A test of the circular Unruh effect using atomic electrons

We propose a test for the circular Unruh effect using certain atoms - fluorine and oxygen. For these atoms the centripetal acceleration of the outer shell electrons implies an effective Unruh temperature in the range 1000 - 2000 K. This range of Unruh temperatures is large enough to shift the expected occupancy of the lowest energy level and nearby energy levels. In effect the Unruh temperature changes the expected pure ground state, with all the electrons in the lowest energy level, to a mixed state with some larger than expected occupancy of states near to the lowest energy level. Examining these atoms at low background temperatures and finding a larger than expected number of electrons in low lying excited levels, beyond what is expected due to the background thermal excitation, would provide experimental evidence for the Unruh effect.Comment: 16 pages, no figures Added discussion. To be published in EPJ

Hydrodynamic Interactions of Spherical Particles in A Fluid Confined by A Rough And No-Slip Wall

In this article we develop a theoretical framework to study the hydrodynamic interactions in the presence of a non-flat and no-slip boundary. We calculate the influence of a small amplitude and sinusoidal deformations of a boundary wall in the self mobility and the two body hydrodynamic interactions for spherical particles. We show that the surface roughness enhances the self mobility of a sphere in a way that, for motion in front of a local hump of the surface, the mobility strength decreases while it increases for the motion above a local deep of the rough surface. The influence of the surface roughness in the two body hydrodynamic interactions is also analyzed numerically.Comment: Phys. Rev. E 82, 036305 (2010

Improvement of BM3D Algorithm and Employment to Satellite and CFA Images Denoising

This paper proposes a new procedure in order to improve the performance of block matching and 3-D filtering (BM3D) image denoising algorithm. It is demonstrated that it is possible to achieve a better performance than that of BM3D algorithm in a variety of noise levels. This method changes BM3D algorithm parameter values according to noise level, removes prefiltering, which is used in high noise level; therefore Peak Signal-to-Noise Ratio (PSNR) and visual quality get improved, and BM3D complexities and processing time are reduced. This improved BM3D algorithm is extended and used to denoise satellite and color filter array (CFA) images. Output results show that the performance has upgraded in comparison with current methods of denoising satellite and CFA images. In this regard this algorithm is compared with Adaptive PCA algorithm, that has led to superior performance for denoising CFA images, on the subject of PSNR and visual quality. Also the processing time has decreased significantly.Comment: 11 pages, 7 figur

Primal Recovery from Consensus-Based Dual Decomposition for Distributed Convex Optimization

Dual decomposition has been successfully employed in a variety of distributed convex optimization problems solved by a network of computing and communicating nodes. Often, when the cost function is separable but the constraints are coupled, the dual decomposition scheme involves local parallel subgradient calculations and a global subgradient update performed by a master node. In this paper, we propose a consensus-based dual decomposition to remove the need for such a master node and still enable the computing nodes to generate an approximate dual solution for the underlying convex optimization problem. In addition, we provide a primal recovery mechanism to allow the nodes to have access to approximate near-optimal primal solutions. Our scheme is based on a constant stepsize choice and the dual and primal objective convergence are achieved up to a bounded error floor dependent on the stepsize and on the number of consensus steps among the nodes

Measuring Tie Strength in Implicit Social Networks

Given a set of people and a set of events they attend, we address the problem of measuring connectedness or tie strength between each pair of persons given that attendance at mutual events gives an implicit social network between people. We take an axiomatic approach to this problem. Starting from a list of axioms that a measure of tie strength must satisfy, we characterize functions that satisfy all the axioms and show that there is a range of measures that satisfy this characterization. A measure of tie strength induces a ranking on the edges (and on the set of neighbors for every person). We show that for applications where the ranking, and not the absolute value of the tie strength, is the important thing about the measure, the axioms are equivalent to a natural partial order. Also, to settle on a particular measure, we must make a non-obvious decision about extending this partial order to a total order, and that this decision is best left to particular applications. We classify measures found in prior literature according to the axioms that they satisfy. In our experiments, we measure tie strength and the coverage of our axioms in several datasets. Also, for each dataset, we bound the maximum Kendall's Tau divergence (which measures the number of pairwise disagreements between two lists) between all measures that satisfy the axioms using the partial order. This informs us if particular datasets are well behaved where we do not have to worry about which measure to choose, or we have to be careful about the exact choice of measure we make.Comment: 10 page