Experimental investigation of a coherent quantum measurement of the degree of polarization of a single-mode light beam

Abstract

A novel method for the direct measurement of the degree of polarization is described. It is one of the first practical implementations of a coherent quantum measurement, the projection on the singlet state. Our first results demonstrate the successful operation of the method. However, because of the nonlinear crystals used at present, its application is limited to spectral widths larger than about 8 nm.     

Photon-counting OTDR for local birefringence and fault analysis in the metro environment

Optical time domain reflectometery (OTDR) is one of the most used measurement techniques in the characterization of optical fiber links. In this paper, we present a thorough investigation of an OTDR using a Peltier cooled photon-counting detector at 1.55 um. Due to its superior spatial resolution and the absence of classical dead-zones, it is well suited for detailed, high resolution analysis of problem zones. We give a detailed analysis of its performance, and also demonstrate that a polarization-sensitive photon-counting OTDR can be used to extract local birefringences too large to be measured with standard P-OTDRs.     

Diode-pumped passively mode-locked Nd3+-doped fluoridefiber laser emitting at 1.05 μm: novel results

The investigation of a novel seed source for Nd:glass or Nd:YLF regenerative amplifiers presented in an earlier work is extended. The new results demonstrate the versatility of the diode-pumped passively mode-locked Nd³⁺:ZBLAN fluoride fiber laser: pulses with durations from 9.2 ps to 320 fs, with center wavelengths in the range 1047-1060 nm, and with a maximum average output power of 4 mW could be generated. The amplitude noise was as low as 0.6% rms (150 Hz-100 kHz) and the longterm stability and reliability were impressive as well. Further, an evaluation of the capabilities of three different (analytical, semi-analytical, and numerical) models to predict the pulse durations is performed for laser setups used in our experiment     

Vitamin A stability in triple fortified extruded,artificial rice grains containing iron,zinc and vitamin A

Multi‐micronutrient‐fortified rice could be an effective and sustainable approach to combat micronutrient deficiencies. We produced hot‐extruded artificial rice grains fortified with 10 mg iron (as micronised ground ferric pyrophosphate), 5 mg zinc (as oxide, sulphate or carbonate) and 750 μg vitamin A/g [as retinyl palmitate (RP)] and measured RP stability. The rice was designed to be mixed 1:200 with natural rice. Mean RP losses were 5.3% during extrusion, 28.5% during storage and 9.8% during cooking. Storage losses after 18 weeks at 30 °C in plastic packages exposed to light were ca 40% with iron and zinc causing no further losses. In aluminium packages (no light), mean RP losses were ca 20%. Iron, but not zinc, increased RP degradation. Zinc sulphate increased the negative effect of iron. The relatively good stability of RP during hot extrusion can be explained by the closed surface and dense nature of the artificial grain protecting RP from oxidation.     

Nonlinear response of composite steel-concrete bridges

This paper is concerned with the overload behavior of a composite beam-slab type highway bridge consisting of steel stringers supporting a cast-in-place reinforced concrete slab. A nonlinear finite element analysis is used to determine the complete state of stress and deformation at any level of overload. A layered model together with an incremental iterative procedure is employed to determine the response of the bridge in the post-elastic range. The results of this analysis are compared with available experimental results for the case of a simply supported bridge. The bridge response under overloads is investigated, and the effects of some major design parameters are studied. Among these parameters are: beam size, torsional constant, slab thickness, Poisson's ratio, yield stress of steel girders and the ratio of transverse to longitudinal stiffness of the slab. The results obtained from this computer analysis compare favorably with experimental results in the elastic and the post-elastic range.     

An advanced system for the automatic classification of multitemporal SAR images

A novel system for the classification of multitemporal synthetic aperture radar (SAR) images is presented. It has been developed by integrating an analysis of the multitemporal SAR signal physics with a pattern recognition approach. The system is made up of a feature-extraction module and a neural-network classifier, as well as a set of standard preprocessing procedures. The feature-extraction module derives a set of features from a series of multitemporal SAR images. These features are based on the concepts of long-term coherence and backscattering temporal variability and have been defined according to an analysis of the multitemporal SAR signal behavior in the presence of different land-cover classes. The neural-network classifier (which is based on a radial basis function neural architecture) properly exploits the multitemporal features for producing accurate land-cover maps. Thanks to the effectiveness of the extracted features, the number of measures that can be provided as input to the classifier is significantly smaller than the number of available multitemporal images. This reduces the complexity of the neural architecture (and consequently increases the generalization capabilities of the classifier) and relaxes the requirements relating to the number of training patterns to be used for classifier learning. Experimental results (obtained on a multitemporal series of European Remote Sensing 1 satellite SAR images) confirm the effectiveness of the proposed system, which exhibits both high classification accuracy and good stability versus parameter settings. These results also point out that properly integrating a pattern recognition procedure (based on machine learning) with an accurate feature extraction phase (based on the SAR sensor physics understanding) represents an effective approach to SAR data analysis.     

Wheat cycle monitoring using radar data and a neural network trained by a model

This paper describes an algorithm aimed at monitoring the soil moisture and the growth cycle of wheat fields using radar data. The algorithm is based on neural networks trained by model simulations and multitemporal ground data measured on fields taken as a reference. The backscatter of wheat canopies is modeled by a discrete approach, based on the radiative transfer theory and including multiple scattering effects. European Remote Sensing satellite synthetic aperture radar signatures and detailed ground truth, collected over wheat fields at the Great Driffield (U.K.) site, are used to test the model and train the networks. Multitemporal, multifrequency data collected by the Radiometer-Scatterometer (RASAM) instrument at the Central Plain site are used to test the retrieval algorithm.     

Retrieval of vegetation parameters with SAR interferometry

The potential of SAR interferometric techniques for the retrieval of vegetation parameters was investigated using ERS-1 data over agricultural and forested test sites. In a first experiment an interferometrically derived forest map was generated. The classification was based on the interferometric correlation and the backscatter intensities. The result was geocoded, using the interferometrically derived height map generated from the same ERS SAR data pair, and validated with a conventional digital forest map. Forest mapping accuracies of around 90% and better were achieved. In a second experiment, multitemporal data over an agricultural site were used to investigate the potential of repeat-pass interferometry to monitor farming activity, crop development, and soil moisture variations. The interferometric correlation was used as an indicator of dense vegetation and geometric change. It was possible, for example, to identify harvesting by the high correlation of the post-harvest bare or stubble field. Decreasing interferometric correlation was observed as a consequence of crop growth