Controlling chaos in the quantum regime using adaptive measurements

The continuous monitoring of a quantum system strongly influences the emergence of chaotic dynamics near the transition from the quantum regime to the classical regime. Here we present a feedback control scheme that uses adaptive measurement techniques to control the degree of chaos in the driven-damped quantum Duffing oscillator. This control relies purely on the measurement backaction on the system, making it a uniquely quantum control, and is only possible due to the sensitivity of chaos to measurement. We quantify the effectiveness of our control by numerically computing the quantum Lyapunov exponent over a wide range of parameters. We demonstrate that adaptive measurement techniques can control the onset of chaos in the system, pushing the quantum-classical boundary further into the quantum regime

Numerical Model Sensitivity to Heterogeneous Satellite Derived Vegetation Roughness

The sensitivity of a mesoscale weather prediction model to a 1 km satellite-based vegetation roughness initialization is investigated for a domain within the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database, specific to the domain, that was previously derived using a physically based procedure and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and iii) a MODIS climatologic roughness database that like (i) is a function only of land cover type, but possesses domain specific mean values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations within a domain including Oklahoma, Eastern Arkansas, and Northwest Louisiana during a 4-day period within IHOP 2002. Sensitivity analysis compares the impact the three roughness initializations on time-series temperature, precipitation probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE). Overall, the results indicate that, for the current investigation, replacement of the standard look-up table values with the satellite-derived values statistically improves model performance for most observed variables. Such natural roughness heterogeneity enhances the surface wind speed, PBL height and TKE production up to 10 percent, with a lesser effect over grassland, and greater effect over mixed land cover domains

Important Characteristics In An MBA Program: The Perceptions Of Online MBA Students

This study examines characteristics important to online MBA students and alumni. The study looks at what characteristics are important in an online MBA Program and if the level of importance of these characteristics varies by demographic variables.  The study focuses on availability, program quality, program length, cost, and courses in the curriculum.  The results suggest that the importance of characteristics in a MBA program falls into three tiers.  The most important characteristic is availability.  The next tier of importance is quality, program length, and cost.  There is no significant difference in importance among these three characteristics, but they are all significantly lower in importance than availability.  The final characteristic is courses as this is rated significantly lower than the other characteristics in terms of importance.  The research also examined if there were differences in importance characteristics by gender, age, years’ work experience and income and found while the basic order rankings were very similar across the different demographic variables, there were a few differences among demographic groups.  Women rated as quality, length, and courses at a higher level of importance than men did.  Finally, those with more years work experience rated availability at a significantly higher level of importance than those with fewer years work experience

An Exploration of Systematic Errors in Transiting Planets and Their Host Stars

Transiting planet systems offer the best opportunity to measure the masses and radii of a large sample of planets and their host stars. However, relative photometry and radial velocity measurements alone only constrain the density of the host star. Thus, there is a one-parameter degeneracy in the mass and radius of the host star, and by extension the planet. Several theoretical, semi-empirical, and nearly empirical methods have been used to break this degeneracy and independently measure the mass and radius of the host star and planets(s). As we approach an era of few percent precisions on some of these properties, it is critical to assess whether these different methods are providing accuracies that are of the same order, or better than, the stated statistical precisions. We investigate the differences in the planet parameter estimates inferred when using the Torres empirical relations, YY isochrones, MIST isochrones, and a nearly-direct empirical measurement of the radius of the host star using its spectral energy distribution, effective temperature, and \textit{Gaia} parallax. We focus our analysis on modelling KELT-15b, a fairly typical hot Jupiter, using each of these methods. We globally model TESS photometry, optical-to-NIR flux densities of the host star, and \textit{Gaia} parallaxes, in conjunction with extant KELT ground-based follow-up photometric and radial velocity measurements. We find systematic differences in several of the inferred parameters of the KELT-15 system when using different methods, including a $\sim 6\%$ ($\sim 2\sigma$) difference in the inferred stellar and planetary radii between the MIST isochrones and SED fitting.Comment: 12 Figures, 20 Tables, Submitted to Ap