Evaluation of the optical conductivity tensor in terms of contour integrations

For the case of finite life-time broadening the standard Kubo-formula for the optical conductivity tensor is rederived in terms of Green's functions by using contour integrations, whereby finite temperatures are accounted for by using the Fermi-Dirac distribution function. For zero life-time broadening, the present formalism is related to expressions well-known in the literature. Numerical aspects of how to calculate the corresponding contour integrals are also outlined.Comment: 8 pages, Latex + 2 figure (Encapsulated Postscript

Coseismic horizontal slip revealed by sheared clastic dikes in the Dead Sea Basin

Peer reviewedPostprin

A statistical approach to persistent homology

Assume that a finite set of points is randomly sampled from a subspace of a metric space. Recent advances in computational topology have provided several approaches to recovering the geometric and topological properties of the underlying space. In this paper we take a statistical approach to this problem. We assume that the data is randomly sampled from an unknown probability distribution. We define two filtered complexes with which we can calculate the persistent homology of a probability distribution. Using statistical estimators for samples from certain families of distributions, we show that we can recover the persistent homology of the underlying distribution.Comment: 30 pages, 2 figures, minor changes, to appear in Homology, Homotopy and Application

Network Lasso: Clustering and Optimization in Large Graphs

Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimization solvers do not scale well, and scalable solvers are often specialized to only work on a narrow class of problems. Therefore, there is a need for simple, scalable algorithms that can solve many common optimization problems. In this paper, we introduce the \emph{network lasso}, a generalization of the group lasso to a network setting that allows for simultaneous clustering and optimization on graphs. We develop an algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in a distributed and scalable manner, which allows for guaranteed global convergence even on large graphs. We also examine a non-convex extension of this approach. We then demonstrate that many types of problems can be expressed in our framework. We focus on three in particular - binary classification, predicting housing prices, and event detection in time series data - comparing the network lasso to baseline approaches and showing that it is both a fast and accurate method of solving large optimization problems

Cosmic-ray induced background intercomparison with actively shielded HPGe detectors at underground locations

The main background above 3\,MeV for in-beam nuclear astrophysics studies with $\gamma$-ray detectors is caused by cosmic-ray induced secondaries. The two commonly used suppression methods, active and passive shielding, against this kind of background were formerly considered only as alternatives in nuclear astrophysics experiments. In this work the study of the effects of active shielding against cosmic-ray induced events at a medium deep location is performed. Background spectra were recorded with two actively shielded HPGe detectors. The experiment was located at 148\,m below the surface of the Earth in the Reiche Zeche mine in Freiberg, Germany. The results are compared to data with the same detectors at the Earth's surface, and at depths of 45\,m and 1400\,m, respectively.Comment: Minor errors corrected; final versio

Magnetic fabrics as strain markers in folded soft-sediment layers

Acknowledgements This study was supported by the Israel Science Foundation (ISF grants 868/17) and a grant from the Israeli Government under Geological Survey of Israel DS project 40706. We thank Catalina Luneburg and Stephen Laubach for efficient editorial handling, together with Ruth Soto and Manish A. Mamtani for helpful reviews and constructive comments. RW was inspired by John Ramsay while participating in a fieldtrip to the Alps led by John in 2002. GIA would like to take this opportunity to acknowledge John Ramsay's support while a post-doc at ETH Zurich in the late 1980's. TL had the privilege of showing John Ramsay outcrops of slump horizons and seismites in the lacustrine sediments of the Dead Sea region during John's visit to Israel in 2008.Peer reviewedPostprin

Electrical transport properties of bulk Nic_{c}Fe1−c_{1-c} alloys and related spin-valve systems

Within the Kubo-Greenwood formalism we use the fully relativistic, spin-polarized, screened Korringa-Kohn-Rostoker method together with the coherent-potential approximation for layered systems to calculate the resistivity for the permalloy series Ni$_{c}$Fe$_{1-c}$. We are able to reproduce the variation of the resistivity across the entire series; notably the discontinuous behavior in the vicinity of the structural phase transition from bcc to fcc. The absolute values for the resistivity are within a factor of two of the experimental data. Also the giant magnetoresistance of a series of permalloy-based spin-valve structures is estimated; we are able to reproduce the trends and values observed on prototypical spin-valve structures.Comment: 6 pages, ReVTeX + 4 figures (Encapsulated Postscript), submitted to PR