Publications

We investigate the effects of non-zero spatial curvature on cosmic inflation in the light of cosmic microwave background (CMB) anisotropy measurements from the Planck 2018 legacy release and from the 2015 observing season of BICEP2 and the Keck Array. Even a small percentage of non-zero curvature today would significantly limit the total number of e-folds of the scale factor during inflation, rendering just-enough inflation scenarios with a kinetically dominated or fast-roll stage prior to slow-roll inflation more likely. Finite inflation leads to oscillations and a cutoff towards large scales in the primordial power spectrum and curvature pushes them into the CMB observable window. Using nested sampling, we carry out Bayesian parameter estimations and model comparisons taking into account constraints from reheating and horizon considerations. We confirm the preference of CMB data for closed universes with Bayesian odds of over 100:1 and with a posterior on the curvature density parameter of ΩK,0=−0.051±0.017 for a curvature extension of LCDM and ΩK,0=−0.031±0.014 for Starobinsky inflation. Model comparisons of various inflation models give similar results as for flat universes with the Starobinsky model outperforming most other models.

Single particle cryo-electron microscopy has become a critical tool in structural biology over the last decade, able to achieve atomic scale resolution in three dimensional models from hundreds of thousands of (noisy) two-dimensional projection views of particles frozen at unknown orientations. This is accomplished by using a suite of software tools to (i) identify particles in large micrographs, (ii) obtain low-resolution reconstructions, (iii) refine those low-resolution structures, and (iv) finally match the obtained electron scattering density to the constituent atoms that make up the macromolecule or macromolecular complex of interest. Here, we focus on the second stage of the reconstruction pipeline: obtaining a low resolution model from picked particle images. Our goal is to create an algorithm that is capable of ab initio reconstruction from small data sets (on the order of a few thousand selected particles). More precisely, we seek an algorithm that is robust, automatic, able to assess particle quality, and fast enough that it can potentially be used to assist in the assessment of the data being generated while the microscopy experiment is still underway.

With the advent of high-resolution, low-noise CMB measurements, the ability to extract cosmological information from thermal Sunyaev-Zel'dovich effect and kinetic Sunyaev-Zel'dovich effect will be limited not by statistical uncertainties but rather by systematic and theoretical uncertainties. The theoretical uncertainty is driven by the lack of knowledge about the electron pressure and density. Thus we explore the electron pressure and density distributions in the IllustrisTNG hydrodynamical simulations, and we demonstrate that the cluster properties exhibit a strong dependence on the halo concentration -- providing some of the first evidence of cluster assembly bias in the electron pressure and density. Further, our work shows evidence for a broken power-law mass dependence, with lower pressure in lower mass halos than previous work and a strong evolution with mass of the radial correlations in the electron density and pressure. Both of these effects highlight the differing impact of active galactic nuclei and supernova feedback on the gas in galaxy groups compared to massive clusters. We verified that we see qualitatively similar features in the SIMBA hydro-dynamical simulations, suggesting these effects could be generic features. Finally, we provide a parametric formula for the electron pressure and density profile as a function of dark matter halo mass, halo concentration, and redshift. These fitting formulae can reproduce the distribution of density and pressure of clusters and will be useful in extracting cosmological information from upcoming CMB surveys.

Numerous engineered and natural systems form through reinforcement and stabilization of a deformed configuration that was generated by a transient force. An important class of such structures arises during gametogenesis, when a dividing cell undergoes incomplete cytokinesis, giving rise to daughter cells that remain connected through a stabilized intercellular bridge (ICB). ICBs can form through arrest of the contractile cytokinetic furrow and its subsequent stabilization. Despite knowledge of the molecular components, the mechanics underlying robust ICB assembly and the interplay between ring contractility and stiffening are poorly understood. Here, we report joint experimental and theoretical work that explores the physics underlying robust ICB assembly. We develop a continuum mechanics model that reveals the minimal requirements for the formation of stable ICBs, and validate the model’s equilibrium predictions through a tabletop experimental analog. With insight into the equilibrium states, we turn to the dynamics: we demonstrate that contractility and stiffening are in dynamic competition and that the time intervals of their action must overlap to ensure assembly of ICBs of biologically observed proportions. Our results highlight a mechanism in which deformation and remodeling are tightly coordinated—one that is applicable to several mechanics-based applications and is a common theme in biological systems spanning several length scales.

We re-examine the model proposed by Alexander et al. (Phys. Fluids, vol. 18, 2006, 062103) for the closing of a circular hole in a molecularly thin incompressible Langmuir film situated on a Stokesian subfluid. For simplicity their model assumes that the surface phase is inviscid which leads to the result that the cavity area decreases at a constant rate determined by the ratio of edge tension to subfluid viscosity. We reformulate the problem, allowing for a regularising monolayer viscosity. The viscosity-dependent corrections to the hole dynamics are analysed and found to be non-trivial, even when the monolayer viscosity is small; these corrections may explain the departure of experimental data from the theoretical prediction when the hole radius becomes comparable to the Saffman–Delbrück length. Through fitting, under these relaxed assumptions, we find the edge tension could be as much as six times larger ( ∼
4.0 pN) than reported previously.

The primary focus of this thesis is on normative synaptic plasticity theories, which establish computational links between experimentally observed synaptic plasticity phenomena and the critical behavioral and developmental functions that they support. In Chapter 2, we will introduce and define this class of theory from the ground up. We will also critically review previous literature dedicated to developing and testing normative plasticity theories, and produce a set of guidelines that future modeling efforts should attempt to adhere to in order to facilitate the testing of these theories. In Chapter 3, we show how a reward-modulated normative plasticity rule can produce sensory representations that compensate for noise and are efficient, in that they selectively represent task-relevant information without wasting metabolic resources. In Chapter 4, we observe that our algorithm has many similarities to perceptual learning in the mouse auditory cortex: we adapt it to demonstrate how reward and context information delivered by acetylcholine signals from the nucleus basalis could underlie both context-specific adaptation in auditory cortex and reward-based perceptual learning in mice. In Chapter 5 we develop a theory called `impression learning', which proposes a mechanism for learning sensory representations by adapting synapses to minimize a prediction error between predictive signals arriving at apical dendrites of pyramidal neurons and incoming sensory information at basal dendrites. This theory generalizes the Wake-Sleep algorithm, and improves on previous prediction-error based theories of learning by demonstrating how learning can occur continuously with sensory perception, rather than requiring an offline learning phase. In Chapter 6, we close off the thesis with a theoretical examination of the difficulties associated with studying complex, adaptive systems experimentally. Our results across the chapters of this thesis collectively demonstrate the importance of normative theories of plasticity, both for conceptualizing learning in the brain and informing experiments that investigate adaptive neural circuits.

The optical properties of transition metal dichalcogenides have previously been modified at the nanoscale by using mechanical and electrical nanostructuring. However, a clear experimental picture relating the local electronic structure with emission properties in such structures has so far been lacking. Here, we use a combination of scanning tunneling microscopy (STM) and near-field photoluminescence (nano-PL) to probe the electronic and optical properties of single nano-bubbles in bilayer heterostructures of WSe2 on MoSe2. We show from tunneling spectroscopy that there are electronic states deeply localized in the gap at the edge of such bubbles, which are independent of the presence of chemical defects in the layers. We also show a significant change in the local bandgap on the bubble, with a continuous evolution to the edge of the bubble over a length scale of 20 nm. Nano-PL measurements observe a continuous redshift of the interlayer exciton on entering the bubble, in agreement with the band to band transitions measured by STM. We use self-consistent Schrödinger-Poisson (SP) simulations to capture the essence of the experimental results and find that strong doping in the bubble region is a key ingredient to achieving the observed localized states, together with mechanical strain.

First-principle calculations are employed to investigate the ultrafast isomerization of the acetylene cation and dication. We use the time-dependent density functional theory together with the Ehrenfest dynamics to track the coupled electron-nuclear dynamics. For both the acetylene cation and the dication, we observe nonadiabatic behaviors during the isomerization. We find that the charge transfer not only alters the electronic structure through nonadiabatic transitions, but also plays a key role in the subsequent hydrogen migration. We show that nonadiabatic transitions affect the structural modification of the excited potential energy surface, and also facilitate the ultrafast isomerization through the creation of a channel of increased negative charge that facilitates the proton movement. For the acetylene cation, we find a timescale for hydrogen isomerization of 66±4 fs, which is consistent with previous pump-probe experiments and on-the-fly calculations. For the dication, we find nonadiabatic transitions occur before the isomerization and identify a similar channel for the proton. Moreover, we find the formation of vinylidene-like structures is always accompanied by a characteristic charge separation on the carbon skeleton. These heuristics will be useful in identifying tautomers and motivating the ultrafast charge-transfer detection methods for future experiments.

A Fermi surface coupled to a scalar field can be described in a 1/N expansion by choosing the fermion-scalar Yukawa coupling to be random in the N-dimensional flavor space, but invariant under translations. We compute the conductivity of such a theory in two spatial dimensions for a critical scalar. We find a Drude contribution, and verify that the proposed 1/ω

Optical properties of semiconducting monolayer transition metal dichalcogenides have received a lot of attention in recent years, following the discovery of the valley selective optical population of either K