Algorithms for 3D rigidity analysis and a first order percolation transition

A fast computer algorithm, the pebble game, has been used successfully to study rigidity percolation on 2D elastic networks, as well as on a special class of 3D networks, the bond-bending networks. Application of the pebble game approach to general 3D networks has been hindered by the fact that the underlying mathematical theory is, strictly speaking, invalid in this case. We construct an approximate pebble game algorithm for general 3D networks, as well as a slower but exact algorithm, the relaxation algorithm, that we use for testing the new pebble game. Based on the results of these tests and additional considerations, we argue that in the particular case of randomly diluted central-force networks on BCC and FCC lattices, the pebble game is essentially exact. Using the pebble game, we observe an extremely sharp jump in the largest rigid cluster size in bond-diluted central-force networks in 3D, with the percolating cluster appearing and taking up most of the network after a single bond addition. This strongly suggests a first order rigidity percolation transition, which is in contrast to the second order transitions found previously for the 2D central-force and 3D bond-bending networks. While a first order rigidity transition has been observed for Bethe lattices and networks with ``chemical order'', this is the first time it has been seen for a regular randomly diluted network. In the case of site dilution, the transition is also first order for BCC, but results for FCC suggest a second order transition. Even in bond-diluted lattices, while the transition appears massively first order in the order parameter (the percolating cluster size), it is continuous in the elastic moduli. This, and the apparent non-universality, make this phase transition highly unusual.Comment: 28 pages, 19 figure

Self-organization with equilibration: a model for the intermediate phase in rigidity percolation

Recent experimental results for covalent glasses suggest the existence of an intermediate phase attributed to the self-organization of the glass network resulting from the tendency to minimize its internal stress. However, the exact nature of this experimentally measured phase remains unclear. We modify a previously proposed model of self-organization by generating a uniform sampling of stress-free networks. In our model, studied on a diluted triangular lattice, an unusual intermediate phase appears, in which both rigid and floppy networks have a chance to occur, a result also observed in a related model on a Bethe lattice by Barre et al. [Phys. Rev. Lett. 94, 208701 (2005)]. Our results for the bond-configurational entropy of self-organized networks, which turns out to be only about 2% lower than that of random networks, suggest that a self-organized intermediate phase could be common in systems near the rigidity percolation threshold.Comment: 9 pages, 6 figure

Science aspects of a 1980 flyby of Comet Encke with a Pioneer spacecraft

Results are presented of an investigation of the feasibility of a 1980 flyby of Comet Encke using a Pioneer class spacecraft. Specific areas studied include: science objectives and rationale; science observables; effects of encounter velocity; science encounter and targeting requirements; selection and description of science instruments; definition of a candidate science payload; engineering characteristics of suggested payload; value of a separable probe; science instruments for a separable probe; science payload integration problems; and science operations profile

Science aspects of 1980 ballistic missions to comet Encke, using Mariner and Pioneer spacecraft

Science aspects of a 1980 spacecraft reconnaissance of Comet Encke are considered. The mission discussed is a ballistic flyby (more exactly, a fly-through) of P/Encke, using either a spin stabilized spacecraft, without despin of instruments, or a 3-axis stabilized spacecraft

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

Scientific possibilities of a solar electric powered rendezvous with comet Encke

The minimum scientific spacecraft instrumentation is considered that is likely to result in as complete an understanding of the composition, structure, and activity of a cometary nucleus as is possible without landing on it. The payload will also give useful results on secondary goals of a better understanding of physical processes in the inner and outer coma. Studies of composition, by means of an actual landing on the surface, details of the internal structure of the nucleus, and sample return were considered beyond the scope of this mission

A bio-inspired image coder with temporal scalability

We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalian retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, our decoded images do not show annoying artefacts such as ringing and block effects. As a whole, this article shows how to capture the main properties of a biological system, here the retina, in order to design a new efficient coder.Comment: 12 pages; Advanced Concepts for Intelligent Vision Systems (ACIVS 2011

Computational study of structural and elastic properties of random AlGaInN alloys

In this work we present a detailed computational study of structural and elastic properties of cubic AlGaInN alloys in the framework of Keating valence force field model, for which we perform accurate parametrization based on state of the art DFT calculations. When analyzing structural properties, we focus on concentration dependence of lattice constant, as well as on the distribution of the nearest and the next nearest neighbour distances. Where possible, we compare our results with experiment and calculations performed within other computational schemes. We also present a detailed study of elastic constants for AlGaInN alloy over the whole concentration range. Moreover, we include there accurate quadratic parametrization for the dependence of the alloy elastic constants on the composition. Finally, we examine the sensitivity of obtained results to computational procedures commonly employed in the Keating model for studies of alloys

High real-space resolution measurement of the local structure of Ga_1-xIn_xAs using x-ray diffraction

High real-space resolution atomic pair distribution functions (PDF)s from the alloy series Ga_1-xIn_xAs have been obtained using high-energy x-ray diffraction. The first peak in the PDF is resolved as a doublet due to the presence of two nearest neighbor bond lengths, Ga-As and In-As, as previously observed using XAFS. The widths of nearest, and higher, neighbor pairs are analyzed by separating the strain broadening from the thermal motion. The strain broadening is five times larger for distant atomic neighbors as compared to nearest neighbors. The results are in agreement with model calculations.Comment: 4 pages, 5 figure