Use of variable lift control to optimize aerodynamic braking for a Mars entry vehicle

Variable lift control to obtain maximum velocity reduction through aerodynamic braking for Mars entr

Pauli blocking effects and Cooper triples in three-component Fermi gases

We investigate the effect of Pauli blocking on universal two- and three-body states in the medium. Their corresponding energies are extracted from the poles of two- and three-body in-medium scattering amplitudes. Compared to the vacuum, the binding of dimer and trimer states is reduced by the medium effects. In two-body scattering, the well-known physics of Cooper pairs is recovered. In the three-body sector, we find a new class of positive energy poles which can be interpreted as Cooper triples.Comment: 19 pages, 9 figures, discussion expanded, final versio

Some recent results in aerospace vehicle trajectory optimization techniques

Algorithms and computation techniques for solving trajectory optimization problem

Variable time optimal control

Computational algorithms and techniques for solving variable time optimal control problem

Generation of soil moisture patterns at the catchment scale by EOF interpolation

International audienceSpatial patterns of soil moisture cannot be adequately characterized by direct measurement for most practical applications, so interpolation between observations is required. Interpolation of soil moisture is complicated because multiple hydrologic processes can affect soil moisture and these processes can introduce distinct modes of variation into the soil moisture patterns. In this paper, a new method to interpolate soil moisture data is presented. This method accepts a dataset of soil moisture at widely-spaced locations on multiple dates and produces fine-scale patterns of soil moisture on the same dates. The method first uses Empirical Orthogonal Function (EOF) analysis to decompose the dataset into a set of time-invariant patterns of covariation (EOFs) and a set of associated time series (called expansion coefficients or ECs) that indicate the importance of the patterns on each date. The method then uses a statistical test to retain only the most important EOFs, and these EOFs are interpolated to the desired resolution using a standard estimation or interpolation method. The interpolated EOFs are finally combined with the spatial averages and the ECs to construct the fine-scale soil moisture patterns. Using the Tarrawarra dataset, the EOF-based interpolation method is shown to outperform analogous direct interpolation methods, and this improved performance is observed when as few as two observation dates are available. The improved performance occurs because EOF analysis decomposes soil moisture roughly according to the controlling processes and the most important EOFs exhibit distinct but more consistent spatial structures than soil moisture itself. Less predictable variation is also separated into higher order EOFs, which are discarded by the method

Plasmon excitation by charged particles interacting with metal surfaces

Recent experiments (R. A. Baragiola and C. A. Dukes, Phys. Rev. Lett. {\bf 76}, 2547 (1996)) with slow ions incident at grazing angle on metal surfaces have shown that bulk plasmons are excited under conditions where the ions do not penetrate the surface, contrary to the usual statement that probes exterior to an electron gas do not couple to the bulk plasmon. We here use the quantized hydrodynamic model of the bounded electron gas to derive an explicit expression for the probability of bulk plasmon excitation by external charged particles moving parallel to the surface. Our results indicate that for each ${\bf q}$ (the surface plasmon wave vector) there exists a continuum of bulk plasmon excitations, which we also observe within the semi-classical infinite-barrier (SCIB) model of the surface.Comment: 4 pages, 3 figures, o appear in Phys. Lett.

Dataset associated with "Temporal Variations of NDVI and LAI and Interactions with Hydroclimatic Variables in a Large and Agro-Ecologically Diverse Region"

It contains the dataset used to produce Figure 2 in the manuscript and to estimate relationships of hydroclimatic variables with vegetation indices. Each variable is a monthly regional average (for combined Sacramento and San Joaquin river basins, California) and spans from October 2002 to September 2015. These regional averages have been estimated using different datasets which are cited in the manuscript. Description of dataset is as follows: 1. Dataset 1: Regional averages of monthly hydroclimatic and vegetation anomalies 2. Dataset 2: Mean and standard deviations of monthly hydroclimatic and vegetation anomalies 3. Dataset 3: Prewhitened time series of monthly hydroclimatic and vegetation anomalies 4. Dataset 4: Prewhitened-detrended time series monthly hydroclimatic and vegetation anomalies 5. Dataset 5: Annual time series of regional hydroclimatic and vegetation anomalies See supplementary information provided with the manuscript for more information.Satellite based vegetation indices are increasingly used to characterize seasonal and interannual variations in vegetation as well as vegetation’s response to hydroclimatic variability. However, differences in the behavior of vegetation indices are not well understood over large spatial extents (e.g., 0.5° or larger). We hypothesize that normalized difference vegetation index (NDVI) and leaf area index (LAI) can exhibit different behaviors due to different relationships with hydroclimatic variables. To test this hypothesis, observations of monthly precipitation, discharge, temperature, vapor pressure deficit, evapotranspiration, and total water storage anomalies (TWSA) are processed for the combined Sacramento and San Joaquin river basins in California for 13 water years (October 2002-September 2015). Estimates of NDVI and LAI are obtained for the same period from MODerate resolution Imaging Spectroradiometer (MODIS). The seasonal cycle of NDVI peaks 2-3 months earlier than LAI. The seasonal variation in NDVI follows the seasonality of TWSA (i.e. water availability) whereas the seasonal cycle of LAI follows the seasonality in mean temperature and vapor pressure deficit (i.e. atmospheric water demand). Cross-correlation analyses of NDVI and LAI with the hydroclimatic variables show that LAI is more strongly correlated with most of the hydroclimatic variables considered.This work was supported by a grant provided by Bureau of Educational and Cultural Affairs, US Department of State under the umbrella of foreign Fulbright scholarship program