Flocculation and Transport of Mud in Rivers and Deltas

Mud (grains &lt; 62.5 μm) dominates the sediment load of rivers from continents to the ocean and contributes to building coastal land and sequestering organic carbon. However, predicting mud transport is challenging because flocculation causes mud grains to aggregate into larger, faster settling particles called flocs, which dynamically respond to local flow, water, and sediment properties. In this thesis, I examined the factors controlling mud flocculation in rivers and deltas and the effects of enhanced floc settling velocity on mud accretion in a river delta using fieldwork and data compilations from the river sediment literature. Flocs have the potential to dictate mud deposition rates and transport patterns by effectively enhancing mud settling velocity. First, I developed a semi-empirical model to predict floc diameter and settling velocity in rivers using a global river data compilation (Chapter 2). Results show that turbulence, sediment concentration and mineralogy, organic matter concentration, and water chemistry are the key flocculation factors in rivers. I conducted fieldwork in the Wax Lake Delta, Louisiana, a river delta in the Mississippi River Delta complex. Based on floc measurements at the Wax Lake Delta, I validated the semi-empirical model and showed that a complementary physics-based floc settling velocity model relies on the permeability and fractal structure of flocs (Chapter 3). To better link floc settling velocity and mud transport, I used the Wax Lake Delta field data to demonstrate that flocculated mud might behave as bed-material load rather than washload (Chapter 4). This result implies that mud concentration and flux might be readily predictable from bed-material entrainment theory using local bed and flow measurements. Connecting mud transport to delta island sedimentation and delta resilience, I analyzed discharge and sediment flux in the Wax Lake Delta to understand how sediment is delivered to and transported in islands (Chapter 5). Field data and backwater modeling results show that tall levees can block flow, but intricate feedbacks between flow depth, velocity, and water surface slope set discharge and sediment flux into the island once primary channels overflow into islands. Suspended mud settles fast enough relative to island flow depth and velocity to settle out within the island rather than bypass. As such, mud can accrete and build up the island over time as evidenced by mud-rich island deposits in Wax Lake Delta. Finally, combining Wax Lake Delta data and a river data compilation on suspended sediment grain size and mineralogy, I showed that most suspended sediment in rivers is flocculated silt (Chapter 6). This silt likely flocculates due to physical trapping mechanisms rather than typically considered interactions between clay minerals and salinity because clay minerals compose a minority of the silt. Overall, this thesis informs how flocculation affects mud transport in rivers and deltas, encompassing the mechanisms of mud flocculation, predictions of floc settling velocity and mud concentration, and the significance of mud flocculation in shaping depositional landscapes.</p

Beyond Symmetry: Normality-Based Analysis of Velocity Gradients in Turbulent Flows

Small-scale turbulence is a hallmark of countless natural and engineered flows. Its features are often described and modeled using the velocity gradient tensor (VGT), which is conventionally decomposed into the (symmetric) strain-rate tensor and the (antisymmetric) vorticity tensor. Although this symmetry-based decomposition has found use in areas such as vortex identification and closure modeling, it provides limited insight into local flow structure. A more refined description can be obtained by further distinguishing the normal and non-normal parts of the VGT. The resulting normality-based decomposition identifies contributions associated with normal straining (symmetric/normal), rigid rotation (antisymmetric/normal), and pure shearing (non-normal). We use this decomposition to identify flow features that are obscured by symmetry-based analyses yet have significant implications for efforts to understand and model turbulent flows. We first demonstrate that partitioning the strength of velocity gradients using our normality-based approach can distinguish between different regimes in various turbulent flows. In wall-bounded flows, the near-wall partitioning is dominated by shearing whereas the partitioning far from the wall collapses onto the partitioning associated with isotropic turbulence. In an unbounded vortex ring collision, our analysis distinguishes the initial vortex rings, which have a strong imprint from rigid rotation, from the decaying turbulent cloud produced by their collision, for which the partitioning is similar to that of isotropic turbulence. It also identifies enhanced shear–rotation correlations as a distinctive fingerprint of the elliptic instability during transition, which can be interpreted using relevant geometric features of local streamlines. By deriving algebraic expressions for the partitioning constituents in terms of the invariants of the VGT and an additional parameter, which represents the alignment of shear vorticity with the local rotation axis, we identify a key facet of our analysis that goes beyond previous analyses of the VGT. We then apply our normality-based framework to filtered velocity gradients in direct and large-eddy simulations of isotropic turbulence. Our analysis enables shear layers, which are associated with shear vorticity, to be distinguished from vortex cores, which are associated with rigid rotation, in a multiscale setting. It reveals that filtering mitigates the relative contribution of shear layers in the subinertial range of the energy cascade. Moreover, it identifies crucial (yet perhaps overlooked) contributions from shear layers to fundamental energy transfer mechanisms, including strain self-amplification, vortex stretching, and backscatter associated with strain–vorticity covariance. The dominant role of shear layers in the backscatter mechanism suggests that they contribute significantly to the bottleneck effect in the subinertial range of the cascade. Our analysis of large-eddy simulation data shows that they also amplify the artificial bottleneck effect produced by an eddy viscosity model in the inertial range. This reflects that the eddy viscosity model mimics an unfiltered direct numerical simulation at a lower Reynolds number. A mixed model can be used to mitigate the artificial bottleneck effect since it more accurately mimics a filtered direct numerical simulation.</p

The Enemy of my Enemy: How Disorder and Dissipation Can Be Your Friend in Quantum Systems

In many physical quantum systems, disorder and dissipation are a nuisance that must be actively countered or minimized, or something that the utility of the system must otherwise survive. In this thesis, we study how these typically harmful concepts can actually be helpful in the right circumstances. We first study disorder-induced localization in quantum systems---so-called \textit{many-body localization}, or MBL. MBL suppresses the spreading of information, an otherwise ubiquitous phenomenon, and thus can be leveraged to preserve information and realize new types of protected quantum order. We discuss a novel mathematical technique to measure a localization length in MBL systems and connect this length scale to the conventional picture of the MBL-thermal transition. In doing so, we are able to probe the probability distribution of the coupling between distant degrees of freedom near the transition, which contains valuable information about the nature of the MBL phase and the transition to thermalization. We then switch gears and study how to harness dissipation for autonomous quantum error correction of Gottesman-Kitaev Preskill (GKP) qubits in superconducting circuits. Typically, dissipation destroys quantum information via decoherence, but we show how, by appropriately constraining the dissipative dynamics, dissipation can actually \textit{prevent} decoherence and counteract the effects of noise. As a result, our proposed GKP qubit enjoys exponential robustness to extrinsic noise and imperfections in the circuit/protocol. We also demonstrate how to realize robust non-Clifford gates on our proposed qubit, granting our device universal, self-correcting single qubit logic. The experimental realization of such a setup, which we discuss in detail, would represent a major step forward for the field of quantum computation.</p

Percolation on Transitive Graphs

Percolation on a transitive graph is an idealized mathematical model for a homogeneous system undergoing a phase transition. We will investigate how the geometry of an infinite transitive graph determines whether percolation undergoes a phase transition, and if so, at what critical point. Building on these ideas, we will develop a new theory of percolation on finite transitive graphs. This theory unifies the percolation phase transition on infinite transitive graphs with the giant-cluster phase transition in the celebrated Erdős-Rényi model from combinatorics

Explications of a Changing Climate

Climate models encode our collective knowledge about the climate system and are among the best tools available for estimating past and future climate change. However, in response to greenhouse gas forcing, climate models exhibit a large intermodel spread in various aspects of the climate system, adding considerable uncertainty to future climate projections. This dissertation introduces a series of conceptual models and frameworks to understand the behavior of climate models under greenhouse gas forcing and, consequently, Earth's changing climate. A simple statistical model is used to explain and constrain the intermodel spread in Arctic sea ice projections across climate models. The probability of encountering seasonally ice-free conditions in the twenty-first century is also explored by systematically constraining components of the statistical model with observations. A conceptual framework is introduced to understand controls on the strength and structure of the Atlantic meridional overturning circulation (AMOC) in climate models. This framework is used to explain why climate models suggest the present-day and future AMOC strength are related. This framework, in conjunction with observations, implies modest twenty-first-century AMOC weakening. A simple energy budget framework is used to examine precipitation over a wide range of climates simulated by climate models. It is shown that in extremely hot climates, global-mean precipitation decreases despite increasing surface temperatures because of increased atmospheric shortwave absorption from water vapor, which limits energy available for surface evaporation. These results have large implications for understanding weathering rates in past climates as well as Earth's climate during the Hadean and Archaean eons. Finally, a framework is introduced to reconcile two different approaches for quantifying the effect of climate feedbacks on surface temperature change. The framework is used to examine the influence of clouds on Arctic amplification in a climate model and an energy balance model. This work introduces an important non-local mechanism for Arctic amplification and shows that constraining the mid-latitude cloud feedback will greatly reduce the intermodel spread in Arctic warming. This dissertation advances our understanding of various aspects of Earth's changing climate and provides a series of conceptual frameworks that can be used to further constrain the behaviour of climate models in response to external forcing.</p

The Neural Computation of Internal Affective States

The study of neural computation has long concentrated on our cognitive abilities, with extensive research dissecting the mechanisms of memory, decision-making, and navigation. In contrast, the realm of social innate behavior and emotion has often been treated as a simpler problem, overlooking the immense complexity and biological significance it entails. This thesis aims to bring neural computation into the domain of emotional or affective states, employing data-driven modeling methods that approximate neural activity as dynamical systems. The application of these methods has uncovered brain representations that encode key qualities of persistence and escalation associated with aggressive states, formalized as line attractors. These emergent features of neural circuits arise from the complex interplay of connectivity and network dynamics, challenging long-held notions of subcortical computation. This discovery led us to rigorously test various key properties of line attractor dynamics. Through closed-loop modeling and holographic neural activation, we demonstrate that the line attractor is intrinsic to the mammalian hypothalamus, providing some of the first causal evidence of this property for any continuous attractor. These experiments also suggest that functional connectivity within the hypothalamus underpins the stability of this attractor. Furthermore, using a new cell-type-specific gene-editing system, we show that the implementation of this line attractor depends on neuropeptides, indicating a non-canonical mechanism that contributes to the robustness of this innate attractor. Finally, we reveal that line attractors encode emotional states beyond aggression, including states of sexual receptivity in the female hypothalamus. Longitudinal recordings of neural data across the estrus cycle show that the line attractor disappears during non-estrus states, suggesting long-timescale modulation of attractor dynamics by hormones. Together, these studies present a new paradigm for understanding subcortical computation underlying internal states and suggest a canonical motif that the brain reuses to encode diverse internal affective states

Development and Characterization of a Table-Top Laser-Produced Plasma Source for In-Situ and Time-Resolved Soft X-Ray Absorption Spectroscopy

X-ray absorption spectroscopy (XAS) has emerged as an indispensable tool in the fields of carbon capture and conversion, providing element-specific insights into electronic structure, oxidation states, and chemical bonding. Of particular interest are soft X-rays (SXRs), which can probe the X-ray water window, enabling detailed studies of carbon, nitrogen, and transition metal L-edges in aqueous environments. Traditionally, access to this technique and this energy range has been limited to large- scale facilities like synchrotrons and XFELs, which can only serve a small population of users in a given year. Furthermore, more complex techniques such as time-resolved and in-situ XAS are practically inaccessible to the majority of users. This thesis explores the development of a table-top laser-produced plasma (LPP) source based on a gaseous target to extend the reach of XAS techniques into laboratory settings. Such sources offer significant advantages in accessibility, flexibility, and cost, while advances in X-ray optics and detection systems have further enhanced their utility. The research presented here focuses on the utilization of gaseous LPP sources for both in-situ and time-resolved XAS, pushing the boundaries of table-top soft X-ray absorption capabilities. Key achievements include exploration of the lower temporal limit of LPP sources for SXR emission, and the first demonstration of liquid-phase XAS measurements using a gaseous LPP source. Gas-phase measurements were also achieved using the system built in this work. Additionally, a novel UV-pump/SXR-probe technique was developed, enabling future time-resolved studies of charge transfer dynamics in transition metal oxides. These advances pave the way for detailed investigations of photodriven processes, interfaces, and catalytic mechanisms critical to carbon capture and conversion. By improving temporal resolution and expanding the scope of in-situ XAS techniques, this work addresses fundamental challenges in the field, bringing the power of synchrotron-like spectroscopy into everyday laboratories. Ultimately, the results presented here aim to democratize XAS, fostering a broader adoption of this technique in catalysis and materials research.</p

Error Quantification and Mitigation for Numerical Compact Binary Waveforms

Gravitational wave analysis requires waveform models to compare with observed signals from compact binaries. These models are based on and validated by numerical relativity waveforms---waveforms output from codes developed to numerically evolve the Einstein field equations. The efficacy of numerical waveforms for analysis is limited by error from both numerical and astrophysical sources. This thesis makes two contributions to the quantification and mitigation of this error. Chapter 2 describes a new algorithm for eccentricity reduction, the process of determining initial conditions for quasicircular binary orbits. This iterative procedure requires a measurement of eccentricity based on an early-inspiral trajectory. We find that the use of nonlinear fitting techniques such as variable projection leads to vastly improved consistency in eccentricity measurements. Finally, Chapter 3 presents an in-depth quantification of error in numerical binary neutron star waveforms from three vastly different numerical relativity codes. We find that overall these codes produce consistent binary neutron star evolutions, but that further accuracy improvements will be required for analysis of next-generation gravitational wave detector signals.</p

An "InCLOSE" View of the Circumgalactic Medium of z~2 Star-Forming Galaxies

This thesis focuses on using diffuse gas to investigate the galactic chemical evolution and circumgalactic medium of galaxies near the peak of cosmic star-formation rate density z ~ 2. There are many fundamental questions that remain unanswered about these processes due to the lack of large observational samples including what the typical yields of massive stars are, the interplay between diffuse circumgalactic and dense interstellar gas in terms of kinematic complexity, metal content, stellar mass, and star formation rate, and the evolution of circumgalactic gas over cosmic time. The common thread between each investigation is the use of QSO absorption line objects (QSO absorbers) to probe diffuse gas that otherwise would be unseen due to its diffusivity. The chemical evolution of galaxies requires accounting for all sources of nucleosynthesis. During the earliest stages of galactic chemical evolution, the metal yields from core-collapse supernovae (CCSNe) are very important but acquiring empirical constraints is difficult because they cannot be easily disentangled from objects that currently exist because they have been enriched by some fraction of CCSNe and late time nucleosynthetic processes e.g., Type Ia SN. To address this, I used the metal abundances of very-metal poor (VMP; [Fe/H] &lt;-2) Damped Lyman Alpha Absorbers (DLAs; QSO absorbers with high H I column density comparable to the interstellar medium, log(NHI/cm⁻² &gt; 20.3) to place empirical constraints on the yields of low-metallicity CCSNe. I found that this approach is comparable to, and sometimes superior to, using abundances from the atmospheres of metal poor stars because of the model-independent nature of measuring abundances from dense, cold gas provided by the DLA. It has been known in the literature that DLAs and other QSO absorbers have a variety of origins so I began an observational campaign to find galaxies associated with QSO absorbers that would allow detailed analysis of the circumgalactic medium (CGM) of z ~ 2 galaxies. This has historically been challenging at all z, but especially at z ~ 2 where, before this thesis, there were only nine galaxies with their inner CGM analyzed (within a projected distance of 100 kpc) and with characterized nebular emission and stellar population properties. To this end, I am leading a survey that builds on the Keck Baryonic Structure Survey (KBSS) that aims to find close-in galaxy-QSO pairs to directly connect the Inner CGM of QSO Line Of Sight Emitting (InCLOSE) galaxies with their ISM. KBSS-InCLOSE relies on new observations that I have conducted using the twin Keck telescopes on Mauna Kea in Hawaii. I use the new optical integral field unit (rest-FUV at z ~ 2.3) called KCWI to discover new "InCLOSE" galaxies; obtain follow Keck/MOSFIRE near infrared (NIR) spectroscopy to confirm their redshifts and infer nebular properties including star-formation rate; use ground- and space-based optical and NIR images to infer stellar mass and age; and finally use high-resolution optical spectra of the KBSS QSOs to perform detailed analysis of CGM gas seen as absorption in the QSO spectra. The novelty of KBSS-InCLOSE goes beyond its large size (55 galaxies currently); the NIR spectra and images allow for the direct determination of galaxy properties, including stellar mass, which are rarely included in similar high-z surveys. The first results from KBSS-InCLOSE showcased the tools and techniques required to remove the bright QSOs from the datacubes, images, and spectra to reveal new faint, close-in galaxy-QSO pairs. Particular focus was payed on the processing of the IFU data because it serves as the main driving instrument for the survey since it provides both images and spectra of each galaxy in the field. By analyzing their CGM absorption, I showed that a M=M*=10¹⁰ M☉ z=2.43 galaxy exhibited strong, multiphase, kinematically complex, and gravitationally unbound metals in its CGM. This has been seen before in previous studies and may suggest that a consensus picture of the CGM of z ~ 2.3, M* galaxies is emerging. In KBSS-InCLOSE II, I focused on the first low-mass galaxies examined in the sample. I showed that the galaxies were star-forming, at the same redshift, and had sizes and masses consistent with dwarf galaxies, and found preliminary insights into the low-mass CGM that would make it distinct from both the massive $z\sim2$ CGM and low-mass local CGM suggesting that there may be strong evolution of the CGM across both stellar mass and redshift. In Chapter \ref{chapter5_InCLOSEIII} I preview work that is yet to be completed, KBSS-InCLOSE III, where I examined the entire sample showing that the z ~ 2 CGM often shows strong of metal absorption, is likely clumpy, and multiphase, and that future IFU follow-up is necessary to find more galaxies, and NIR spectroscopic follow-up is necessary to secure redshifts to mitigate mismatches between galaxy's and absorbers. Altogether, this thesis has laid fundamental groundwork towards expanding our understanding of the galaxy-scale baryon cycle of z ~ 2 star-forming galaxies by building the largest z ~ 2 close-in galaxy-QSO pair observational dataset thus far. It provides the data required to perform the most detailed examination of the connection between galaxies and their CGM during the peak epoch for galaxy formation.</p

Variable-Stiffness and Shape-Morphing Structured Media

Advancements in additive manufacturing and material synthesis with highly controlled geometries have enabled the creation of structured media, engineered materials with patterned micro- and meso-scale geometries that impart unique mechanical properties. By fine-tuning these architectures, structured materials can achieve properties beyond those of their base materials. A subcategory, structured fabrics, consists of discrete granular particles rather than continuous fibers. Their mechanical behavior is governed by jamming, a transition driven by geometric constraints, allowing them to switch between flexible and rigid states. By leveraging the interactions of the building blocks, structured fabrics enable tunable stiffness, global shape change, and adaptive functionalities, making them ideal for wearable, deployable, and morphing structures. The first structured fabric study explores a topologically interlocking material (TIM) system with adjustable bending stiffness controlled by external pre-stress. The system consists of truncated tetrahedral particles connected by tensioned nylon wires, allowing stiffness to be tuned by varying wire tension. Experiments examine the effects of surface friction and interlocking angle on bending response, guided by Level Set Discrete Element Method (LS-DEM) simulations. The second design presents deployable 3D structures that fold without rigid mechanisms, offering compact storage and stable deployment. The design consists of computationally generated rigid tiles adhered to a pre-stretched elastic sheet, which transforms from a flat state and jams into a predetermined 3D shape when released. Although the designs exhibited unique mechanical properties, experimentally understanding their internal mechanics was challenging due to limited visibility of the concealed membrane upon jamming. To optimize future designs, simulations were conducted to analyze the effects of various pattern designs and folding on membrane behavior.</p