Multiparticle Quantum Superposition and Stimulated Entanglement by Parity Selective Amplification of Entangled States

A multiparticle quantum superposition state has been generated by a novel phase-selective parametric amplifier of an entangled two-photon state. This realization is expected to open a new field of investigations on the persistence of the validity of the standard quantum theory for systems of increasing complexity, in a quasi decoherence-free environment. Because of its nonlocal structure the new system is expected to play a relevant role in the modern endeavor on quantum information and in the basic physics of entanglement.Comment: 13 pages and 3 figure

Bars from the Inside Out: An HST Study of their Dusty Circumnuclear Regions

The results of bar-driven mass inflow are directly observable in high-resolution HST observations of their circumnuclear regions. These observations reveal a wealth of structures dominated by dust lanes, often with a spiral-like morphology, and recent star formation. Recent work has shown that some of these structures are correlated with the presence or absence of a bar. I extend this work with an investigation of circumnuclear morphology as a function of bar strength for a sample of 48 galaxies with both measured bar strengths and ``structure maps'' computed from HST images. The structure maps for these galaxies, which have projected spatial resolutions of 2 - 15 pc, show that the fraction of galaxies with grand-design (GD) circumnuclear dust spirals increases significantly with bar strength, while tightly wound dust spirals are only present in the most axisymmetric galaxies. GD structure is only found at the centers of galaxies classified as SB(s) or SB(rs) and not SB(r). SB(s) galaxies on average have stronger bars than SB(r) galaxies. There is also a modest increase in the fraction of loosely wound dust spirals at later morphological types, which may reflect an increase in the fraction of galaxies with circumnuclear, gaseous disks. (abridged)Comment: 10 pages, 6 figures. To appear in "Penetrating Bars through Masks of Cosmic Dust: The Hubble Tuning Fork strikes a New Note" held June 7-12th, 2004 in Pilanesberg National Park, South Africa. Version with higher resolution figures is available at http://cfa-www.harvard.edu/~pmartini/professional/publications/safrica04.pd

An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization

Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results.Comment: mail: [email protected]

Input-Output Relations in Optical Cavities: a Simple Point of View

In this work we present a very simple approach to input-output relations in optical cavities, limiting ourselves to one- and two-photon states of the field. After field quantization, we derive the non-unitary transformation between {\em Inside} and {\em Outside} annihilation and creation operators. Then we express the most general two-photon state generated by {\em Inside} creation operators, through base states generated by {\em Outside} creation operators. After renormalization of coefficients of inside two-photon state, we calculate the outside photon-number probability distribution in a general case. Finally we treat with some detail the single mode and symmetrical cavity case.Comment: 34 pages, 5 figures jpg, LaTe

Progressive impairment of CaV1.1 function in the skeletal muscle of mice expressing a mutant type 1 Cu/Zn superoxide dismutase (G93A) linked to amyotrophic lateral sclerosis

Background: Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disorder that is typically fatal within 3–5 years of diagnosis. While motoneuron death is the defining characteristic of ALS, the events that underlie its pathology are not restricted to the nervous system. In this regard, ALS muscle atrophies and weakens significantly before presentation of neurological symptoms. Since the skeletal muscle L-type Ca2+ channel (CaV1.1) is a key regulator of both mass and force, we investigated whether CaV1.1 function is impaired in the muscle of two distinct mouse models carrying an ALS-linked mutation. Methods: We recorded L-type currents, charge movements, and myoplasmic Ca2+ transients from dissociated flexor digitorum brevis (FDB) fibers to assess CaV1.1 function in two mouse models expressing a type 1 Cu/Zn superoxide dismutase mutant (SOD1G93A). Results: In FDB fibers obtained from “symptomatic” global SOD1G93A mice, we observed a substantial reduction of SR Ca2+ release in response to depolarization relative to fibers harvested from age-matched control mice. L-type current and charge movement were both reduced by ~40 % in symptomatic SOD1G93A fibers when compared to control fibers. Ca2+ transients were not significantly reduced in similar experiments performed with FDB fibers obtained from “early-symptomatic” SOD1G93A mice, but L-type current and charge movement were decreased (~30 and ~20 %, respectively). Reductions in SR Ca2+ release (~35 %), L-type current (~20 %), and charge movement (~15 %) were also observed in fibers obtained from another model where SOD1G93A expression was restricted to skeletal muscle. Conclusions: We report reductions in EC coupling, L-type current density, and charge movement in FDB fibers obtained from symptomatic global SOD1G93A mice. Experiments performed with FDB fibers obtained from early-symptomatic SOD1G93A and skeletal muscle autonomous MLC/SOD1G93A mice support the idea that events occurring locally in the skeletal muscle contribute to the impairment of CaV1.1 function in ALS muscle independently of innervation status

Using object-based image analysis to detect laughing gull nests

Remote sensing has long been used to study wildlife; however, manual methods of detecting wildlife in aerial imagery are often time-consuming and prone to human error, and newer computer vision techniques have not yet been extensively applied to wildlife surveys. We used the object-based image analysis (OBIA) software eCognition to detect laughing gull (Leucophaeus atricilla) nests in Jamaica Bay as part of an ongoing monitoring effort at the John F. Kennedy International Airport. Our technique uses a combination of high resolution 4-band aerial imagery captured via manned aircraft with a multispectral UltraCam Falcon M2 camera, LiDAR point cloud data, and land cover data derived from a bathymetric LiDAR point cloud to classify and extract laughing gull nests. Our ruleset uses the site (topographic position of nest objects), tone (spectral characteristic of nest objects), shape, size, and association (nearby objects commonly found with the objects of interest that help identify them) elements of image interpretation, as well as NDVI and a sublevel object examination to classify and extract nests. The ruleset achieves a producer’s accuracy of 98% as well as a user’s accuracy of 65% and a kappa of 0.696, indicating that it extracts a majority of the nests in the imagery while reducing errors of commission to only 35% of the final results. The remaining errors of commission are difficult for the software to differentiate without also impacting the number of nests successfully extracted and are best addressed by a manual verification of output results as part of a semi-automated workflow in which the OBIA is used to complete the initial search of the imagery and the results are then systematically verified by the user to remove errors. This eliminates the need to manually search entire sets of imagery for nests, resulting in a much more efficient and less error prone methodology than previous unassisted image interpretation techniques. Because of the extensibility of OBIA software and the increasing availability of imagery due to small unmanned aircraft systems (sUAS), our methodology and its benefits have great potential for adaptation to other species surveyed using aerial imagery to enhance wildlife population monitoring