Jose Luis Guisado

Coulomb- and nuclear-induced break-up of halo nuclei at bombarding energies around the Coulomb barrier

Abstract We investigate the relative importance of the Coulomb and nuclear fields to induce the break-up of neutron-rich nuclei such as 11 Li at energies close to the Coulomb barrier. We assume that the mechanism that leads to the separation is the excitation of a low-lying dipole mode in which the weakly-bound neutron halo performs a collective oscillation against the residual nuclear core. To this end we exploit semiclassical prescriptions that are adequate to calculate not only the average break-up probabilities but also to estimate the size of fluctuations about the quantal expectation values. Possible outcomes are explored as a function of both bombarding energy and impact parameter. Consequences of the couplings for elastic scattering and fusion processes are also discussed.

Application of shannon's entropy to classify emergent behaviors in a simulation of laser dynamics

Laser dynamics simulations have been carried out using a cellular automata model. The Shannons entropy has been used to study the different emergent behaviors exhibited by the system, mainly the laser spiking and the laser constant operation. It is also shown that the Shannons entropy of the distribution of the populations of photons and electrons reproduces the laser stability curve, in agreement with the theoretical predictions from the laser rate equations and with the experimental results.

Performance evaluation of RAM-based implementation of Finite State Machines in FPGAs

This paper presents a study of performance of RAM-based implementations in FPGAs of Finite State Machines (FSMs). The influence of the FSM characteristics on speed and area has been studied, taking into account the particular features of different FPGA families, like the size of LUTs, the size of memory blocks, the number of embedded multiplexer levels and the specific decoding logic for distributed RAM. Our study can be useful for efficiently implementing FPGA-based state machines.

Parallel implementation of a cellular automaton model for the simulation of laser dynamics

The classical modeling approach for laser study relies on the differential equations. In this paper, a cellular automaton model is proposed as an alternative for the simulation of population dynamics. Even though the model is simplified it captures the essence of laser phenomenology: (i) there is a threshold pumping rate that depends inversely on the decaying lifetime of the atoms and the photons; and (ii) depending on these lifetimes and on the pumping rate, a constant or an oscillatory behavior can be observed. More complex behaviors such as spiking and pattern formation can also be studied with the cellular automaton model.

Control of Bloat in Genetic Programming by Means of the Island Model

This paper presents a new proposal for reducing bloat in Genetic Programming. This proposal is based in a well-known parallel evolutionary model: the island model. We firstly describe the theoretical motivation for this new approach to the bloat problem, and then we present a set of experiments that gives us evidence of the findings extracted from the theory. The experiments have been performed on a representative problem extracted from the GP field: the even parity 5 problem. We analyse the evolution of bloat employing different settings for the parameters employed. The conclusion is that the Island Model helps to prevent the bloat phenomenon.

Simulation of the Dynamics of Pulsed Pumped Lasers Based on Cellular Automata

Laser dynamics is traditionally modeled using differential equations. Recently, a new approach has been introduced in which laser dynamics is modeled using two-dimensional Cellular Automata (CA). In this work, we study a modified version of this model in order to simulate the dynamics of pulsed pumped lasers. The results of the CA approach are in qualitative agreement with the outcome of the numerical integration of the laser rate equations.

CELLULAR AUTOMATA AND CLUSTER COMPUTING: AN APPLICATION TO THE SIMULATION OF LASER DYNAMICS

Firstly, the application of a cellular automata (CA) model to simulate the dynamics of lasers is reviewed. With this kind of model, the macroscopic properties of the laser system emerge as a cooperative phenomenon from elementary components locally interacting under simple rules. Secondly, a parallel implementation of this kind of model for distributed-memory parallel computers is presented. Performance and scalability of this parallel implementation running on a computer cluster are analyzed, giving very satisfactory results. This confirms the feasibility of running large 3D simulations — unaffordable on an individual machine — on computer clusters, in order to simulate specific real laser systems.

Application of Shannon's entropy to classify emergent behaviors in a simulation of laser dynamics

Laser dynamics simulations have been carried out using a cellular automata model. The Shannons entropy has been used to study the different emergent behaviors exhibited by the system, mainly the laser spiking and the laser constant operation. It is also shown that the Shannons entropy of the distribution of the populations of photons and electrons reproduces the laser stability curve, in agreement with the theoretical predictions from the laser rate equations and with the experimental results.

Performance analysis of a parallel discrete model for the simulation of laser dynamics

This paper presents an analysis on the performance of a parallel implementation of a discrete model of laser dynamics, which is based on cellular automata. The performance of a 2D parallel version of the model is studied as a first step to test the feasibility of a parallel 3D version, which is needed to simulate specific laser systems. The 3D version will have to run on a parallel computer due to its runtime and memory requirements. The model has been implemented on a Beowulf cluster using the message passing paradigm. The parallel implementation is found to exhibit a good speedup, allowing us to run realistic simulations of laser systems on clusters of workstations, which could not be afforded on an individual machine due to the extensive runtime and memory size needed

Using cellular automata for parallel simulation of laser dynamics with dynamic load balancing

We present an analysis of the feasibility of executing a parallel bioinspired model of laser dynamics, based on cellular automata (CA), on the usual target platform of this kind of applications: a heterogeneous non-dedicated cluster. As this model employs a synchronous CA, using the single program, multiple data (SPMD) paradigm, it is not clear in advance if an appropriate efficiency can be obtained on this kind of platform. We have evaluated its performance including artificial load to simulate other tasks or jobs submitted by other users. A dynamic load balancing strategy with two main differences from most previous implementations of CA based models has been used. First, it is possible to migrate load to cluster nodes initially not belonging to the pool. Second, a modular approach is taken in which the model is executed on top of a dynamic load balancing tool – the Dynamite system – gaining flexibility. Very satisfactory results have been obtained, with performance increases from 60% to 80%.