Lossless State Detection of Single Neutral Atoms

We introduce lossless state detection of trapped neutral atoms based on cavity-enhanced fluorescence. In an experiment with a single 87-Rb atom, a hyperfine-state-detection fidelity of 99.4% is achieved in 85 microseconds. The quantum bit is interrogated many hundreds of times without loss of the atom while a result is obtained in every readout attempt. The fidelity proves robust against atomic frequency shifts induced by the trapping potential. Our scheme does not require strong coupling between the atom and cavity and can be generalized to other systems with an optically accessible quantum bit.Comment: 4 pages, 4 figure

Bounded Fatou and Julia components of meromorphic functions

We completely characterise the bounded sets that arise as components of the Fatou and Julia sets of meromorphic functions. On the one hand, we prove that a bounded domain is a Fatou component of some meromorphic function if and only if it is regular. On the other hand, we prove that a planar continuum is a Julia component of some meromorphic function if and only if it has empty interior. We do so by constructing meromorphic functions with wandering continua using approximation theory.Comment: 15 pages, 4 figures. V2: We have revised the introduction, and introduced two new sections: Section 2 discusses and compare topological properties of Fatou components, while Section 3 establishes that certain bounded regular domains cannot arise as eventually periodic Fatou components of meromorphic function

Computational optimization of synthetic water channels.

Membranes for liquid and gas separations and ion transport are critical to water purification, osmotic energy generation, fuel cells, batteries, supercapacitors, and catalysis. Often these membranes lack pore uniformity and robustness under operating conditions, which can lead to a decrease in performance. The lack of uniformity means that many pores are non-functional. Traditional membranes overcome these limitations by using thick membrane materials that impede transport and selectivity, which results in decreased performance and increased operating costs. For example, limitations in membrane performance demand high applied pressures to deionize water using reverse osmosis. In contrast, cellular membranes combine high flux and selective transport using membrane-bound protein channels operating at small pressure differences. Pore size and chemistry in the cellular channels is defined uniformly and with sub-nanometer precision through protein folding. The thickness of these cellular membranes is limited to that of the cellular membrane bilayer, about 4 nm thick, which enhances transport. Pores in the cellular membranes are robust under operating conditions in the body. Recent efforts to mimic cellular water channels for efficient water deionization produced a significant advance in membrane function. The novel biomimetic design achieved a 10-fold increase in membrane permeability to water flow compared to commercial membranes and still maintained high salt rejection. Despite this success, there is a lack of understanding about why this membrane performs so well. To address this lack of knowledge, we used highperformance computing to interrogate the structural and chemical environments experienced by water and electrolytes in the newly created biomimetic membranes. We also compared the solvation environments between the biomimetic membrane and cellular water channels. These results will help inform future efforts to optimize and tune the performance of synthetic biomimetic membranes for applications in water purification, energy, and catalysis

Norm-Referenced Effects of a Campus-Based Therapeutic Mentoring Program

The purpose of this study was to explore potential effects of a 12-week therapeutic mentoring program targeting social, emotional, and behavioral concerns in 52 children and adolescents between 11 and 17 years of age. Self-reported scores on a norm-referenced behavioral questionnaire were tracked across the span of a mentoring program, and then analyzed using multilevel modeling. Results showed that participant scores changed in a healthy direction across all domains measured (i.e., conduct, negative affect, cognitive/attention, and academic functioning). Predictors in the multilevel model included caregiver-reported sex assigned at birth, the semester that the intervention took place, and whether a participant had repeated the program. Findings lend further support to research-based mentoring programs as effective community interventions to address behavioral, emotional, social, and academic concerns in youth

A Framework For The Domain-Driven Utilization Of Manufacturing Sensor Data In Process Mining: An Action Design Approach

Manufacturers install and rely on a large number of sensors to operate and control their processes. However, the collected sensor data is rarely used to analyse and improve the higher-level, aggregated business processes. Process mining (PM) appears to be a promising solution, with the ability to automatically generate and analyse business process models based on data. However, the atomic events of sensor measurements need to be refined, aggregated, and enriched to properly represent a business process. In this paper, we propose a novel framework to make manufacturing sensor data analysable with PM. The framework allows manufacturers with batch and continuous processes (BCP) to systematically enrich their sensor data to use it for optimization purposes. Following the action design research, we demonstrate the applicability of the framework in a use case study using sensor data from a BCP beverage production

Nonlinear eigenvalue problem for optimal resonances in optical cavities

The paper is devoted to optimization of resonances in a 1-D open optical cavity. The cavity's structure is represented by its dielectric permittivity function e(s). It is assumed that e(s) takes values in the range 1 <= e_1 <= e(s) <= e_2. The problem is to design, for a given (real) frequency, a cavity having a resonance with the minimal possible decay rate. Restricting ourselves to resonances of a given frequency, we define cavities and resonant modes with locally extremal decay rate, and then study their properties. We show that such locally extremal cavities are 1-D photonic crystals consisting of alternating layers of two materials with extreme allowed dielectric permittivities e_1 and e_2. To find thicknesses of these layers, a nonlinear eigenvalue problem for locally extremal resonant modes is derived. It occurs that coordinates of interface planes between the layers can be expressed via arg-function of corresponding modes. As a result, the question of minimization of the decay rate is reduced to a four-dimensional problem of finding the zeroes of a function of two variables.Comment: 16 page

Detection statistics in the micromaser

We present a general method for the derivation of various statistical quantities describing the detection of a beam of atoms emerging from a micromaser. The user of non-normalized conditioned density operators and a linear master equation for the dynamics between detection events is discussed as are the counting statistics, sequence statistics, and waiting time statistics. In particular, we derive expressions for the mean number of successive detections of atoms in one of any two orthogonal states of the two-level atom. We also derive expressions for the mean waiting times between detections. We show that the mean waiting times between de- tections of atoms in like states are equivalent to the mean waiting times calculated from the uncorrelated steady state detection rates, though like atoms are indeed correlated. The mean waiting times between detections of atoms in unlike states exhibit correlations. We evaluate the expressions for various detector efficiencies using numerical integration, reporting re- sults for the standard micromaser arrangement in which the cavity is pumped by excited atoms and the excitation levels of the emerging atoms are measured. In addition, the atomic inversion and the Fano-Mandel function for the detection of de-excited atoms is calculated for compari- son to the recent experimental results of Weidinger et al. [1], which reports the first observation of trapping states.Comment: 26 pages, 11 figure

HUMMR, a hypoxia- and HIF-1α–inducible protein, alters mitochondrial distribution and transport

Mitochondrial transport is critical for maintenance of normal neuronal function. Here, we identify a novel mitochondria protein, hypoxia up-regulated mitochondrial movement regulator (HUMMR), which is expressed in neurons and is markedly induced by hypoxia-inducible factor 1 α (HIF-1α). Interestingly, HUMMR interacts with Miro-1 and Miro-2, mitochondrial proteins that are critical for mediating mitochondrial transport. Interestingly, knockdown of HUMMR or HIF-1 function in neurons exposed to hypoxia markedly reduces mitochondrial content in axons. Because mitochondrial transport and distribution are inextricably linked, the impact of reduced HUMMR function on the direction of mitochondrial transport was also explored. Loss of HUMMR function in hypoxia diminished the percentage of motile mitochondria moving in the anterograde direction and enhanced the percentage moving in the retrograde direction. Thus, HUMMR, a novel mitochondrial protein induced by HIF-1 and hypoxia, biases mitochondria transport in the anterograde direction. These findings have broad implications for maintenance of neuronal viability and function during physiological and pathological states