Generation of pulsed bipartite entanglement using four-wave mixing

Using four-wave mixing in a hot atomic vapor, we generate a pair of entangled twin beams in the microsecond pulsed regime near the D1 line of $^{85}$Rb, making it compatible with commonly used quantum memory techniques. The beams are generated in the bright and vacuum-squeezed regimes, requiring two separate methods of analysis, without and with local oscillators, respectively. We report a noise reduction of up to $3.8\pm 0.2$ dB below the standard quantum limit in the pulsed regime and a level of entanglement that violates an Einstein--Podolsky--Rosen inequality.Comment: 10 pages, 5 figures, accepted for publication in New Journal Of Physici

A Spatially Enhanced Data‐Driven Multimodel to Improve Semiseasonal Groundwater Forecasts in the High Plains Aquifer, USA

The aim of this paper is to improve semiseasonal forecast of groundwater availability in response to climate variables, surface water availability, groundwater level variations, and human water management using a two‐step data‐driven modeling approach. First, we implement an ensemble of artificial neural networks (ANNs) for the 300 wells across the High Plains aquifer (USA). The modeling framework includes a method to choose the most relevant input variables and time lags; an assessment of the effect of exogenous variables on the predictive capabilities of models; and the estimation of the forecast skill based on the Nash‐Sutcliffe efficiency (NSE) index, the normalized root mean square error, and the coefficient of determination (R2). Then, for the ANNs with low‐ accuracy, a MultiModel Combination (MuMoC) based on a hybrid of ANN and an instance‐based learning method is applied. MuMoC uses forecasts from neighboring wells to improve the accuracy of ANNs. An exhaustive‐search optimization algorithm is employed to select the best neighboring wells based on the cross correlation and predictive accuracy criteria. The results show high average ANN forecasting skills across the aquifer (average NSE \u3e 0.9). Spatially distributed metrics of performance showed also higher error in areas of strong interaction between hydrometeorological forcings, irrigation intensity, and the aquifer. In those areas, the integration of the spatial information into MuMoC leads to an improvement of the model accuracy (NSE increased by 0.12), with peaks higher than 0.3 when the optimization objectives for selecting the neighbors were maximized.t

First Report of Soybean (Glycine max) Disease Caused by Pseudomonas aeruginosa in Cuba

Soybean (Glycine max L.) has become one of the most widely consumed foods, however diseases caused by microorganisms can affect yields and seed quality. In March 2015, during routine survey in a soybean growing area in Pinar del Rio province, Cuba; disease symptoms were observed in some leaves. These included water-soaked necrotic spots with surrounded chlorotic halos, especially on the margins of the leaves. To identify the possible pathogens involved, leaves were disinfected with tap water, 70% ethanol and were rinsed with sterile distilled water. Small segments from diseased tissue were macerated in sterile 0.85% NaCl solution, decimal dilutions were performed and 20 µL aliquots were streaked onto King´s B medium (KB). After 24 hours of incubation at 28 oC, a fluorescent pseudomonad was isolated. Colonies were round, smooth and produced yellowish-green diffusible pigments on KB. Physiological and morphological characteristics were determined using standard microbiological techniques (Schaad et al., 200..

Imaging using quantum noise properties of light

We show that it is possible to estimate the shape of an object by measuring only the fluctuations of a probing field, allowing us to expose the object to a minimal light intensity. This scheme, based on noise measurements through homodyne detection, is useful in the regime where the number of photons is low enough that direct detection with a photodiode is difficult but high enough such that photon counting is not an option. We generate a few-photon state of multi-spatial-mode vacuum-squeezed twin beams using four-wave mixing and direct one of these twin fields through a binary intensity mask whose shape is to be imaged. Exploiting either the classical fluctuations in a single beam or quantum correlations between the twin beams, we demonstrate that under some conditions quantum correlations can provide an enhancement in sensitivity when estimating the shape of the object