Atomic-level structure and deformation in metallic glasses

Metallic glasses (MGs) are a relatively new class of materials discovered in 1960 and lauded for its high strengths and superior elastic properties. Three major obstacles prevent their widespread use as engineering materials for nanotechnology and industry: 1) their lack of plasticity mechanisms for deformation beyond the elastic limit, 2) their disordered atomic structure, which prevents effective study of their structure-to-property relationships, and 3) their poor glass forming ability, which limits bulk metallic glasses to sizes on the order of centimeters. We focused on understanding the first two major challenges by observing the mechanical properties of nanoscale metallic glasses in order to gain insight into its atomic-level structure and deformation mechanisms. We found that anomalous stable plastic flow emerges in room-temperature MGs at the nanoscale in wires as little as ~100 nanometers wide regardless of fabrication route (ion-irradiated or not). To circumvent experimental challenges in characterizing the atomic-level structure, extensive molecular dynamics simulations were conducted using approximated (embedded atom method) potentials to probe the underlying processes that give rise to plasticity in nanowires. Simulated results showed that mechanisms of relaxation via the sample free surfaces contribute to tensile ductility in these nanowires. Continuing with characterizing nanoscale properties, we studied the fracture properties of nano-notched MGnanowires and the compressive response of MG nanolattices at cryogenic (~130 K) temperatures. We learned from these experiments that nanowires are sensitive to flaws when the (amorphous) microstructure does not contribute stress concentrations, and that nano-architected structures with MG nanoribbons are brittle at low temperatures except when elastic shell buckling mechanisms dominate at low ribbon thicknesses (~20 nm), which instead gives rise to fully recoverable nanostructures regardless of temperature. Finally, motivated by understanding structure-to-property relationships in MGs, we studied the disordered atomic structure using a combination of in-situ X-ray tomography and X-ray diffraction in a diamond anvil cell and molecular dynamics simulations. Synchrotron X-ray experiments showed the progression of the atomic-level structure (in momentum space) and macroscale volume under increasing hydrostatic pressures. Corresponding simulations provided information on the real space structure, and we found that the samples displayed fractal scaling (r^d ∝ V, d < 3) at short length scales (< ~8 Å), and exhibited a crossover to a homogeneous scaling (d = 3) at long length scales. We examined this underlying fractal structure of MGs with parallels to percolation clusters and discuss the implications of this structural analogy to MG properties and the glass transition phenomenon.

Testing inflationary cosmology with the BICEP1 and BICEP2 experiments

Recent observations of the temperature anisotropies of the cosmic microwave background (CMB) favor an inflationary paradigm in which the scale factor of the universe inflated by many orders of magnitude at some very early time. Such a scenario would produce the observed large-scale isotropy and homogeneity of the universe, as well as the scale-invariant perturbations responsible for the observed (10 parts per million) anisotropies in the CMB. An inflationary epoch is also theorized to produce a background of gravitational waves (or tensor perturbations), the effects of which can be observed in the polarization of the CMB. The E-mode (or parity even) polarization of the CMB, which is produced by scalar perturbations, has now been measured with high significance. Con- trastingly, today the B-mode (or parity odd) polarization, which is sourced by tensor perturbations, has yet to be observed. A detection of the B-mode polarization of the CMB would provide strong evidence for an inflationary epoch early in the universe’s history.

In this work, we explore experimental techniques and analysis methods used to probe the B- mode polarization of the CMB. These experimental techniques have been used to build the Bicep2 telescope, which was deployed to the South Pole in 2009. After three years of observations, Bicep2 has acquired one of the deepest observations of the degree-scale polarization of the CMB to date. Similarly, this work describes analysis methods developed for the Bicep1 three-year data analysis, which includes the full data set acquired by Bicep1. This analysis has produced the tightest constraint on the B-mode polarization of the CMB to date, corresponding to a tensor-to-scalar ratio estimate of r = 0.04±0.32, or a Bayesian 95% credible interval of r < 0.70. These analysis methods, in addition to producing this new constraint, are directly applicable to future analyses of Bicep2 data. Taken together, the experimental techniques and analysis methods described herein promise to open a new observational window into the inflationary epoch and the initial conditions of our universe.

Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.

Experimental and theoretical developments in extended x-ray absorption fine structure (EXAFS) spectroscopy

To obtain accurate information from a structural tool it is necessary to have an understanding of the physical principles which govern the interaction between the probe and the sample under investigation. In this thesis a detailed study of the physical basis for Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy is presented. A single scattering formalism of EXAFS is introduced which allows a rigorous treatment of the central atom potential. A final state interaction formalism of EXAFS is also discussed. Multiple scattering processes are shown to be significant for systems of certain geometries. The standard single scattering EXAFS analysis produces erroneous results if the data contain a large multiple scattering contribution. The effect of thermal vibrations on such multiple scattering paths is also discussed. From symmetry considerations it is shown that only certain normal modes contribute to the Debye-Waller factor for a particular scattering path. Furthermore, changes in the scattering angles induced by thermal vibrations produces additional EXAFS components called modification factors. These factors are shown to be small for most systems.

A study of the physical basis for the determination of structural information from EXAFS data is also presented. An objective method of determining the background absorption and the threshold energy is discussed and involves Gaussian functions. In addition, a scheme to determine the nature of the scattering atom in EXAFS experiments is introduced. This scheme is based on the fact that the phase intercept is a measure of the type of scattering atom. A method to determine bond distances is also discussed and does not require the use of model compounds or calculated phase shifts. The physical basis for this method is the absence of a linear term in the scattering phases. Therefore, it is possible to separate these phases from the linear term containing the distance information in the total phase.

Measurement of the Polarization of the Cosmic Microwave Background with the BICEP2 and Keck Array Telescopes

Precision polarimetry of the cosmic microwave background (CMB) has become a mainstay of observational cosmology. The ΛCDM model predicts a polarization of the CMB at the level of a few μK, with a characteristic E-mode pattern. On small angular scales, a B-mode pattern arises from the gravitational lensing of E-mode power by the large scale structure of the universe. Inflationary gravitational waves (IGW) may be a source of B-mode power on large angular scales, and their relative contribution to primordial fluctuations is parameterized by a tensor-to-scalar ratio r. BICEP2 and Keck Array are a pair of CMB polarimeters at the South Pole designed and built for optimal sensitivity to the primordial B-mode peak around multipole l ~ 100. The BICEP2/Keck Array program intends to achieve a sensitivity to r ≥ 0.02. Auxiliary science goals include the study of gravitational lensing of E-mode into B-mode signal at medium angular scales and a high precision survey of Galactic polarization. These goals require low noise and tight control of systematics. We describe the design and calibration of the instrument. We also describe the analysis of the first three years of science data. BICEP2 observes a significant B-mode signal at 150 GHz in excess of the level predicted by the lensed-ΛCDM model, and Keck Array confirms the excess signal at > 5σ. We combine the maps from the two experiments to produce 150 GHz Q and U maps which have a depth of 57 nK deg (3.4 μK arcmin) over an effective area of 400 deg² for an equivalent survey weight of 248000 μK². We also show preliminary Keck Array 95 GHz maps. A joint analysis with the Planck collaboration reveals that much of BICEP2/Keck Array's observed 150 GHz signal at low l is more likely a Galactic dust foreground than a measurement of r. Marginalizing over dust and r, lensing B-modes are detected at 7.0σ significance.