Control of coherent backscattering by breaking optical reciprocity

Reciprocity is a universal principle that has a profound impact on many areas of physics. A fundamental phenomenon in condensed-matter physics, optical physics and acoustics, arising from reciprocity, is the constructive interference of quantum or classical waves which propagate along time-reversed paths in disordered media, leading to, for example, weak localization and metal-insulator transition. Previous studies have shown that such coherent effects are suppressed when reciprocity is broken. Here we show that by breaking reciprocity in a controlled manner, we can tune, rather than simply suppress, these phenomena. In particular, we manipulate coherent backscattering of light, also known as weak localization. By utilizing a non-reciprocal magneto-optical effect, we control the interference between time-reversed paths inside a multimode fiber with strong mode mixing, and realize a continuous transition from the well-known peak to a dip in the backscattered intensity. Our results may open new possibilities for coherent control of classical and quantum waves in complex systemsComment: Comments are welcom

A Competitive Education: How Charter Schools Include and Exclude

A Competitive Education examines how the charter school movement is one of both inclusion and exclusion, while also serving as a study in rhetorical theory. Written as a senior thesis in the discipline of Writing and Rhetoric, this paper includes an introduction and reflection analyzing the text of the document from a rhetorical perspective. The article, written in a journalistic style, is presented in two ways: first, as one long article, and then as two shorter articles. The content of the articles looks at the history, politics, and real world effects of the charter school movement in California and across the United States

Critical States Embedded in the Continuum

We introduce a class of critical states which are embedded in the continuum (CSC) of one-dimensional optical waveguide array with one non-Hermitian defect. These states are at the verge of being fractal and have real propagation constant. They emerge at a phase transition which is driven by the imaginary refractive index of the defect waveguide and it is accompanied by a mode segregation which reveals analogies with the Dicke super -radiance. Below this point the states are extended while above they evolve to exponentially localized modes. An addition of a background gain or loss can turn these localized states to bound states in the continuum.Comment: 4.5 pages, 3 figures, 1 page of supplementary material including one figur

The IBMAP approach for Markov networks structure learning

In this work we consider the problem of learning the structure of Markov networks from data. We present an approach for tackling this problem called IBMAP, together with an efficient instantiation of the approach: the IBMAP-HC algorithm, designed for avoiding important limitations of existing independence-based algorithms. These algorithms proceed by performing statistical independence tests on data, trusting completely the outcome of each test. In practice tests may be incorrect, resulting in potential cascading errors and the consequent reduction in the quality of the structures learned. IBMAP contemplates this uncertainty in the outcome of the tests through a probabilistic maximum-a-posteriori approach. The approach is instantiated in the IBMAP-HC algorithm, a structure selection strategy that performs a polynomial heuristic local search in the space of possible structures. We present an extensive empirical evaluation on synthetic and real data, showing that our algorithm outperforms significantly the current independence-based algorithms, in terms of data efficiency and quality of learned structures, with equivalent computational complexities. We also show the performance of IBMAP-HC in a real-world application of knowledge discovery: EDAs, which are evolutionary algorithms that use structure learning on each generation for modeling the distribution of populations. The experiments show that when IBMAP-HC is used to learn the structure, EDAs improve the convergence to the optimum

High temperature superconducting magnet control actuators for the NGST

for the United States government is permitted