Essays on Sequential Sampling in Value-Based Choice

This dissertation comprises three chapters related to the fields of psychology, computational neuroscience, and experimental economics. Chapters 1 and 2 use experimental and computational methods to study the role of attention in simple, value-based choices. Chapter 3 examines risky choices from experience and tests some of the underlying assumptions of sequential sampling models. A growing body of research has shown that simple choices involve the construction and comparison of values at the time of decision. These processes are modulated by attention in a way that leaves decision makers susceptible to attentional biases. In Chapter 1, co-authored with Stephanie Dolbier and Antonio Rangel, we studied the role of peripheral visual information on the choice process and on attentional choice biases. We used an eye-tracking experiment in which participants (N = 50 adults) made binary choices between food items that were displayed in marked screen ``shelves'' in two conditions: (a) where both items were displayed, and (b) where items were displayed only when participants fixated within their shelves. We found that removing the nonfixated option approximately doubled the size of the attentional biases. The results show that peripheral visual information is crucial in facilitating good decisions and suggest that individuals might be influenceable by settings in which only one item is shown at a time, such as e-commerce. In Chapter 2, co-authored with Stephen Gonzalez and Antonio Rangel, we studied the role of attention in aversive risky choices where all outcomes were unpleasant. We used two eye-tracking experiments in which participants made binary choices between two lotteries in two conditions: (a) a gain condition where outcomes for lotteries were weakly positive, and (b) a loss condition where outcomes were weakly negative. Contrary to the predictions of the standard aDDM, we found that attentional choice biases in the loss condition were identical to those found in the gain condition, suggesting that attention nudges choices towards the attended option even in losses. To explain these results, we propose a variation of the Attentional Drift-Diffusion-Model (called the Hybrid aDDM) that incorporates (a) both a value-dependent and a value-independent effect of attention on the choice process and (b) reference-dependent value signals. We show that the observed attentional choice biases and other behavioral signatures in the loss condition can only be explained by the Hybrid aDDM with a reference-point rule that sets the reference-point at or below the minimum possible outcome in a given context. In Chapter 3, co-authored with Antonio Rangel, we establish that sequential sampling models apply to risky decisions from experience and test some of the underlying assumptions of these models. We ran an online study in which participants chose to Play or Skip a slot machine, based on a stream of samples drawn from its outcome distribution. We found evidence for leakage, collapsing decision boundaries, and a delay in sample integration. We also found evidence of non-linear sample weighting depending on when the sample occurred during the trial. As a bonus, we established a link between the fixed decision boundaries in a Drift-Diffusion-Model and a Modified Probit model, allowing for estimation of decision boundaries in cumulative sample space without the need to fit a computational model.</p

Atomically Thin Spatial Light Modulators with Excitonic Nanomaterials

Achieving active control of light at the ultimate thickness limit—a single atomic layer—offers unprecedented opportunities for next-generation optoelectronic devices. The quest for ultrathin spatial light modulators has long relied on integrating tunable materials with plasmonic or high-index nanoantennas that serve as small, but three-dimensional optical resonators. As structures for controlling light become increasingly complex and compact, the geometrical constraints of these three-dimensional resonators will ultimately limit their scalability and versatility. A new avenue for device miniaturization emerges when harnessing electrically tunable resonances that are intrinsic to atomically thin materials. This thesis explores how exciton resonances, specifically in two-dimensional (2D) van der Waals materials, can serve as the central building blocks for future spatial light modulators that are as thin as atoms. We start by characterizing the gate-tunable optical properties of a monolayer molybdenum diselenide (MoSe₂), a 2D transition metal dichalcogenide. By tuning the exciton resonances with voltage, we demonstrate over 200% modulation in the real and imaginary part of the complex refractive index. We attribute this large tunability to the interplay between radiative and nonradiative decay channels of the excitons. The index modulation gives rise to amplitude and phase modulation of the scattered light, which is then used to engineer an electrically tunable phase gradient across a single monolayer MoSe₂ flake to dynamically steer the reflected beam. Next, we present a theoretical analysis of the complex frequency response of a generalized excitonic heterostructure. We show how the spectral positions of the phase singularities, e.g. zeros and poles, can be dynamically controlled, their impacts on the real frequency phase response, and how they can be used in active metasurface design. Finally, we evaluate excitons in quantum dots as an alternative platform for room temperature optical modulators and show how they present different challenges in designing phase modulators. Overall, our work highlights the novel functionalities enabled by exciton resonances for advanced light manipulation, underscoring their potential for atomically thin light modulators.</p

High-Field Charge Transport and Fluctuation Phenomena in Semiconductors from First Principles

Charge transport and dynamics in semiconductors determine the limits of contemporary high-performance electronic devices. Previously, in order to understand the microscopic mechanisms underlying charge transport, and to efficiently find novel materials for new applications, computational methods were limited to using parameterized scattering rates and simplistic band structure models as inputs. However, with ab-initio methods, only the atomic identities and lattice vectors are needed as inputs. These methods have the capability of providing insights not possible with methods that rely on empirical data, and predicting properties for not-yet-synthesized materials. While ab-initio computation of low-field transport properties have become common in recent years, these methods have not been extensively applied to non-equilibrium phenomena. In addition, the ab-initio simulation of fluctuational properties (such as the diffusion coefficient or power spectral density of current fluctuations) is an area that has been minimally explored. In order to approach quantum-limited noise levels in devices, a better understanding of the mechanisms that govern electronic noise away from equilibrium is needed. Thus, motivated by this, the overarching goal of this work is to develop and use first-principles methods to gain insight into the scattering processes that govern high-field electronic transport and noise in well-known semiconductors, and to use the same approach to make predictions and identify promising device applications for novel materials. The warm electron tensor is a quantity that describes the quadratic change of conductivity with electric field, which provides a quantitative way to examine the heating of the electron gas. However, this has not been examined from first-principles previously. In this work, we report the warm electron tensor of n-Si computed over a large temperature range, and find that the most commonly used order of perturbation theory only captures the qualitative change of the warm electron tensor with angle. However, by including the next-to-leading order two-phonon scattering term in our approach, we find near-quantitative agreement. This finding indicates that two-phonon scattering has a non-negligible role to play in transport in nonpolar semiconductors. We continue our investigation of n-Si by examining the diffusion coefficient and its anisotropy by applying our Boltzmann transport framework to fluctuational variables. We find that the qualitative features of the anisotropy are correct, but its magnitude is greatly underestimated in comparison to experimental data, while the onset of the noise is overestimated. While this suggests an incorrect description of f-type scattering in our work, by computing the frequency dependence of the diffusion coefficient as well as the piezoresistivity (two observables sensitive to the balance of f- and g-type scattering), we find that the qualitative agreement of these two observables with experiment shows that such a discrepancy cannot be due to an incorrect description. Instead, we suggest that the experiment contains charge transport phenomena not accounted for by our electron-phonon scattering framework. Finally, we use the same approach to investigate the high-field transport and noise in the novel ultra-wide-bandgap semiconductor cubic boron nitride (c-BN). While c-BN is known for its excellent mechanical and thermal properties, its high predicted saturation velocity and breakdown field make it a promising candidate in high-power and high-frequency devices. However, very few experimental and theoretical studies have probed its transport properties. Here, we show that c-BN exhibits a negative differential resistance (NDR) region below 140 K, and show that the cause is due to an abrupt valley repopulation effect with applied electric field. We also show that the intervalley time in c-BN is extremely large, on the order of diamond, and that this large intervalley time causes a distinct noise peak, most prominent at low temperatures. We discuss how the NDR region and large intervalley time make c-BN a potential candidate for transferred-electron devices and Gunn oscillators, respectively.</p

Planning for an Uncertain Future: Tree-Based Methods for Real-Time Fault Estimation, Collision Avoidance, and Multi-Agent Reconfiguration

Autonomous spacecraft making independent high-level decisions present the promise of dramatically increased productivity in space for both exploration and economic activity. While autonomy has seen limited use in space to date owing to a lack of flight heritage, limited computational resources, and a traditionally risk adverse industry, the growing numbers of spacecraft and increasingly ambitious missions will soon render the current ground-intensive mode of space operation untenable. In this thesis, we develop two critical capabilities for an autonomous future in space. The first is proactive fault estimation, which seeks to rapidly and safely identify the root causes of onboard anomalies by planning sequences of test actions to gather information while probabilistically ensuring safety. The second is real-time reconfiguration to enable formations of spacecraft to respond quickly and effectively to changing environments or mission objectives. We achieve both goals using various forms of Monte-Carlo Tree Search planning. By formalizing each capability as sequential decision-making problems, and developing algorithms well suited to information gathering, we show that our algorithms provably converge to optimal solutions while maintaining the ability to run in real-time on robotic spacecraft simulators. We present several algorithmic innovations, including marginalized filtering, sampling-based chance constraint evaluation, and an array-based implementation of Monte-Carlo Tree Search. Through and numerical simulations and hardware experiments, we demonstrate that these modifications enable our algorithms to outperform existing tree search methods and achieve better scaling across system complexity, noise, and simulation depth.</p

Mechanisms of Pharmacological and Cellular Regulators of Mitophagy

Autophagy is a highly conserved cellular process that isolates and degrades damaged or unnecessary intracellular structures. Mitochondria, well known as metabolic centers, provide ATP and critical metabolites essential for life. Unchecked mitochondrial damage impairs metabolism, releases immunogenic mitochondrial DNA, and triggers apoptosis. Mitophagy, the selective removal of mitochondria via autophagy, is vital to preventing these harmful outcomes. The PINK1/Parkin pathway detects damaged mitochondria and targets them for mitophagy. Dysfunction in this pathway underlies certain subset Parkinson’s Disease (PD) cases. Efforts to understand the mechanistic basis of this pathway and its regulators provides a pathway to development of potentially disease modifying therapeutics for PD. In this thesis, I characterize the mechanism of action of a series of clinical stage mitophagy activating drugs. We find that these compounds reduce the threshold for which mitochondrial stress initiates mitophagy. However, contrary to reported literature, I demonstrate that these compounds do not directly activate PINK1 or Parkin. Rather, they act as weak mitochondrial toxins sensitizing cells to mitochondrial insult. I reveal that this phenomenon is characteristic of any weak mitochondrial toxin, revealing a potent pitfall for current drug discovery campaigns. Next, I detail a novel endogenous regulator of PINK1/Parkin mitophagy, the immune-related protein TNIP1. We show through a series of cell, biochemistry, and biophysical assays, that TNIP1 competes for autophagy machinery to slow down mitophagy. These data center TNIP1 as a important regulator of autophagic processes, and a unique negative regulator of mitophagy. Finally, I describe a biophysical analysis of the mitochondrial ion channel, VDAC2, critical in apoptosis and PINK1/Parkin pathways. Using a series of single-molecule approaches, I reveal how its structural plasticity regulates its interactions with protein partners. These finding provide a mechanistic basis for understanding its role in disparate cellular processes. I also explore the biological impact of KO of each VDAC isoform on mitochondrial and cell function. Unexpectedly, we find that the lowest expressed isoform, VDAC3, has an outsized impact on mitochondrial function

Soft Theorems from Spontaneous Symmetry Breaking

Spontaneous symmetry breaking occurs when the vacuum state is not preserved under (a subset of) symmetries in the theory. Instead, the symmetry is non-linearly realized by the associated massless degrees of freedom, the Nambu-Goldstone bosons. At the level of on-shell observables, the non-linearly realized symmetry is manifested as a universal structure of scattering amplitudes in the so-called soft limit, which means sending the momenta of a Nambu-Goldstone modes to zero. In this dissertation, we further explore the link between spontaneous symmetry breaking and infrared dynamics of massless scalars. First, we derive soft theorems for theories with spontaneously broken Poincaré symmetries, corresponding to effective field theories for condensed matter systems such as solids, fluids, superfluids, and framids. We also implement a bootstrap in which the enhanced vanishing of amplitudes in the soft limit is taken as an input, thus sculpting out a subclass of exceptional solid, fluid, and framid theories. Next, we consider spontaneous breaking of higher symmetries. We derive a new sub-leading double soft pion theorem in theories with a spontaneously-broken continuous 2-group global symmetry, which intertwines amplitudes with different numbers of pions and photons. We also provide a novel derivation of the leading soft photon theorem from the Ward identity of an emergent 1-form global symmetry in effective field theories where antiparticles are integrated out. Finally, we turn to universal features in low-energy dynamics of generic effective field theories. We extend the scalar geometric soft theorem by allowing the massless scalar to couple to other scalars, fermions, and gauge bosons. The soft theorem keeps its geometric form, but where the field-space geometry now involves the full field content of the theory. As a bonus, we also present novel double soft theorems with fermions, which mimic the geometric structure of the double soft theorem for scalars.</p

Domestication of Environmental Bacteria for Biosensing Applications

The field of synthetic biology has made impressive progress in the past 25 years, but is still lacking when it comes to our capability to predictably engineer organisms outside of a small group of lab model organisms. In this thesis, I present the efforts to domesticate two soil bacteria important in agriculture for biosensing. The first, Pseudomonas synxantha, a wheat-colonizing bacterium that helps fight off fungal disease, was engineered into a bioreporter for phosphorus limitation. We also made cell-free extract from this organism, to enable rapid characterization of genetic elements. For the second, Xenorhabdus griffiniae, we asked the question of whether this bacterium can sense the presence of its entomopathogenic nematode host Steinernema hermaphroditum. We learned that X. griffiniae is able to sense its host and we were able to build an early variant of a nematode reporter by first characterizing genetic elements in X. griffiniae

Exploring Cell Diversity in Complex Tissues through Spatial Genomics and Spatial Transcriptomics

The study of cellular diversity is a fundamental requirement for understanding how multicellular organisms function. During the development of multicellular organisms, cells differentiate into various cell types with different molecular compositions, exhibit different phenotypes, and show distinct morphologies. Each single cell occupies a specific spatial location within different tissues and organs and performs a unique function. A holistic understanding of cells requires the integration of multiple “omics” modalities, including genomics, epigenomics, transcriptomics, and proteomics. Current well-established single-cell sequencing methods have been used to build enormous single-cell transcriptomic atlases. While single-cell sequencing methods are now capable of multi-omic profiling, they all require cell dissociation, during which important spatial context information is lost. To study cellular diversity within its native spatial context, our lab has developed innovative spatial genomics and transcriptomics tools that enable multi-omics profiling at single-cell resolution while preserving intact tissue organization. This thesis presents two projects that leverage these tools to investigate cellular diversity in complex tissues across different biological scales, from subnuclear to tissue-level organization. In Chapter 2, we applied spatial multi-omics to the mouse cerebellum, achieving single-cell resolution profiling of 100,049 genomic loci, 17,856 nascent transcripts, 60 mature mRNAs, and 28 immunofluorescently labeled subnuclear structures. To achieve this, we developed innovative two-layer barcodes for DNA sequential fluorescence in situ hybridization (seqFISH). Combining cell-type information from nascent and mature transcriptomes, we captured the three-dimensional genomic architecture and its interactions with subnuclear compartments in a cell-type-specific manner. Our findings show that repressive chromatin compartments have greater cell-type specificity than active chromatin compartments in the mouse cerebellum. In Chapter 3, we integrated single-cell multiome sequencing, which profiles single-nucleus RNA and chromatin accessibility (ATAC) from the same cells, with seqFISH spatial transcriptomics. This approach was applied to the 17- to 18-week-old human fetal kidney, targeting 224 marker genes. By combining sequencing and spatial profiling data, we constructed a comprehensive developmental atlas of human kidney organogenesis, providing new insights into the tissue organization and gene expression patterns during kidney development

Measuring Neutrino Oscillations with NOvA and T2K

The discoveries of the twentieth century proved that neutrinos have mass and can change flavor. For the past few decades, a major focus of research has been the measurement of the physical parameters which govern this flavor oscillation. These measurements remain inconclusive on a few key questions, including the ordering of the neutrino masses and whether neutrinos violate CP symmetry. NOvA and T2K are two long-baseline accelerator neutrino experiments working in this space. By placing detectors in a beam of muon (anti-)neutrinos, these experiments interrogate neutrino oscillations by measuring muon (anti-)neutrino disappearance and electron (anti-)neutrino appearance. The complementarity of NOvA's and T2K's oscillation measurements motivated the experiments to pursue a joint oscillation analysis. After bracketing the potential impacts of correlations between the two experiments' systematic uncertainties and constructing a joint likelihood function, we share in this thesis the first results from the NOvA-T2K joint oscillation analysis. We report the world's most precise measurement of &#916;m232 to date: +2.429+0.039-0.035 (-2.477&#177;0.035) &#215; 10-3 eV2 assuming the normal (inverted) mass ordering, showing a slight preference for the inverted mass ordering. The maximally CP-violating value of &#948;CP=+&#960;/2 is excluded by 3&#963; credible intervals, and if we assume neutrinos are in the inverted mass ordering, we see evidence of CP violation at 3&#963;. Additionally, we present an effort to encapsulate neutrino cross-section models in a parametrization-agnostic way. We have created a suite of systematic parameters that are capable of mimicking the action of NOvA's cross-section model. This method could be used in a future joint data analysis between long-baseline neutrino experiments. We also introduce Voronoi histograms, an ancillary technique developed as part of this program. Voronoi histograms are a new way to efficiently bin high-dimensional data. This method preserves bin density in regions of interest, while tightly controlling the total number of bins used. The performance gains from using Voronoi binnings over standard rectangular binnings scale dramatically with the dimensionality of the data

Sums of Various Dilates

Given a finite subset A of an ambient abelian group and a dilate λ, how large must the sum of dilate A+λ∙A be in terms of A? In this thesis, we study this problem in various settings and generalizations, proving tight bounds in many cases. Our five main results are as follows. 1. In the setting of a d-dimensional subset A of ℝᵈ, we prove an exact lower bound on the size of the difference set A-A. 2. In the case when λ ∈ \in C is a transcendental number, we show that there is an absolute constant c&gt;0 such that |A+λ∙A|≥ exp(c√log|A|)|A| for any finite subset A of C. This is best possible up to the constant c. 3. In the algebraic case, given algebraic numbers λ1,...,λk, we prove tight lower bounds for the sum of dilates A+λ∙A+ ... λk∙A. As an important ingredient, we also prove a Freiman-type structure theorem for sets with small sums of dilates. 4. In the setting of sums of linear transformations, we prove tight bounds for the sum of two linear transformations and tight bounds for the sum of multiple pre-commuting linear transformations. 5. In the setting of groups of prime order, we prove near-optimal lower and upper bounds for the sum of dilate A+λ∙A for A of a given density and large λ.</p