Structure and reorientation kinetics of hydrogen passivated shallow impurities in silicon from vibrational spectroscopy

A survey is presented of what has been learned from vibrational spectroscopy and theory about the structure and reorientation kinetics of hydrogen-passivated shallow impurities in Si.     

An analytical proof of Hardy-like inequalities related to the Dirac operator

We prove some sharp Hardy-type inequalities related to the Dirac operator by elementary, direct methods. Some of these inequalities have been obtained previously using spectral information about the Dirac-Coulomb operator. Our results are stated under optimal conditions on the asymptotics of the potentials near zero and near infinity.     

Unsupervised constrained radar imaging of low resolution targets

A linear spectral estimation technique, the PDFT algorithm, is used as part of a nonlinear iterative reconstruction scheme to obtain improved radar images. The iterative PDFT algorithm is used to address the limited resolution problem inherent to imaging objects buried in soil and hidden under foliage. This is achieved by subsequent application of two properties of the PDFT algorithm: the energy parameter of the PDFT algorithm is used to determine the target shape, while the shape information in turn is used to obtain super-resolved images. We describe algorithms able to exploit both properties automatically and without manual intervention. Two methods are investigated in particular, one iteratively optimizing the constraints by monitoring the energy parameter, the other method computing energy values for all points, from which a weighted prior function is determined. In addition, we discuss variants of both algorithm which provide an optimized trade-off between computation time and performance. Additional attention is given to situations, where a known target is embedded in an unknown background. Imaging results are presented for both synthetic and measured data.     

The emergence of a giant component in random subgraphs of pseudo‐random graphs

Let G be a d‐regular graph G on n vertices. Suppose that the adjacency matrix of G is such that the eigenvalue λ which is second largest in absolute value satisfies λ = o(d). Let G_p with p = α/d be obtained from G by including each edge of G independently with probability p. We show that if α < 1, then whp the maximum component size of G_p is O(log n) and if α > 1, then G_p contains a unique giant component of size Ω(n), with all other components of size O(log n). © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 2004