensionality of the state and action space, the enormous variability of tasks, and the uncertainty of surrounding environments. This dissertation contains our work to guide robots to learn to perceive objects and motion, master various manipulation skills, and develop concepts to better interact with the world. Robots need to develop their visual systems to perceive objects and motion. When robots start to move and interact with surrounding environments, they thereby autonomously induce motion in the scene. Such motion creates a rich, visual sensory signal facilitating better scene understanding. We introduce our work that jointly estimates the segmentation of a scene into a finite number of rigidly moving objects, the motion trajectories of these objects, and the object scene flow. After robots perceive objects, they can move their hands to manipulate these objects. We present our approaches to train robots to master various primitive and complex manipulation skills. Choosing the right action representation is important to master primitive skills. We present a data-driven grasp synthesis method that considers both the object geometry and gripper attributes. Our method leverages contact points as an abstraction that can be re-used by a diverse set of robot hands. Besides contact points between objects and robotic hands, we propose a contact point matching representation between two objects and utilize it to train robots to learn how to hang arbitrary objects onto diverse supporting items such as racks or hooks. For complex skills such as tool manipulation and robotic assembly, we describe a learning framework that allows a robot to autonomously modify the environment and discover how to ease manipulation skill learning. As robots master more and more skills, it becomes important for robots to learn to abstract and represent these skills. We present our learning framework that endows robots with the ability to acquire various concepts to represent manipulation skills. These manipulation concepts act as mental representations of verbs in natural language instructions. We propose a learning from demonstration approach to learn manipulation actions from large-scale video data sets that are annotated with natural language instructions. Thus, we could use natural language instructions to guide robots to better interact with the world. We conclude by summarizing our efforts and discuss future directions

Advisor: Bohg Jeannette
Guibas Leonidas J.
Khatib Oussama
Seeking rights to a city of huacas : cultural heritage management and urban citizenship in Lima, Peru

In Peru, the pre-colonial past is central to the construction of national identity and visions of tourism-driven economic development. Yet few of the pre-colonial monuments (huacas) in Peru's capital of Lima have been conserved. My dissertation seeks to unravel this apparent puzzle, in which a nation of archaeological riches has neglected its own capital's pre-colonial heritage. Blending archaeological, ethnographic, historical, and archival research methods, I explore how the modern pursuit of urban citizenship is intimately interwoven with ongoing struggles to preserve Lima's remaining huacas. Over the 20th century, hundreds of thousands of rural migrants sought refuge in Lima's burgeoning periphery, forming self-constructed, informal settlements among hundreds of seemingly abandoned, pre-colonial "ruins." Amidst the entangled processes of destruction and creation that characterize migrant settlements on and near huacas, the state's refusal to recognize these displaced Peruvians as full citizens of Lima has made both life in the city periphery and huaca conservation increasingly precarious. Faced with two equally difficult alternatives—illegal settlement or remaining landless—informal settlers have come to be seen (and even see themselves) as opposed to huaca protection. Yet a growing number of heritage grassroots organizations (HGROs) and progressive state allies aim to reverse such alienation through citizen participation and social use initiatives. Seen through the lens of citizenship, my dissertation illustrates the political function of huacas and the discriminatory effects of Peru's object-oriented system for managing pre-colonial heritage. Specifically, my analysis reveals how both HGR members and marginalized residents embody a self-made approach to urban citizenship through their struggles for the right to the city and cultural rights as Peruvians. I argue that these long-neglected huacas thus play a vibrant role in contemporary contestation over political citizenship and social inclusion in a Latin American megacity

Keywords: Anthropology.
Advisor: Ebron Paulla A.
Meskell Lynn
Castillo Luis Jaime
Voss Barbara L.
Seismic Images Segmentation with Deep Learning

The task of seismic facies classification with machine learning has gained momentum and is currently receiving significant attention from researchers. The capabilities of modern neural networks encourage experiments dedicated to finding optimal ways of applying them to the seismic images segmentation task. It is, however, non-trivial to apply conventional machine learning techniques to seismic data. Obtaining labels when working with seismic data is very expensive; labeled data is scarce overall and knowledge generally is not transferrable from one dataset to another; representing a distribution of an entire dataset with labeled data of limited size is often challenging. Due to the seismic data volumes, inference time for machine learning algorithms can be a point of concern. These and some other aspects of applying machine learning to the seismic images segmentation task and seismic data in general are what we seek to address in this work. The topic is vast and requires a lot of time and resources to be tackled robustly. We, therefore, do not aim to provide solutions but rather highlight some key issues, give a possible direction for further investigations, and speculate on the results of experiments.

Keywords:  Department of Energy Resources Engineering
Image segmentation
Seismic interpretation
Reservoir characterization
Semi-supervised learning
Text
Thesis
Advisor: Mukerji Tapan
Self-programming networks : measuring and controlling networks from the edge

The Self-Programming Networks (SPNs) research project aims to build autonomous networks; i.e., networks which sense, monitor, program and control themselves. SPNs use an "edge-centric" architecture, where sensing and controlling are primarily conducted at the network's edge. Prior work on SPNs has yielded two key systems: (i) Huygens, a highly accurate and scalable algorithm for network clock synchronization, and (ii) SIMON, a system for fine-grained network telemetry using observations at the network's edge. These systems have been applied in distributed computing -- e.g., for building faster distributed databases and scalable state-machine replication, and networking -- e.g., for building "jitter-free networks" which underlie financial trading exchanges. In this dissertation, I present my contributions to SPNs. First, by building on SIMON, I present the methods of reconstructing more detailed network states, extending its deployability, and reducing its overhead in computation and storage. Second, I present a novel approach, called On-Ramp, for controlling congestion in SPNs. Akin to on-ramp meters at freeways, On-Ramp "holds" or "pauses" traffic at the network's edge if congestion on the traffic's path is high. Congestion is measured using accurately synchronized clocks at the sender and receiver. On-Ramp operates as a universal underlay: it augments, and greatly improves, the performance of any existing congestion-control protocol during periods of transient overload. It can be deployed by cloud users in their virtual machines (VMs) without any in-network support. I demonstrate the effectiveness of On-Ramp on Google Cloud, CloudLab, ns-3 simulations, and the production clusters in Facebook. Finally, I conclude the dissertation by describing another SPN-enabled application, ClockChain, which scales the transaction ordering service in permissioned distributed ledgers

Keywords: Electrical Engineering.
Advisor: Prabhakar Balaji
Alizadeh Mohammad (Professor)
Rosenblum Mendel
Sensorimotor control of lower-limb assistive devices

Human sensorimotor control is extremely complex. Because of this, it remains an open question how best to control lower-limb devices, such as exoskeletons and robotic prostheses, that seek to assist in human movement. A common approach is to attempt to replicate average biological joint torques, but this does not incorporate individualized differences in movement or the sensorimotor control loop that allows humans to adjust motor commands in response to sensory feedback. My dissertation comprises three different approaches to device control, with each subsequent approach providing greater incorporation of user input. First, I discuss a passive assistive device for running that is successful in reducing human metabolic cost due to gait adaptation to the device and the complex and interconnected biomechanics of running. Second, I present an approach for customizing the control parameters of robotic prostheses for individuals with lower-limb amputation. Finally, I present a system that closes the sensorimotor control loop of robotic prostheses, in which an individual with amputation teleoperates their own prosthetic ankle and receives sensory feedback regarding its behavior via a wearable wrist exoskeleton. This work contributes to the development of future lower-limb assistive devices not only through novel device control strategies but also through insights regarding human interaction with assistive devices

Keywords: Bioengineering.
Advisor: Delp Scott
Okamura Allison
Collins Steve (Steven Hartley)
Shining light on TrkA : an optobiological approach to dissecting location-specific TrkA signaling

Nerve growth factor (NGF) and its primary receptor, tropomyosin receptor kinase A (TrkA), play a crucial role in neuronal development, differentiation, and survival. Aberrant TrkA signaling has been implicated in chronic neuropathic and nociceptive pain disorders, neurodegenerative disorders, and cancers. It has been hypothesized that after endocytosis of the active receptor, TrkA continues to signal from the endosome. Although neurotrophin biology has been an active field of study for almost 70 years, questions around the identity of the signaling endosome and the impact of the location and duration of receptor activation have remained unanswered, due to the limitations of traditional cell biology methods. In this work, we have leveraged the light-induced protein-protein interaction system iLID to construct opto-TrkA, a version of this receptor that is activated by blue light rather than its endogenous ligand. This system permits rapid, reversible, location-specific activation of TrkA in cellular systems as well as model organisms. We have demonstrated that opto-TrkA is capable of reproducing key hallmarks of endogenous TrkA signaling in a cellular model. We offer the system for use in dissecting the contributions of TrkA at different subcellular compartments to the overall cell response. Further, we have begun to demonstrate the utility of opto-TrkA in model organisms. It is our hope that this system will be an invaluable tool in expanding our understanding of neurotrophin biology

Keywords: Chemistry.
Advisor: Cui Bianxiao
Cegelski Lynette
Lin Michael
Shock tube study of weakly ionized plasmas using laser absorption spectroscopy of excited state oxygen atoms

This work studies the collisional excitation kinetics of atomic oxygen diluted in argon at extreme temperatures (8,000 - 11,000 K) in a shock tube. Two lasers at 777 and 926 nm were scanned across the transitions of atomic oxygen at a rate of 25 kHz, providing the absorbance time histories within the 0.5-1 ms test time after the reflected shock passed. Four key quantities were measured in the current work to understand the collisional excitation kinetics, namely, the number density of the: fourth level of atomic oxygen; sixth level of atomic oxygen; electrons; and heavy-particle translational temperature. The number density of atomic oxygen and heavy-particle translational temperature were inferred from the integrated area and the Doppler linewidth of the measured oxygen absorbance. A preliminary two-temperature collisional-radiative model was developed to explain the multi-stage behavior of the measured oxygen number density time histories from 8,000 to 10,000 K. Reaction rate constants were fitted to match the measured excited-state atomic oxygen time histories. A sensitive, in-situ electron number density diagnostic method was developed by measuring the Stark shift of excited-state atomic oxygen. The measured electron number density was consistent with the preliminary model. The kinetics model was revised to match the measured time histories from 10,000 to 11,000 K.

Keywords: Mechanical Engineering.
Advisor: Hanson Ronald
Cappelli Mark A. (Mark Antony)
Hollberg Leo (Leo William)
The signal in the noise : developing tools to extract meaning from biological variation

Mammalian cells contain a multitude of dynamic structures, from those of force-generating cytoskeletal fibers to the networks of ATP-producing mitochondria. While the structure and dynamics of these systems have been made visible by advances in microscopy, the quantification of useful metrics from these images still requires careful and tailored analysis. Here, I present my work developing statistical tools and analysis pipelines in order to elucidate biological properties and mechanism in three studies: (1) the accurate measurement of cytoskeletal actin velocity distributions, (2) the characterization of mitochondria network topology, and (3) the development of quantitative tools to describe focal adhesion ultrastructure. Taken together, these studies illustrate both the rich biological data which can be extracted from microscopy experiments and the development of quantitative tools which may be useful in the characterization of other cellular structures and processes

Keywords: Chemical Engineering.
Advisor: Dunn Alexander
Boettiger Alistair
Sattely Elizabeth
Simulating earthquake-induced ductile crack propagation and brittle fracture in steel structures

Fracture represents a key limit state in evaluating the safety of steel structures subjected to earthquakes. Significant advancements have been recently made in the development of "local" fracture models, which are based on the underlying micromechanics which cause fracture, and predict fracture based on continuum stresses and strains. These models have proven successful at predicting fracture for both monotonic and cyclic loading conditions, under a wide variety of stress states. However, they do not model the physical processes of crack formation and crack growth, which alter the stresses and strains throughout the component as the crack propagates. Motivated by this, a framework was developed and implemented to simulate earthquake-induced ductile crack propagation within a continuum finite element setting. This framework, which combines a local model to predict fracture initiation and a cohesive zone model to simulate the physical process of crack growth, is capable of accurately simulating fracture initiation and subsequent propagation under both monotonic and cyclic loading conditions. Aspects unique to earthquake engineering, such as fracture due to ultra-low cycle fatigue and crack face closure under compressive loading, have been incorporated into the framework. An experimental testing program, consisting of 49 small-scale laboratory experiments, provided the scientific basis upon which the propagation framework was calibrated and validated. A methodology for calibrating the parameters of the various aspects of the framework, critical for widespread adoption, was developed. The propagation framework was proven to successfully simulate crack propagation under both monotonic and cyclic loading conditions in a wide variety of specimens

Advisor: Deierlein Gregory G. (Gregory Gerard)
Kanvinde Amit M.
Linder Christian (Engineering professor)
Simulations of particle laden turbulence in a radiation environment using heterogeneous high performance computing systems

The Predictive Science Academic Alliance Program (PSAAP) II at Stanford University investigated particle-laden turbulent flows in a radiation environment for concentrated solar power (CSP) applications. Over the course of the PSAAP project an extensive series of laboratory scale experiments and corresponding high fidelity simulations were designed and conducted for a conceptual volumetric solar energy receiver design. The configuration of interest involved the coupling of three distinct physical phenomena: fluid turbulence, particle dynamics, and the transport of thermal radiation. The work presented in this thesis is primarily focused on computational thermal radiation transport and multi-physics simulations of this conceptual solar energy receiver. The governing equations and numerical methods used to model the three major physical processes relevant to the PSAAP application (fluid, particles, and radiation) are presented. The couplings between the various processes are discussed due to their consequence on the data communication required by the computational solvers. The computational expense required to perform simulations of the PSAAP apparatus, due to the large range of length and time scales that needed to be resolved, required the use of high performance computing (HPC) systems. An overview of the multi-physics solver that was developed to simulate the physical processes relevant to the PSAAP application, Soleil-X, is given. Soleil-X used the Legion programming system, through the Regent programming language, in order to effectively use high performance computing systems with a variety of diverse architectures. A series of high fidelity radiative boundary conditions for the PSAAP multi-physics simulations were generated using specially developed emission models based on the radiation source used in the PSAAP experiments. The development, validation, and implementation of the custom emission models in the Monte Carlo Ray Tracing (MCRT) solver in Soleil-X are discussed. Then the full capability of Soleil-X is demonstrated with a multi-physics simulation of a particle laden open jet with co-flow that was radiatively heated with 10 [kW] of radiation

Keywords: Mechanical Engineering.
Advisor: Iaccarino Gianluca 
Aiken Alexander
Mani Ali (Professor of mechanical engineering)