Splitting the fast and slow motions in molecular dynamics simulations based on the change of cold potential well bottom

Abstract. The atomic motion is coupled by the fast and slow components due to the high frequency vibration of atoms and the low frequency deformation of atomic lattice, respectively. A two-step approximate method was presented to determine the atomic slow motion. The first step is based on the change of the location of the cold potential well bottom and the second step is based on the average of the appropriate slow velocities of the surrounding atoms. The simple tensions of one-dimensional atoms and two-dimensional atoms were performed with the full molecular dynamics simulations. The conjugate gradient method was employed to determine the corresponding location of cold potential well bottom. Results show that our two-step approximate method is appropriate to determine the atomic slow motion under the low strain rate loading. This splitting method may be helpful to develop more efficient molecular modeling methods and simulations pertinent to realistic loading conditions of materials.

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

The diagnostics of density distribution for inhomogeneous dense DT plasmas using fast protons

The density distribution of inhomogeneous dense deuterium-tritium plasmas in laser fusion is revealed by the energy loss of fast protons going through the plasma. In our simulation of a plasma density diagnostics, the fast protons used for the diagnostics may be generated in the laser-plasma interaction. Dividing a two-dimensional area into grids and knowing the initial and final energies of the protons, we can obtain a large linear and ill-posed equation set. for the densities of all grids, which is solved with the Tikhonov regularization method. We find that the accuracy of the set plan with four proton sources is better than those of the set plans with less than four proton sources. Also we have done the density reconstruction especially. for four proton sources with and without assuming circularly symmetrical density distribution, and find that the accuracy is better for the reconstruction assuming circular symmetry. The error is about 9% when no noise is added to the final energy for the reconstruction of four proton sources assuming circular symmetry. The accuracies for different random noises to final proton energies with four proton sources are also calculated.

Analog VLSI-based, neuromorphic sensorimotor systems: modeling the primate oculomotor system

Using neuromorphic analog VLSI techniques for modeling large neural systems has several advantages over software techniques. By designing massively-parallel analog circuit arrays which are ubiquitous in neural systems, analog VLSI models are extremely fast, particularly when local interactions are important in the computation. While analog VLSI circuits are not as flexible as software methods, the constraints posed by this approach are often very similar to the constraints faced by biological systems. As a result, these constraints can offer many insights into the solutions found by evolution. This dissertation describes a hardware modeling effort to mimic the primate oculomotor system which requires both fast sensory processing and fast motor control. A one-dimensional hardware model of the primate eye has been built which simulates the physical dynamics of the biological system. It is driven by analog VLSI circuits mimicking brainstem and cortical circuits that control eye movements. In this framework, a visually-triggered saccadic system is demonstrated which generates averaging saccades. In addition, an auditory localization system, based on the neural circuits of the barn owl, is used to trigger saccades to acoustic targets in parallel with visual targets. Two different types of learning are also demonstrated on the saccadic system using floating-gate technology allowing the non-volatile storage of analog parameters directly on the chip. Finally, a model of visual attention is used to select and track moving targets against textured backgrounds, driving both saccadic and smooth pursuit eye movements to maintain the image of the target in the center of the field of view. This system represents one of the few efforts in this field to integrate both neuromorphic sensory processing and motor control in a closed-loop fashion.

Experiments in Neutrino Mass and Mixing: Part I - New Limits on Heavy Neutrino Emission in Nuclear Beta Decay. Part II - Fast Neutron Backgrounds for the San Onofre Neutrino Detector

In Part I of this thesis, a new magnetic spectrometer experiment which measured the β spectrum of ^(35)S is described. New limits on heavy neutrino emission in nuclear β decay were set, for a heavy neutrino mass range between 12 and 22 keV. In particular, this measurement rejects the hypothesis that a 17 keV neutrino is emitted, with sin^2 θ = 0.0085, at the 6δ statistical level. In addition, an auxiliary experiment was performed, in which an artificial kink was induced in the β spectrum by means of an absorber foil which masked a fraction of the source area. In this measurement, the sensitivity of the magnetic spectrometer to the spectral features of heavy neutrino emission was demonstrated.

In Part II, a measurement of the neutron spallation yield and multiplicity by the Cosmic-ray Underground Background Experiment is described. The production of fast neutrons by muons was investigated at an underground depth of 20 meters water equivalent, with a 200 liter detector filled with 0.09% Gd-loaded liquid scintillator. We measured a neutron production yield of (3.4 ± 0.7) x 10^(-5) neutrons per muon-g/cm^2, in agreement with other experiments. A single-to-double neutron multiplicity ratio of 4:1 was observed. In addition, stopped π^+ decays to µ^+ and then e^+ were observed as was the associated production of pions and neutrons, by the muon spallation interaction. It was seen that practically all of the π^+ produced by muons were also accompanied by at least one neutron. These measurements serve as the basis for neutron background estimates for the San Onofre neutrino detector.