249 research outputs found
First principles calculations of band offsets at heterovalent -Ge/InAlAs interfaces
First principles electronic structure calculations are carried out to
investigate the band alignments of tensile strained (001) Ge interfaced with
(001) InAlAs. The sensitivities of band offsets to interfacial
structure, interfacial stoichiometry, and substrate stoichiometry, are
investigated. Large qualitative variations of the valence and conduction band
offsets are observed, including changes of the band offset type, indicating the
importance of local structural variations of the interface for band offsets in
real samples. Our results explain recent measurements of band offsets derived
from XPS core level spectra in terms of As atoms penetrating through the first
few monolayers of the Ge film. Analogous studies are carried out for the
diffusion of other species across the interface, and in general the band
offsets vary approximately linearly with diffusion depth relative to the values
for pristine "sharp" interfaces, where the sign of the linear variation depends
on the diffusing species. This large sensitivity of the band alignments to
interface details indicates potential routes to chemically control the band
offset of this group IV/III-V interface by tuning the stoichiometry of the
substrate surface that the thin film is grown on.Comment: 12 pages, 10 figure
Matching the BRIC equity premium: A structural approach
The equity risk premium (ERP) in BRIC markets is, on average, significantly higher than that in the US market. This paper employs an endowment economy with recursive preferences and long-run risk to explain the ERP generated by a portfolio of BRIC equity indices. The combination of recursive preferences and long-run risk partially explains the BRIC ERP. It turns out that there is a puzzle with respect to BRIC data as well. This holds even if we account for high levels of aversion to consumption and utility risk and for the empirically observed autoregressive structure of US consumption and BRIC dividend growth. (C) 2014 Elsevier B.V. All rights reserved
Structure Preserving Parallel Algorithms for Solving the Bethe-Salpeter Eigenvalue Problem
The Bethe-Salpeter eigenvalue problem is a dense structured eigenvalue
problem arising from discretized Bethe-Salpeter equation in the context of
computing exciton energies and states. A computational challenge is that at
least half of the eigenvalues and the associated eigenvectors are desired in
practice. We establish the equivalence between Bethe-Salpeter eigenvalue
problems and real Hamiltonian eigenvalue problems. Based on theoretical
analysis, structure preserving algorithms for a class of Bethe-Salpeter
eigenvalue problems are proposed. We also show that for this class of problems
all eigenvalues obtained from the Tamm-Dancoff approximation are overestimated.
In order to solve large scale problems of practical interest, we discuss
parallel implementations of our algorithms targeting distributed memory
systems. Several numerical examples are presented to demonstrate the efficiency
and accuracy of our algorithms
Supervised Learning in Multilayer Spiking Neural Networks
The current article introduces a supervised learning algorithm for multilayer
spiking neural networks. The algorithm presented here overcomes some
limitations of existing learning algorithms as it can be applied to neurons
firing multiple spikes and it can in principle be applied to any linearisable
neuron model. The algorithm is applied successfully to various benchmarks, such
as the XOR problem and the Iris data set, as well as complex classifications
problems. The simulations also show the flexibility of this supervised learning
algorithm which permits different encodings of the spike timing patterns,
including precise spike trains encoding.Comment: 38 pages, 4 figure
No evidence for a shift in pyruvate kinase PKM1 to PKM2 expression during tumorigenesis
The Warburg effect describes the circumstance that tumor cells preferentially use glycolysis rather than oxidative phosphorylation for energy production. It has been reported that this metabolic reconfiguration originates from a switch in the expression of alternative splice forms (PKM1 and PKM2) of the glycolytic enzyme pyruvate kinase (PK), which is also important for malignant transformation. However, analytical evidence for this assumption was still lacking. Using mass spectrometry, we performed an absolute quantification of PKM1 and PKM2 splice isoforms in 25 human malignant cancers, 6 benign oncocytomas, tissue matched controls, and several cell lines. PKM2 was the prominent isoform in all analyzed cancer samples and cell lines. However, this PKM2 dominance was not a result of a change in isoform expression, since PKM2 was also the predominant PKM isoform in matched control tissues. In unaffected kidney, lung, liver, and thyroid, PKM2 accounted for a minimum of 93% of total PKM, for 80% - 96% of PKM in colon, and 55% - 61% of PKM in bladder. Similar results were obtained for a panel of tumor and non-transformed cell lines, where PKM2 was the predominant form. Thus, our results reveal that an exchange in PKM1 to PKM2 isoform expression during cancer formation is not occurring, nor do these results support conclusions that PKM2 is specific for proliferating, and PKM1 for non-proliferating tissue
Exact exchange-correlation potential of a ionic Hubbard model with a free surface
We use Lanczos exact diagonalization to compute the exact
exchange-correlation (xc) potential of a Hubbard chain with large binding
energy ("the bulk") followed by a chain with zero binding energy ("the
vacuum"). Several results of density functional theory in the continuum
(sometimes controversial) are verified in the lattice. In particular we show
explicitly that the fundamental gap is given by the gap in the Kohn-Sham
spectrum plus a contribution due to the jump of the xc-potential when a
particle is added. The presence of a staggered potential and a nearest-neighbor
interaction V allows to simulate a ionic solid. We show that in the ionic
regime in the small hopping amplitude limit the xc-contribution to the gap
equals V, while in the Mott regime it is determined by the Hubbard U
interaction. In addition we show that correlations generates a new potential
barrier at the surface
Anatomy of BioJS, an open source community for the life sciences
BioJS is an open source software project that develops visualization tools for different types of biological data. Here we report on the factors that influenced the growth of the BioJS user and developer community, and outline our strategy for building on this growth. The lessons we have learned on BioJS may also be relevant to other open source software projects
Improved Slater approximation to SIC-OEP
We propose a simplification of the Optimized Effective Potential (OEP)
applied to the Self Interaction Correction (SIC) scheme of Density Functional
Theory (DFT). The new scheme fulfills several key formal properties and turns
out to be both simple and accurate. We show examples of applications on model
molecules in terms of observables known to be especially sensitive to details
of the SIC-OEP approach.Comment: 3 figure
Random-phase approximation and its applications in computational chemistry and materials science
The random-phase approximation (RPA) as an approach for computing the
electronic correlation energy is reviewed. After a brief account of its basic
concept and historical development, the paper is devoted to the theoretical
formulations of RPA, and its applications to realistic systems. With several
illustrating applications, we discuss the implications of RPA for computational
chemistry and materials science. The computational cost of RPA is also
addressed which is critical for its widespread use in future applications. In
addition, current correction schemes going beyond RPA and directions of further
development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012
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