Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSolving for Micro- and Macro- Scale Electrostatic Configurations Using the Robin Hood Algorithm
96
0
0.0
(
0
)
Added by
Joseph A. Formaggio
Publication date
2011
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We present a novel technique by which highly-segmented electrostatic configurations can be solved. The Robin Hood method is a matrix-inversion algorithm optimized for solving high density boundary element method (BEM) problems. We illustrate the capabilities of this solver by studying two distinct geometry scales: (a) the electrostatic potential of a large volume beta-detector and (b) the field enhancement present at surface of electrode nano-structures. Geometries with elements numbering in the O(10^5) are easily modeled and solved without loss of accuracy. The technique has recently been expanded so as to include dielectrics and magnetic materials.
rate research
Read More
We propose a harmonic surface mapping algorithm (HSMA) for electrostatic pairwise sums of an infinite number of image charges. The images are induced by point sources within a box due to a specific boundary condition which can be non-periodic. The HSMA first introduces an auxiliary surface such that the contribution of images outside the surface can be approximated by the least-squares method using spherical harmonics as basis functions. The so-called harmonic surface mapping is the procedure to transform the approximate solution into a surface charge and a surface dipole over the auxiliary surface, which becomes point images by using numerical integration. The mapping procedure is independent of the number of the sources and is considered to have a low complexity. The electrostatic interactions are then among those charges within the surface and at the integration points, which are all the form of Coulomb potential and can be accelerated straightforwardly by the fast multipole method to achieve linear scaling. Numerical calculations of the Madelung constant of a crystalline lattice, electrostatic energy of ions in a metallic cavity, and the time performance for large-scale systems show that the HSMA is accurate and fast, and thus is attractive for many applications.
Multi-scale feedback systems, where information cycles through micro- and macro-scales leading to adaptation, are ubiquitous across domains, from animal societies and human organisations to electric grids and neural networks. Studies on the effects of timing on system properties are often domain specific. The Multi-Scale Abstraction Feedbacks (MSAF) design pattern aims to generalise the description and understanding of multi-scale systems where feedback occurs across scales. We expand on MSAF to include timing considerations. We then apply these considerations to two models: a hierarchical oscillator (HO) and a hierarchical cellular automata (HCA). Results show how (i) different timing configurations significantly affect system macro-properties and (ii) different regions of time configurations can lead to the same macro-properties. These results contribute to theory, while also providing useful insights for designing and controlling such systems.
We propose to create and detect opto-mechanical entanglement by storing one component of an entangled state of light in a mechanical resonator and then retrieving it. Using micro-macro entanglement of light as recently demonstrated experimentally, one can then create opto-mechanical entangled states where the components of the superposition are macroscopically different. We apply this general approach to two-mode squeezed states where one mode has undergone a large displacement. Based on an analysis of the relevant experimental imperfections, the scheme appears feasible with current technology.
Synchronization overheads pose a major challenge as applications advance towards extreme scales. In current large-scale algorithms, synchronization as well as data communication delay the parallel computations at each time step in a time-dependent partial differential equation (PDE) solver. This creates a new scaling wall when moving towards exascale. We present a weakly-synchronous algorithm based on novel asynchrony-tolerant (AT) finite-difference schemes that relax synchronization at a mathematical level. We utilize remote memory access programming schemes that have been shown to provide significant speedup on modern supercomputers, to efficiently implement communications suitable for AT schemes, and compare to two-sided communications that are state-of-practice. We present results from simulations of Burgers equation as a model of multi-scale strongly non-linear dynamical systems. Our algorithm demonstrate excellent scalability of the new AT schemes for large-scale computing, with a speedup of up to $3.3$x in communication time and $2.19$x in total runtime. We expect that such schemes can form the basis for exascale PDE algorithms.
Three-dimensional (3D) printing has allowed for production of geometrically complex 3D objects with extreme flexibility, which is currently undergoing rapid expansions in terms of materials, functionalities, as well as areas of application. When attempting to print 3D microstructures in glass, femtosecond laser induced chemical etching (FLICE) has proved itself a powerful approach. Here, we demonstrate fabrication of macro-scale 3D glass objects of large heights up to ~3.8 cm with a well-balanced (i.e., lateral vs longitudinal) spatial resolution of ~20 {mu}m. The remarkable accomplishment is achieved by revealing an unexplored regime in the interaction of ultrafast laser pulses with fused silica which results in aberration-free focusing of the laser pulses deeply inside fused silica.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
