Comment on "Spectroscopic Evidence for Multiple Order Parameter Components in the Heavy Fermion Superconductor CeCoIn5_5"

Recently, Rourke et al. reported point-contact spectroscopy results on the heavy-fermion superconductor CeCoIn$_5$ [1]. They obtained conductance spectra on the c-axis surfaces of CeCoIn$_5$ single crystals. Their major claims are two-fold: CeCoIn$_5$ has i) d-wave pairing symmetry and ii) two coexisting order parameter components. In this Comment, we show that these claims are not warranted by the data presented. [1] Rourke et al., Phys. Rev. Lett. 94, 107005 (2005).Comment: accepted for publication in Phys. Rev. Lett., final for

Light mixed sneutrinos as thermal dark matter

In supersymmetric models with Dirac neutrino masses, a left-right mixed sneutrino can be a viable dark matter candidate. We examine the MSSM+$\tilde\nu_R$ parameter space where this is the case with particular emphasis on light sneutrinos with masses below 10 GeV. We discuss implications for direct and indirect dark matter searches, including the relevant uncertainties, as well as consequences for collider phenomenology.Comment: 33 pages, 14 figures; one figure and references adde

Determination of the Joint Confidence Region of Optimal Operating Conditions in Robust Design by Bootstrap Technique

Robust design has been widely recognized as a leading method in reducing variability and improving quality. Most of the engineering statistics literature mainly focuses on finding "point estimates" of the optimum operating conditions for robust design. Various procedures for calculating point estimates of the optimum operating conditions are considered. Although this point estimation procedure is important for continuous quality improvement, the immediate question is "how accurate are these optimum operating conditions?" The answer for this is to consider interval estimation for a single variable or joint confidence regions for multiple variables. In this paper, with the help of the bootstrap technique, we develop procedures for obtaining joint "confidence regions" for the optimum operating conditions. Two different procedures using Bonferroni and multivariate normal approximation are introduced. The proposed methods are illustrated and substantiated using a numerical example.Comment: Two tables, Three figure

Point-contact spectroscopy in heavy-fermion superconductors

We develop a minimal model to calculate point-contact spectra between a metallic tip and a superconducting heavy-fermion system. We apply our tunneling model to the heavy fermion CeCoIn5, both in the normal and superconducting state. In point-contact and scanning tunneling spectroscopy many heavy-fermion materials, like CeCoIn5, exhibit an asymmetric differential conductance, dI/dV, combined with a strongly suppressed Andreev reflection signal in the superconducting state. We argue that both features may be explained in terms of a multichannel tunneling model in the presence of localized states near the interface. We find that it is not sufficient to tunnel into two itinerant bands of light and heavy electrons to explain the Fano line shape of the differential conductance. Localized states in the bulk or near the interface are an essential component for quantum interference to occur when an electron tunnels from the metallic tip of the point contact into the heavy-fermion system.Comment: 13 pages, 9 figures. Accepted for publication in Physical Review

Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression

This paper studies the connections among quantile regression, the asymmetric Laplace distribution, maximum likelihood and maximum entropy. We show that the maximum likelihood problem is equivalent to the solution of a maximum entropy problem where we impose moment constraints given by the joint consideration of the mean and median. Using the resulting score functions we propose an estimator based on the joint estimating equations. This approach delivers estimates for the slope parameters together with the associated “most probable” quantile. Similarly, this method can be seen as a penalized quantile regression estimator, where the penalty is given by deviations from the median regression. We derive the asymptotic properties of this estimator by showing consistency and asymptotic normality under certain regularity conditions. Finally, we illustrate the use of the estimator with a simple application to the U.S. wage data to evaluate the effect of training on wages