Entanglement Distribution in Quantum Metropolitan Optical Networks

The ability to generate entangled photon-pairs over a broad wavelength range opens the door to the simultaneous distribution of entanglement to multiple users of a network using a single source and wavelength-division multiplexing technologies. Here we show the design of a metropolitan optical network made of tree-type access networks where entangled photon-pairs are distributed to any pair of users, independently of their location. The resulting network improves the reach, number of users and capabilities of existing proposals. Moreover, it is made up of typical commercial components and uses the existing infrastructure, which allows for moderate deployment costs. Finally, we develop a channel plan and a network design that allow direct optical communications, quantum and classical, between any pair of users. Therefore, multiple quantum information technologies can make use of this network.

Entanglement distribution in optical networks

The ability to generate entangled photon pairs over a broad wavelength range opens the door to the simultaneous distribution of entanglement to multiple users in a network by using centralized sources and flexible wavelength-division multiplexing schemes. Here, we show the design of a metropolitan optical network consisting of tree-type access networks, whereby entangled photon pairs are distributed to any pair of users, independent of their location. The network is constructed employing commercial off-the-shelf components and uses the existing infrastructure, which allows for moderate deployment costs. We further develop a channel plan and a network-architecture design to provide a direct optical path between any pair of users; thus, allowing classical and one-way quantum communication, as well as entanglement distribution. This allows the simultaneous operation of multiple quantum information technologies. Finally, we present a more flexible backbone architecture that pushes away the load limitations of the original network design by extending its reach, number of users and capabilities.

Categorical Structures in Non-Commutative Measure Theory.

In this paper, we investigate effect algebras and base normed spaces from the categorical point of view. We prove that the category of effect algebras is complete and cocomplete as well as the category of base normed spaces is complete, and discuss the contravariant functor from the category of effect algebras to the category of base normed spaces.

Entanglement generation and routing in optical networks

New telecom wavelength sources of polarization entangled photon pairs allow the distribution of entanglement through metro-access networks using standard equipment. This is essential to ease the deployment of future applications that can profit from quantum entanglement, such as quantum cryptography.

Methodologies to measure and to manage the decarbonisation of road transport: the case of Spain

El sector del transporte por carretera es uno de los principales contribuyentes de consumo de combustible y emisiones de España. Por lo tanto, la evaluación de los impactos ambientales del tráfico rodado es esencial para los programas de mitigación del cambio climático y la eficiencia energética. Sin embargo, uno de los retos en la planificación del transporte y el diseño de políticas consiste en la aplicación de metodologías de evaluación de emisiones consistentes, el diseño de estrategias y la evaluación de su eficacia. Las metodologías existentes de evaluación de las emisiones del transporte por carretera, utilizan diferentes niveles de análisis y períodos. Sin embargo, estos análisis son puntuales y no existe una continuidad en el análisis de diferentes estrategias o políticas. Esta tesis doctoral proporciona conocimientos y herramientas para el análisis de las políticas destinadas a reducir las emisiones de tráfico, tomando España como caso de estudio. La investigación se estructura en dos partes: i) el desarrollo y aplicación de metodologías para el análisis de factores y políticas que contribuyen en la evolución de las emisiones GEI del transporte por carretera en España; desde una perspectiva nacional; y ii) el desarrollo y aplicación de un marco metodológico para estimar las emisiones del tráfico interurbano y de evaluar estrategias centradas en la operación del tráfico y en la infraestructura. En resumen, esta tesis demuestra la idoneidad de utilizar diferentes herramientas para analizar las emisiones de tráfico desde diferentes puntos de vista. Desde el diseño de políticas de mitigación y eficiencia energética a nivel nacional, a estrategias centradas en la operación del tráfico interurbano y la infraestructura. Road transport is one of the major contributors to fuel consumption and emissions in Spain. Consequently, assessing the environmental impacts of road traffic is essential for climate change mitigation and energy efficiency programs. However, one of the key challenges of policy makers and transport planners consists of implementing consistent assessment emissions methodologies, applying mitigation strategies, and knowing their effectiveness. Current state-of-the-art emissions assessment methodologies estimate emissions from different levels and periods, using different approaches. Nevertheless, these studies are timely and they usually take different methodologies for analysing different strategies or policies, regardless of the assessment as a whole. This doctoral thesis provides knowledge and methodologies for analysing policies designed to reduce road traffic emissions, using the case study of Spain. The research procedure consists of two main scopes: i) the development and application of methodologies for analysing key factors and policies driving the GHG emissions of road transport in Spain; from a national perspective; and ii) the development and application of a road traffic emissions model for assessing operational and infrastructure strategies of the interurban road network at segment level. In summary, this thesis demonstrates the appropriateness to use different tools to analyse road traffic emissions at different levels: from appropriate nationwide mitigation and energy efficiency policies, to strategies focused on the operation of interurban traffic and infrastructure.

A CO2-saving-based methodology to measure the impact of the SUMP in European Cities: Application to the City of Burgos

Urban mobility in Europe is always a responsibility of the municipalities which propose measures to reduce CO2 emissions in terms of mobility aimed at reducing individual private transport (car). The European Commission's Action Plan on Urban Mobility calls for an increase in the take-up of Sustainable Urban Mobility Plans in Europe. SUMPs aim to create a sustainable urban transport system. Europe has got some long term initiatives and has been using some evaluation procedures, many of them through European projects. Nevertheless, the weak point with the SUMPs in Spain, has been the lack of concern about the evaluation and the effectiveness of the measures implemented in a SUMP. For this reason, it is difficult to know exactly whether or not the SUMPs have positively influenced in the modal split of the cities, and its contribution to reduce CO2 levels. The case of the City of Burgos is a very illustrative example as it developed a CiViTAS project during the years 2005-2009, with a total investment of 6M?. The results have been considered as ?very successful? even at European level. The modal split has changed considerably for better, The cost-effectiveness ratio of the SUMP in the city can be measured with the CO2 ton saved, specifically 36 ? per CO2 ton saved, which is fully satisfactory and in line with calculations from other European researchers. Additionally, the authors propose a single formula to measure the effectiveness of the activities developed under the umbrella of a SUMP.

Designing new cereal cultivars as an adaptation measure using crop model ensembles

To date, crop models have been little used for characterising the types of cultivars suited to a changed climate, though simulations of altered management (e.g. sowing) are often reported. However, in neither case are model uncertainties evaluated at the same time.

Relevance of Higher Education. How to measure it? The case of masters of engineering in Peru

Existing evaluation models for higher education have, mainly, accreditation purposes, and evaluate the efficiency of training programs, that is to say, the degree of suitability between the educational results and the objectives of the program. However, it is not guaranteed that those objectives adequate to the needs and real interests of students and stakeholders, that is to say, they do not assess the relevance of the programs, a very important aspect in developing countries. From the review of experiences, this paper proposes a model for evaluating the relevance of engineering masters program, and applies it to the case of a master?s degree at the University of Piura, Peru. We conclude that the proposed model is applicable to other masters program, offers an objective way for determining is a training program keep being relevant, and identifies improvement opportunities

The optimal measure of allelic association

Allelic association between pairs of loci is derived in terms of the association probability ρ as a function of recombination θ, effective population size N, linear systematic pressure v, and time t, predicting both ρrt, the decrease of association from founders and ρct, the increase by genetic drift, with ρt = ρrt + ρct. These results conform to the Malecot equation, with time replaced by distance on the genetic map, or on the physical map if recombination in the region is uniform. Earlier evidence suggested that ρ is less sensitive to variations in marker allele frequencies than alternative metrics for which there is no probability theory. This robustness is confirmed for six alternatives in eight samples. In none of these 48 tests was the residual variance as small as for ρ. Overall, efficiency was less than 80% for all alternatives, and less than 30% for two of them. Efficiency of alternatives did not increase when information was estimated simultaneously. The swept radius within which substantial values of ρ are conserved lies between 385 and 893 kb, but deviation of parameters between measures is enormously significant. The large effort now being devoted to allelic association has little value unless the ρ metric with the strongest theoretical basis and least sensitivity to marker allele frequencies is used for mapping of marker association and localization of disease loci.

A complexity measure for selective matching of signals by the brain.

We have previously derived a theoretical measure of neural complexity (CN) in an attempt to characterize functional connectivity in the brain. CN measures the amount and heterogeneity of statistical correlations within a neural system in terms of the mutual information between subsets of its units. CN was initially used to characterize the functional connectivity of a neural system isolated from the environment. In the present paper, we introduce a related statistical measure, matching complexity (CM), which reflects the change in CN that occurs after a neural system receives signals from the environment. CM measures how well the ensemble of intrinsic correlations within a neural system fits the statistical structure of the sensory input. We show that CM is low when the intrinsic connectivity of a simulated cortical area is randomly organized. Conversely, CM is high when the intrinsic connectivity is modified so as to differentially amplify those intrinsic correlations that happen to be enhanced by sensory input. When the input is represented by an individual stimulus, a positive value of CM indicates that the limited mutual information between sensory sheets sampling the stimulus and the rest of the brain triggers a large increase in the mutual information between many functionally specialized subsets within the brain. In this way, a complex brain can deal with context and go "beyond the information given."

The deferred imitation task as a nonverbal measure of declarative memory.

We tested amnesic patients, patients with frontal lobe lesions, and control subjects with the deferred imitation task, a nonverbal test used to demonstrate memory abilities in human infants. On day 1, subjects were given sets of objects to obtain a baseline measure of their spontaneous performance of target actions. Then different event sequences were modeled with the object sets. On day 2, the objects were given to the subjects again, first without any instructions to imitate the sequences, and then with explicit instructions to imitate the actions exactly as they had been modeled. Control subjects and frontal lobe patients reproduced the events under both uninstructed and instructed conditions. In contrast, performance by the amnesic patients did not significantly differ from that of a second control group who had the same opportunities to handle the objects but were not shown the modeled actions. These findings suggest that deferred imitation is dependent on the brain structures essential for declarative memory that are damaged in amnesia, and they support the view that infants who imitate actions after long delays have an early capacity for long-term declarative memory.

Analytical method to measure bending deformations in prismatic optical films

The aim of this work is to provide an analytical method based on experimental measurements in order to obtain the prismatic film deformation for different curvatures of Hollow Cylindrical Prismatic Light Guides (CPLG). To conform cylindrical guides is necessary bend the film to guide the light, changes induced by curving the film give rise to deformation shifts. Light losses affected by deformation has been experimentally evaluated and numerically analyzed. The effect of deformation in prism angle is specially increased for CPLG of curvatures higher than 20 m-1. An experimental method for accurate transmittance measurements related to bending is presented.

A new modularity measure for Fuzzy Community detection problems based on overlap and grouping functions

One of the main challenges of fuzzy community detection problems is to be able to measure the quality of a fuzzy partition. In this paper, we present an alternative way of measuring the quality of a fuzzy community detection output based on n-dimensional grouping and overlap functions. Moreover, the proposed modularity measure generalizes the classical Girvan–Newman (GN) modularity for crisp community detection problems and also for crisp overlapping community detection problems. Therefore, it can be used to compare partitions of different nature (i.e. those composed of classical, overlapping and fuzzy communities). Particularly, as is usually done with the GN modularity, the proposed measure may be used to identify the optimal number of communities to be obtained by any network clustering algorithm in a given network. We illustrate this usage by adapting in this way a well-known algorithm for fuzzy community detection problems, extending it to also deal with overlapping community detection problems and produce a ranking of the overlapping nodes. Some computational experiments show the feasibility of the proposed approach to modularity measures through n-dimensional overlap and grouping functions.