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.

Guiding and confining fast electrons by transient electric and magnetic fields with a plasma inverse cone

The fast electron propagation in an inverse cone target is investigated computationally and experimentally. Two-dimensional particle-in-cell simulation shows that fast electrons with substantial numbers are generated at the outer tip of an inverse cone target irradiated by a short intense laser pulse. These electrons are guided and confined to propagate along the inverse cone wall, forming a large surface current. The propagation induces strong transient electric and magnetic fields which guide and confine the surface electron current. The experiment qualitatively verifies the guiding and confinement of the strong electron current in the wall surface. The large surface current and induced strong fields are of importance for fast ignition related researches.

Optimum hot electron production with low-density foams for laser fusion by fast ignition

We propose a foam cone-in-shell target design aiming at optimum hot electron production for the fast ignition. A thin low-density foam is proposed to cover the inner tip of a gold cone inserted in a fuel shell. An intense laser is then focused on the foam to generate hot electrons for the fast ignition. Element experiments demonstrate increased laser energy coupling efficiency into hot electrons without increasing the electron temperature and beam divergence with foam coated targets in comparison with solid targets. This may enhance the laser energy deposition in the compressed fuel plasma.

Future of earthquake early warning : quantifying uncertainty and making fast automated decisions for applications

Earthquake early warning (EEW) systems have been rapidly developing over the past decade. Japan Meteorological Agency (JMA) has an EEW system that was operating during the 2011 M9 Tohoku earthquake in Japan, and this increased the awareness of EEW systems around the world. While longer-time earthquake prediction still faces many challenges to be practical, the availability of shorter-time EEW opens up a new door for earthquake loss mitigation. After an earthquake fault begins rupturing, an EEW system utilizes the first few seconds of recorded seismic waveform data to quickly predict the hypocenter location, magnitude, origin time and the expected shaking intensity level around the region. This early warning information is broadcast to different sites before the strong shaking arrives. The warning lead time of such a system is short, typically a few seconds to a minute or so, and the information is uncertain. These factors limit human intervention to activate mitigation actions and this must be addressed for engineering applications of EEW. This study applies a Bayesian probabilistic approach along with machine learning techniques and decision theories from economics to improve different aspects of EEW operation, including extending it to engineering applications.

Existing EEW systems are often based on a deterministic approach. Often, they assume that only a single event occurs within a short period of time, which led to many false alarms after the Tohoku earthquake in Japan. This study develops a probability-based EEW algorithm based on an existing deterministic model to extend the EEW system to the case of concurrent events, which are often observed during the aftershock sequence after a large earthquake.

To overcome the challenge of uncertain information and short lead time of EEW, this study also develops an earthquake probability-based automated decision-making (ePAD) framework to make robust decision for EEW mitigation applications. A cost-benefit model that can capture the uncertainties in EEW information and the decision process is used. This approach is called the Performance-Based Earthquake Early Warning, which is based on the PEER Performance-Based Earthquake Engineering method. Use of surrogate models is suggested to improve computational efficiency. Also, new models are proposed to add the influence of lead time into the cost-benefit analysis. For example, a value of information model is used to quantify the potential value of delaying the activation of a mitigation action for a possible reduction of the uncertainty of EEW information in the next update. Two practical examples, evacuation alert and elevator control, are studied to illustrate the ePAD framework. Potential advanced EEW applications, such as the case of multiple-action decisions and the synergy of EEW and structural health monitoring systems, are also discussed.

Fast growing mode of stimulated Raman scattering in a pure three-wave process

Stimulated Raman scattering (SRS) of a relativistic laser in plasmas is studied in the framework of the standard equation set of a three-wave process. As far as every wave involved in the process is concerned, its evolution has two aspects: time-dependent amplitude and time-dependent frequency. These two aspects affect each other. Strict analysis and numerical experiment on the full three-wave equation set reveal that a fast growing mode of the instability, which could reach a balance or saturation point during a period far shorter than an estimation based on conventional analysis, could take place in a standard three-wave process without coupling with a fourth wave. This fast growing mode is found to stem from the constraint set by the background density on the amplitude of the driven Langmuir wave. The effect of various parameters on the development of the SRS instability is studied by numerical calculation of the history of the instability in different cases. (c) 2007 American Institute of Physics.

Relativistic laser channeling in plasmas for fast ignition

We report an experimental observation suggesting plasma channel formation by focusing a relativistic laser pulse into a long-scale-length preformed plasma. The channel direction coincides with the laser axis. Laser light transmittance measurement indicates laser channeling into the high-density plasma with relativistic self-focusing. A three-dimensional particle-in-cell simulation reproduces the plasma channel and reveals that the collimated hot-electron beam is generated along the laser axis in the laser channeling. These findings hold the promising possibility of fast heating a dense fuel plasma with a relativistic laser pulse.