Extension of Bilbro-McMillan Charge Density Wave-Superconductivity coexistence relation to quantum régimes: application to superconducting domes around quantum critical points

International audienceQuantum critical points (QCP) accompanied by superconductivity are ubiquitous in condensed matter physics. In general, the transition temperature T_O of an ordered state, e.g. antiferromagnetic, goes to zero under the influence of an external parameter, e.g. pressure. Superconductivity appears before the disappearance of the ordered state, but reaches its maximum when T_O=0. Presently, the implications of the QCP's on superconductivity are a subject of debate. It is propose here that both transition temperatures satisfy the relation 〖T ̃_O〗^2+〖T ̃_c〗^2=1, where the tilde indicates normalization to the maximum values. Inspired from the basic postulate of theories of superconductors, it is proposed as an extension from Bilbro-McMillan relation

The relationship between the normal state Fermi liquid scattering rate and the superconducting state

International audienceMany superconductors show a low temperature electrical resistivity of Fermi liquid type ρ =AT2. We show empirically that there exists a relationship between A and Tc when both vary under an external parameter, such as pressure. The more resistive the compound the higher the Tc. Through the analysis of Landau theory of FL, we find that it is a general feature of FL, due to the fact that the scattering that is the main cause of τ is the same one that bounds the pairs that condensed at Tc. We devise a method that allows the determination of the coupling constant λ, which is validated through application to 3He-'s superfluid transitions and τ's extracted from different properties. This method works for conventional superconductors, but fails with heavy fermions

Mean-Dispersion Preferences with a Specific Dispersion Function

A popular approach to modeling ambiguity aversion is to decompose preferences into the subjective expected utility of an act and an ambiguity index, or an adjustment factor, or a dispersion function. However, in these approaches the dispersion function (or ambiguity index, or adjustment factor) has very little structure imposed on it, leaving the selection of a specific dispersion function in applications to be rather arbitrary. In this note, working in the Anscombe- Aumann (1963) framework, we provide a simpler axiomatic characterization of mean-dispersion preferences which uniquely identifies the dispersion function from the infinite class of possible alternatives. Given the representation, we also obtain unique identification of subjective probabilities

A Capital Asset Pricing Model with Idiosyncratic Risk and the Sources of the Beta Anomaly

We introduce a generalization of the classical capital asset pricing model in which market uncertainty, market sentiment, and forms of idiosyncratic volatility and idiosyncratic skewness are priced in equilibrium. We derive two versions of the model, one based on a representative agent who cares about three criteria (risk, robustness, and expected returns), and the other with a microfoundation based on three types of investors (speculators, hedgers, and arbitrageurs). We apply the resulting capital asset pricing model with idiosyncratic risk (IR-CAPM) to provide a new theoretical account of the beta anomaly, one of the most fundamental and widely studied empirical limitations of the CAPM. We show that the IR-CAPM explains the main conditional relationships involving the beta anomaly in the literature including the time variation of the beta anomaly across optimistic and pessimistic periods and across high and low uncertainty periods, the relationship between the beta anomaly and the correlation between a stock\u27s beta and its idiosyncratic volatility, and the concentration of the beta anomaly among stocks with high idiosyncratic maximum returns

Condition-Measure Bounds on the Behavior of the Central Trajectory of a Semi-Definete Program

We present bounds on various quantities of interest regarding the central trajectory of a semi-definite program (SDP), where the bounds are functions of Renegar's condition number C(d) and other naturally-occurring quantities such as the dimensions n and m. The condition number C(d) is defined in terms of the data instance d = (A, b, C) for SDP; it is the inverse of a relative measure of the distance of the data instance to the set of ill-posed data instances, that is, data instances for which arbitrary perturbations would make the corresponding SDP either feasible or infeasible. We provide upper and lower bounds on the solutions along the central trajectory, and upper bounds on changes in solutions and objective function values along the central trajectory when the data instance is perturbed and/or when the path parameter defining the central trajectory is changed. Based on these bounds, we prove that the solutions along the central trajectory grow at most linearly and at a rate proportional to the inverse of the distance to ill-posedness, and grow at least linearly and at a rate proportional to the inverse of C(d)2 , as the trajectory approaches an optimal solution to the SDP. Furthermore, the change in solutions and in objective function values along the central trajectory is at most linear in the size of the changes in the data. All such bounds involve polynomial functions of C(d), the size of the data, the distance to ill-posedness of the data, and the dimensions n and m of the SDP

Strategic Planning and Project Selection for IT Portfolio Management

Software project proposals, solicited from various sources across an organization, could significantly vary in strategic value, overlap in functionality, and assume conflicting technical infrastructure. Without a holistic approach toward project selection and planning, the resulting project portfolio will likely incur undue risk while delivering poor return on investment. We propose a two-stage optimization procedure. In the first stage, project characteristics such as strategic alignment, perceived benefits, cost, and risk are considered to maximize portfolio value. In the second stage, inter-project dependencies and team expertise are used to determine how projects are assigned to programs and in what sequence they should be carried out. Future extension on the proposed optimization procedure is also discussed

Inscripciones de la Galicia altomedieval.

89 Jan.-Dez. 1979, p. 293-320

Aproximacion al estudio de las formas ornamentales en Galicia durante la epoca visigoda.

86 Jan.-Dez. 1976, p. 177-186

Effects of bioenergy on biodiversity arising from land-use change and crop type

Understanding how the world's flora and fauna will respond to bioenergy expansion is critical. This issue is particularly pronounced considering bioenergy's potential role as a driver of land‐use change, the variety of production crops being considered and currently used for biomass, and the diversity of ecosystems that can potentially supply land for bioenergy across the planet. We conducted 2 global meta‐analyses to determine how 8 of the most commonly used bioenergy crops may affect site‐level biodiversity. One search was directed at finding data on biodiversity in different production land uses and the other at extracting energy‐yield estimates of potential bioenergy crops. We used linear mixed‐effect models to test whether effects on biodiversity varied with different individual bioenergy crop species, estimated energy yield, first‐ or second‐generation crops, type of reference ecosystem considered, and magnitude of vertical change in habitat structure between any given crop and the reference ecosystem. Species diversity and abundance were generally lower in crops considered for bioenergy relative to the natural ecosystems they may replace. First‐generation crops, derived from oils, sugars, and starches, tended to have greater effects than second‐generation crops, derived from lignocellulose, woody crops, or residues. Crop yield had nonlinear effects on abundance and, to a lesser extent, overall biodiversity; biodiversity effects were driven by negative yield effects for birds but not other taxa. Our results emphasize that replacing natural ecosystems with bioenergy crops across the planet will largely be detrimental for biodiversity, with first generation and high‐yield crops having the strongest negative effects. We argue that meeting energy goals with bioenergy using existing marginal lands or biomass extraction within existing production landscapes may provide more biodiversity‐friendly alternatives than conversion of natural ecosystems for biofuel production.Fil: Nunez Regueiro, Mauricio Manuel. University of Florida. Department of Wildlife Ecology and Conservation; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Bio y Geociencias del NOA. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Museo de Ciencias Naturales. Instituto de Bio y Geociencias del NOA; Argentina. Universidad Católica de Salta; ArgentinaFil: Siddiqui, Sharmin F.. University of Florida. Department of Wildlife Ecology and Conservation; Estados UnidosFil: Fletcher, Robert J.. University of Florida. Department of Wildlife Ecology and Conservation; Estados Unido