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Quantum Matter Synthesizer: Seeing and Arranging Atoms in an Optical Lattice
Get PDF Quantum simulation with ultracold atoms offers a powerful route to exploring complex quantum systems that are beyond the reach of classical computation. Two major experimental platforms have driven progress in this field: degenerate quantum gases in optical lattices, which enable the study of many-body dynamics governed by Hubbard-type Hamiltonians; and reconfigurable Rydberg atom arrays, which provide programmable geometries for quantum information processing. This thesis presents the development of a new experimental platform, the Quantum Matter Synthesizer (QMS), which integrates the strengths of both approaches by combining dynamic tweezer arrays with optical lattices. The envisioned QMS experiment contains three main steps. First, we stochastically load a thermal atomic gas into a two-dimensional optical lattice, and perform site-resolved imaging to determine the initial atom occupancy. Second, dynamic optical tweezers are applied to rearrange the atomic distribution into a desired target configuration. Third, after the rearrangement, we perform a second imaging to verify the resulting atom distribution, and subsequently cool the atoms to their motional ground states to enable coherent many-body dynamics. This thesis presents the design and characterization of the QMS, with emphasis on the two key capabilities: site-resolved imaging and integration of dynamic optical tweezers. We highlight the dual-objective microscope setup that demonstrates excellent mechanical stability. We detail the implementation of optical trapping using a triangular lattice in conjunction with a light sheet, and fluorescence imaging based on degenerate Raman sideband cooling. This configuration enables high-fidelity, diffraction-limited, site-resolved imaging of atoms in the lattice. We also describe the implementation of an innovative scheme for real-time control of optical tweezers using digital micromirror devices (DMD), operating at a binary pattern refresh rate of 2.88 kHz. We present the calibration procedure for addressing individual lattice sites with DMD-generated patterns, along with initial results demonstrating controlled atom transport using dynamically shifting tweezers. The future integration of ground-state cooling will allow rapid and flexible initialization of many-body quantum states, enhancing preparation and manipulation of strongly correlated atomic systems through independent control of single atoms. </p
Essays on Macroeconomic Development
Get PDFWhat are the key barriers to economic growth in developing countries? This dissertation examines this question through two in-depth case studies, each highlighting distinct frictions that constrain economic development. The first case study investigates how coordination frictions contribute to food loss in agricultural supply chains in Ghana. While food loss is often attributed to inadequate storage technologies, I find that farmers who struggle to find buyers experience significantly higher levels of food loss than those who do not. When searching for a buyer takes time, farmers store their harvests for extended periods, leading to increased losses. I then identify potential policy interventions to improve supply chain efficiency and reduce food loss. The second case study, co-authored with Robert Townsend, explores how financial frictions hinder economic growth in Thailand. Microfinance programs are frequently piloted at the village level, but must be expanded nationally to drive large-scale economic change. Our research examines how barriers to migration between villages mediate the effectiveness of microfinance when financial interventions are implemented at scale, providing insights into how to design more effective interventions
Cross-Species Mapping of Functional Connectivity Alterations and Therapeutic Responses in Hyper-Acute Ischemic Stroke
Get PDFSince the advent of magnetic resonance imaging (MRI) in the 1970s, the field of medical imaging has witnessed remarkable progress, allowing unprecedented examination of both structural and functional aspects of the human body. Among these developments, functional MRI (fMRI) has emerged as a powerful modality for probing neural activity and deciphering the intricate patterns of connectivity that underlie cognition, perception, and motor control. Resting-state functional MRI (rsfMRI), in particular, provides a non-invasive means of observing the brain’s intrinsic functional organization without the need for explicit behavioral tasks, making it especially valuable for investigating complex pathologies such as ischemic stroke, where network-level disruptions can critically influence patient prognosis. This thesis establishes and validates a rigorous cross-species functional connectivity mapping framework designed to enhance the translational relevance of preclinical stroke models for clinical neuroscience. Focusing on canine models of acute ischemic stroke, it leverages advanced MRI acquisition protocols, comprehensive preprocessing pipelines, and sophisticated computational methods—including manifold alignment algorithms, nonlinear registration techniques, and graph-theoretic analyses—to characterize stroke-induced alterations in large-scale brain networks. Critically, this research evaluates how novel hemodynamic and oxygenation-enhancing interventions, specifically NEH and Sanguinate, modulate these disrupted networks. By quantitatively assessing network reorganization and functional recovery patterns in canines treated with these agents, the framework identifies conserved features of connectivity that can be mapped onto human stroke data. Building on this cross-species alignment, the thesis employs predictive modeling strategies to infer potential therapeutic outcomes in human stroke patients. Machine learning tools are used to integrate animal-derived biomarkers, connectivity metrics, and inferred network topologies into predictive models that estimate patient-specific responses to analogous interventions. This approach capitalizes on the biophysical parallels between canine and human cerebrovascular systems, thereby reducing uncertainties associated with direct extrapolation and improving the reliability of translational insights. The outcomes of this research reinforce the notion that intrinsic network dynamics, captured via rsfMRI, offer crucial information about tissue viability, metabolic demands, and the capacity for functional reorganization following ischemic injury. Moreover, by methodically bridging the gap between preclinical and clinical domains, the thesis demonstrates how cross-species connectivity mapping can inform precision medicine approaches in stroke care. Taken together, these findings not only advance fundamental knowledge of stroke-induced network perturbations but also pave the way for more targeted, evidence-based clinical interventions and the refinement of therapeutic strategies aimed at improving patient outcomes in neurological rehabilitation
Pseudorepresentations Not Arising from Genuine Representations
Get PDFWe show that a pseudorepresentation of a (finite) group need not arise from a genuine representation, even if one is allowed to extend the ring . This shows that a theorem of the ``embedding problem'' for residually multiplicity free pseudorepresentations in Bellaiche and Chenevier's work can not be extended to the general setting. We focus particularly on the case where with a trivial residual pseudorepresentation. The main idea is to explicitly compute the pseudodeformation ring and the trace subring of the framed deformation ring, demonstrating that these rings are different even for finite groups
Statistical Estimation with Heterogenous Data Structures
Get PDFStatistical estimation in modern data science often encounters heterogeneous data structures, arise from diverse sources, irregular sampling patterns, or harbor latent subpopulations. In these cases, traditional methods that rely on strong regularity assumptions may struggle to provide reliable estimates. This dissertation addresses these challenges by developing robust statistical methodologies for heterogeneous data structures across three domains: ranking from pairwise comparisons, parameter estimation in item response theory, and shared subspace estimation in multi-matrix settings. Each problem is characterized by challenges such as non-uniform sampling, imbalanced data, or misaligned subspaces, necessitating novel theoretical and algorithmic advancements. In the first part, we study ranking from pairwise comparison with general or semi-random comparison graph. We propose a weighted maximum likelihood estimator that utilizes a semi-definite programming based reweighting to restore the spectral properties in the comparison graphs and achieves near-optimal sample complexity for top- ranking. In the second part, we design the random pairing MLE (RP-MLE) that addresses sparse and imbalanced item-response data. We derive minimax-optimal error bounds as well as asymptotic normality for this algorithm. In the third part, we give an analysis of the estimation of shared subspace in the presence of unique and misaligned component using Angle-based Joint and Individual Variation Explained (AJIVE), revealing its strengths in high signal-to-noise regimes and fundamental limitations in signal-to-noise settings. Integrating innovative algorithms and novel analytical tools, this work advances efficient, theoretically grounded solutions for statistical estimation with heterogeneity in ranking, item response theory, and multi-view learning
Topics Around Braid Groups and Spaces of Polynomials
Get PDFThis dissertation comprises three papers. In Chapter 1 we will introduce the basic setup, definitions, and notation common to these papers, including the braid group on strands, and the configuration spaces of unordered points in the complex plane. In Chapter 2 we consider the two related problems of classifying the homomorphisms between braid groups, and classifying the holomorphic maps . As a consequence of our work, we complete the classification of holomorphic maps for . In particular, the map that appears in Ferrari's solution to the quartic equation is characterized as the the unique holomorphic map, up to an appropriate equivalence relation, whose image is not contained in a single orbit of the affine group. The contents of this chapter are joint work with Jeroen Schillewaert, first published in Mathematische Annalen 391.3 (2025), pp. 4409--4440. In Chapter 3 we consider certain subgroups of , called level congruence subgroups, associated to the integral Burau representation . For we prove that is generated by and the normal closure of a single th power of a half twist. As a consequence, we find that is normally generated in by just three elements for , each of which admits a simple topological description. The results of this chapter are joint work with Ishan Banerjee. In Chapter 4 we work with a stratification of the configuration space , called the equicritical stratification, indexed by partitions of . The fundamental group of a stratum is called a stratified braid group . If is the number of parts in the partition, then there is a monodromy homomorphism which arises from a natural map . We prove that this monodromy homomorphism is not injective when . The results of this chapter are joint work with Nick Salter
Quasicrystalline string landscape
Get PDFIn this work, we investigate a largely unexplored nongeometric corner of the string landscape: the quasicrystalline orbifolds. These exist at special points of the Narain moduli, leading to frozen moduli and large quantum symmetries. Here, we complete the classification and construction of quasicrystalline Narain lattices and use this to explore supersymmetric compactifications in 4 ≤ ≤ 6 and with 4 ≤ ≤ 16 supercharges, leading to novel theories, including theories with large quantum symmetries at all points in the moduli space. We anticipate that these constructions will have many applications, and in subsequent work, we apply these techniques to construct new nonsupersymmetric tachyon-free models. Similarly, these constructions can lead to constructing exotic matter representations in the string landscape
Supplementary Data 3 associated with manuscript "Structural basis for regulation of CELSR1 by a compact module in its extracellular region" in Nature Communications. Contains Molecular dynamics coordinates and trajectories
No full textSupplementary Data 3 associated with manuscript "Structural basis for regulation of CELSR1 by a compact module in its extracellular region" in Nature Communications. Contains Molecular dynamics coordinates and trajectories
Beyond Supply and Demand: The Moral Economy of Price Formation in Slab City
Get PDFThis article investigates the unique economic practices of Slab City, California, an off-grid community that rejects mainstream US values. Despite operating within the broader US economic system, Slab City residents have developed alternative forms of exchange, using cigarettes and cannabis alongside US dollars. The article examines the symbolic meanings associated with these alternative currencies, arguing that their value derives from symbolic gestures of trust and solidarity, reflecting a rejection of surplus value extraction and an embrace of shared economic experience. The analysis dives into Slab City's moral economy, highlighting the community's reliance on collective action for resource provisioning, such as weekly rituals of free meals, communal water tanks, and group efforts in resource acquisition and distribution. Contrasting Slab City's internal economic practices with the exploitative practices of the investor–state nexus in surrounding towns, the article underscores the community's commitment to mutual aid and challenges to capitalist norms. Finally, the article highlights the fluidity of monetary forms and the potential for alternative currencies to emerge within specific social contexts
Where Does Homophily Come From?
Get PDFThis study evaluates the evolution of friendship networks amongst first year undergraduate students at the beginning of college. While homophily, or the tendency to associate with similar others, is a network trait that sociologists have extensively studied, less is known about how it arises. Current research focuses on homophily dynamics but fails to adequately address if it plays a direct role in match selection or whether it arises indirectly. I address this gap by employing a qualitative, semi-longitudinal approach to evaluate college student personal networks as they naturally form and evolve due to random happenstances and individual choices. Specifically, I ask how does homophily arise in personal networks, and how do these contexts affect subsequent patterns of interaction? Participants, recruited through a combination of random and snowball samples, were interviewed periodically over their first two quarters of college to determine who they are associating with, how they are associating with them, and where they are looking for friends. These answers were then compiled and analysed to evaluate trends in network evolution with respect to homophily, heterophily, and propinquity. The findings suggest that individuals engage in a dual filtering exercise to identify friends. First, they choose environments based on the desired level of baseline similarity and then filter the subset based on personal preferences. By considering how the concept of shared experiences varies between different spaces, I explain common patterns in collegiate personal network