Query: accelerating particle in cell methods

title: Efficient Modeling of Plasma Wake Field Acceleration Experiments Using Particle In Cell Methods
abstract: There is no clear path for building a particle accelerator at the energy frontier beyond the Large Hadron Collider (LHC) One option that is receiving attention is to use plasma wave wakefields driven by intense particle beams. Recent experiments conducted at the Stanford Linear Accelerator Center (SLAC) show that accelerating gradients in such wakefields in excess of 50 GeV/m can be sustained over meter scales. Based on this, a linear collider concept of staging one meter long plasma cells together has been proposed. A facility at SLAC has been built to study the physics in one stage. In this dissertation we describe improvements and enhancements to a highly efficient simulation model for simulating current experiments at SLAC as well as parameters beyond the reach of current experiments. The model is the quasi static particle in cell (PIC) code QuickPIC. A modified set of quasi static field equations were developed, which reduced the number of predictor corrector iteration loops and an improved source deposit scheme was developed to reduce the parallel communication. These improvements led to a factor of 5 to 8 (depending on the simulation parameters) speedup compared with the previous set of field equations and deposition scheme. Several new modules were also added to QuickPIC, including the multiple field ionization and improved beam and plasma particle diagnostics. We also used QuickPIC to study the optimum plasma density for maximizing the acceleration field for fixed electron beam parameters. QuickPIC simulations were also used to study and design two bunch PWFA experiments at SLAC including methods for mitigating the ionization induced beam head erosion. The mitigation methods can enhance the energy gain in two bunch PWFA experiments at SLAC by a factor of 10 for the same beam parameters. For beam parameters beyond SLAC but perhaps necessary for a future collider, QuickPIC was used to study how the ultra high electric fields of a tightly focused second electron bunch could lead to ion motion, which disrupts the focusing fields on the second bunch. The resulting nonlinearity in the transverse focusing force of the plasma wake will lead to emittance growth. We used QuickPIC to carry out the first fully self consistent high resolution simulation on the effects of ion motion for PWFA linear collider problems. Preliminary results showed that the plasma ion motion induced emittance growth was limited to less than a factor of 2. In addition to the electron beam driven PWFA, we also study how a short proton beam can excite a large plasma wake. Such short proton beams are currently not experimentally available. We therefore also study how long proton beams such as those at Fermi National Laboratory and CERN may drive a large plasma wake through a self modulation instability. A linear theory for the self modulation instability is presented under the wide beam limit. QuickPIC simulations show that the self modulation of a long proton beam in a plasma may lead to the micro bunching of the beam and excite a large plasma wake.

title: Particle in cell simulation of collisional plasmas using multi processor architectures
abstract: The low temperature plasma physics community often employ s particle in cell simulation in conjunction with Monte Carlo collisions, typically to mode l the interaction between the plasma and a background neutral gas, although more general collisi onal nteractions can be handled as well. The use of this attractive procedure is limited by th e computational cost. This paper describes various methods for accelerating particle in c ell simulations using commodity computer hardware.  Particle in cell simulation is widely used for modelling l ow temperature plasma phenomena  The attraction of the method is that it entails no assump tions about the form of particle distribution functions, or the nature of their interactions wi th the electromagnetic fields. This is useful, because plasma discharges often feature exotically no n Maxwellian distribution functions, and violently non equilibrium interactions between the ch arged particles and the fields. The purpose of the present paper is to explore the use of modern de sktop computers for particle incell simulation. Such computers typically feature multipl e rocessors, and multiple cores within processors, combined with a hierarchical memory structure This usually means that a relatively capacious main memory is shared by all the processors, while each processor or core has one or more local memories, with less capacity but greater speed. M oreover, most modern processors have some capability for so called single instruction mult iple data (SIMD) operations, a kind of vectorisation. The approach discussed in this paper has t hree elements: (1) A reorganistion of the simulation data structure, with the twin aims of reduc ing memory bandwidth usage and facilitating vectorisation (2) introducing SIMD instruct ions to speed processing of particles and (3) using OpenMP constructions to enable multiple cores to b e used. The combination of these measures can accelerate the simulation by as much as a factor of thirteen, and by a factor of ten over a wide range of conditions, on a common hardware configur ation with two processors and eight cores. 37 EPS Conference on Plasma Physics P4.329 Data structure and vectorization The natural data structure for a particle in cell simulati on is a set of arrays, each storing one of the particle coordinates, with no correlation between th e logical position of a particle in the array and the physical location of the same particle in the si mulated spatial region. The computational cycle of a particle in cell simulation consists o f data transfers from particle positions to spatial mesh points and back again. If the particles are proc essed in sequential order, this leads to a random pattern of access to the mesh point data. Not only w ill this produce much movement of mesh data through the memory hierarchy, but vectorisatio n is impeded by simultaneous accesses to the same mesh location. These issues are addressed by introducing a data structure that associates particles with cells. We can then process all the particles belonging to a given cell in a group, and the mesh data can be stored in registers, economi si g on both memory bandwidth and pointer arithmetic when loading mesh data. This approac h also facilitates vectorisation. Although there are other possibilities [2, 3] the data stru cture we have adopted is an unrolled linked list, a hybrid approach in which an array of data is sto red at each node of a linked list. Of course, particles move between cells, and work is required t o maintain the data structure. This is equivalent to sorting the particles, but this is a tolerable computational burden. Fig. 1 compares an orthodox particle in cell implementation with the pres ent approach, for a simple case with one real space and one velocity space dimension. For a reason ably large number of particles per cell (NC 100) the improvement achieved is about 20 for the new data s tructure only, and about 50 when vectorisation is also used. The orthodox impl e entation cannot be vectorised, for reasons already remarked. Maintaining the sorted data s tructure consumes 30 40 of the computation time, with the implication that better results can be expected for more elaborate models, such as those involving three velocity components a nd magnetic fields. Parallelisation OpenMP  offers a lightweight framework for introducing p arallelism into programs designed for shared memory architectures. The approach discu ssed above lends itself readily to parallisation using OpenMP, which can be combined with MPI t o exploit systems that combine shared and distributed memory. Results obtained in this way are shown in Figs. 2 and 3. Fig. 3 shows that there is a regime where a superlinear speedup is ob tained. This occurs because the available cache memory is increased by using more cores.  The methods employed here combine to produce a speedup that i s in excess of thirteen at best, and above ten over a useful range of problem sizes. More m dern hardware, with better 37 EPS Conference on Plasma Physics P4.329

title: Accelerating Cell Dynamics Simulations of Soft Materials using CUDA GPU
abstract: Soft materials are a highly demanded class of research for predicting the characteristics of phase separation and self assembly into nanoscale structures. One of the most well known methods to demonstrate and simulate dynamic behavior of particles, such as particle tracking, and to consider different effects of simulation parameters is cell dynamic simulation. In fact, cell dynamic simulation as a cellular computerization can be used to investigate different aspects of morphological topographies of soft material system. To achieve accurate and efficient computational results for cell dynamic simulation method, two factors are essential and vital: first, computing/calculating time scale; and second, simulation system size. Consequently, finding available computing algorithms and resources such as sequential algorithm for implementing a complex technique and achieving precise results is critical and expensive. Therefore, it is very important to consider a parallel algorithm and programming model to solve time consuming and massive computational processing. This paper presents a novel GPU based parallel acceleration approach to cell dynamics simulations (CDS) for a spherical phase diblock copolymer under a shear flow. A new achievement is based on a commodity NVIDIA Quadro K5000 graphic card and Compute Unified Device Architecture (CUDA) C language.

title: Accelerating a paricle in cell simulation using a hybrid counting sort
abstract: In this article, performance limitations of the particle advance in a particle in cell (PIC) simulation are discussed. It is shown that the memory subsystem and cache thrashing severely limit the speed of such simulations. Methods to implement a PIC simulation under such conditions are explored. An algorithm based on a counting sort is developed which effectively eliminates PIC simulation cache thrashing. Sustained performance gains of 40 to 70 percent are measured on commodity workstations for a minimal 2d2v electrostatic PIC simulation. More complete simulations are expected to have even better results as larger simulations are usually even more memory subsystem limited.

title: Niobium pentoxide and hydroxyapatite particle loaded electrospun polycaprolactone/gelatin membranes for bone tissue engineering.
abstract: Effective methods of accelerating the bone regeneration healing process are in demand for a number of bone related diseases and trauma. This work developed scaffolds with improved properties for bone tissue engineering by electrospinning composite polycaprolactone gelatin hydroxyapatite niobium pentoxide (PGHANb) membranes. Composite membranes, with average fiber diameters ranging from 123 to 156 nm, were produced by adding hydroxyapatite (HA) and varying concentrations of niobium pentoxide (Nb2O5) particles (0, 3, 7, and 10 wt% to a polycaprolactone (PCL) and gelatin (GL) matrix prior to electrospinning. The morphology, mechanical, chemical and biological properties of resultant membranes were evaluated. Bioactivity was assessed using simulated body fluid (SBF) and it confirmed that the presence of particles induced the formation of hydroxyapatite crystals on the surface of the membranes. Samples were hydrophilic and cell metabolism results showed that the niobium containing membranes were non toxic while improving cell proliferation and differentiation compared to controls. This study demonstrated that electrospun membranes containing HA and Nb2O5 particles have potential to promote cell adhesion and proliferation while exhibiting bioactive properties. PGHANb membranes are promising candidates for bone tissue engineering applications.

title: Fermi type Particle Acceleration from Magnetic Reconnection at the Termination Shock of a Relativistic Striped Wind
abstract: An oblique rotating pulsar generates a relativistic striped wind in a pulsar wind nebula (PWN) The termination shock of the PWN compresses the Poynting flux dominated flow and drives magnetic reconnection. By carrying out particle in cell simulations of the termination shock of the PWN, we study the shock structure as well as the energy conversion processes and particle acceleration mechanisms. With the recent advances in the numerical methods, we extend the simulations to the ultrarelativistic regime with a bulk Lorentz factor of up to g 0 106. Magnetic reconnection at the termination shock is highly efficient at converting magnetic energy to particle kinetic energy and accelerating particles to high energies. Similar to earlier studies, we find that the resulting energy spectra crucially depend on l/d e (l is the wavelength of the striped wind and d e is the relativistic plasma skin depth) When l/d e is large (l 40d e the downstream particle spectra form a power law distribution in the magnetically dominated relativistic wind regime. By analyzing particle trajectories and statistical quantities relevant to particle energization, we find that Fermi type mechanism dominates the particle acceleration and power law formation. We find that the results for particle acceleration are scalable as g 0 and s 0 increase to large values. The maximum energy for electrons and positrons can reach hundreds of TeV if the wind has a bulk Lorentz factor of g 0 106 and a magnetization parameter of s 0 10, which can explain the recent observations of high energy gamma rays from PWNe.

title: Accelerating Pairwise Computations on Cell Processors
abstract: Direct computation of all pairwise distances or interactions is a fundamental problem that arises in many application areas including particle or atomistic simulations, fluid dynamics, computational electromagnetics, materials science, genomics and systems biology, and clustering and data mining. In this paper, we present methods for performing such pairwise computations efficiently in parallel on Cell processors. This problem is particularly challenging on the Cell processor due to the small sized Local Stores of the Synergistic Processing Elements, the main computational cores of the processor. We present techniques for different variants of this problem including those with large number of entities or when the dimensionality of the information per entity is large. We demonstrate our methods in the context of multiple applications drawn from fluid dynamics, materials science and systems biology, and present detailed experimental results. Our software library is an open source and can be readily used by application scientists to accelerate pairwise computations using Cell accelerators.

title: Photovoltaic Characteristics of a Dye Sensitized Solar Cell (DSSC) Fabricated by a Nano Particle Deposition System (NPDS)
abstract: Nano particle deposition system (NPDS) was evaluated for the potential photoelectrode fabrication method for dye sensitized solar cell (DSSC) TiO2 powders as a photoelectrode for DSSC, were fabricated via NPDS and screen printing methods to compare its photovoltaic characteristics. The NPDS is a novel system for depositing ceramic and metallic powders on substrates at room temperature without using solvents by accelerating particles to supersonic velocity. The conventional method for preparing working electrodes uses TiO2 paste where poor adhesion to the substrate and numerous steps to properly disperse the powders are the main problems. To overcome these issues, TiO2 powders were directly sprayed onto ITO glass using the NPDS. The nano sized TiO2 particles were densely deposited, no adhesion problems were noted and the solar cell properties were improved. The photovoltaic performance of a cell having TiO2 layers first deposited by the NPDS method and then deposited by the paste method was compared to a cell fabricated only using the NPDS and only using the paste. A light conversion efficiency of 3.5% was obtained for the former cell, which indicates synergy effect of using these two methods. The screen printing step right after NPDS deposition served to densify the TiO2 film, which decreased the series resistance. Therefore, NPDS was found to be a promising approach for improving DSSC properties and efficiencies.

title: 3 D Structure of Cellulose Microfibril in Wood Using Electron Tomography and Single Particle Reconstruction Methods
abstract: Extended abstract of a paper presented at Microscopy and Microanalysis 2013  2013.

title: Single Shot Characterization of High Transformer Ratio Wakefields in Nonlinear Plasma Acceleration.
abstract: Plasma wakefields can enable very high accelerating gradients for frontier high energy particle accelerators, in excess of 10 GeV/m. To overcome limits on single stage acceleration, specially shaped drive beams can be used in both linear and nonlinear plasma wakefield accelerators (PWFA) to increase the transformer ratio, implying that the drive beam deceleration is minimized relative to acceleration obtained in the wake. In this Letter, we report the results of a nonlinear PWFA, high transformer ratio experiment using high charge, longitudinally asymmetric drive beams in a plasma cell. An emittance exchange process is used to generate variable drive current profiles, in conjunction with a long (multiple plasma wavelength) witness beam. The witness beam is energy modulated by the wakefield, yielding a response that contains detailed spectral information in a single shot measurement. Using these methods, we generate a variety of beam profiles and characterize the wakefields, directly observing transformer ratios up to R=7.8. Furthermore, a spectrally based reconstruction technique, validated by 3D particle in cell simulations, is introduced to obtain the drive beam current profile from the decelerating wake data.