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Artículos de revistas sobre el tema "Particle-In-Cell code"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 12 de febrero de 2022

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1

Welch, D. R., T. C. Genoni, R. E. Clark y D. V. Rose. "Adaptive particle management in a particle-in-cell code". Journal of Computational Physics 227, n.º 1 (noviembre de 2007): 143–55. http://dx.doi.org/10.1016/j.jcp.2007.07.015.

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2

Tao, Weifeng. "Skeleton Particle-In-Cell Code on CUDA". Journal of the Visualization Society of Japan 28-1, n.º 1 (2008): 291. http://dx.doi.org/10.3154/jvs.28.291.

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3

Matsumoto, Masami y Shigeo Kawata. "TRIPIC: Triangular-mesh particle-in-cell code". Journal of Computational Physics 87, n.º 2 (abril de 1990): 488–93. http://dx.doi.org/10.1016/0021-9991(90)90262-y.

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4

Mehrling, T., C. Benedetti, C. B. Schroeder y J. Osterhoff. "HiPACE: a quasi-static particle-in-cell code". Plasma Physics and Controlled Fusion 56, n.º 8 (22 de julio de 2014): 084012. http://dx.doi.org/10.1088/0741-3335/56/8/084012.

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5

SEIDEL, D. B., M. L. KIEFER, R. S. COATS, T. D. POINTON, J. P. QUINTENZ y W. A. JOHNSON. "The 3-D, Electromagnetic, Particle-In-Cell Code, QUICKSILVER". International Journal of Modern Physics C 02, n.º 01 (marzo de 1991): 475–82. http://dx.doi.org/10.1142/s012918319100072x.

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6

Olshevsky, V., F. Bacchini, S. Poedts y G. Lapenta. "Slurm: Fluid particle-in-cell code for plasma modeling". Computer Physics Communications 235 (febrero de 2019): 16–24. http://dx.doi.org/10.1016/j.cpc.2018.06.014.

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7

BRODIN, GERT, AMOL HOLKUNDKAR y MATTIAS MARKLUND. "Particle-in-cell simulations of electron spin effects in plasmas". Journal of Plasma Physics 79, n.º 4 (21 de febrero de 2013): 377–82. http://dx.doi.org/10.1017/s0022377813000093.

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AbstractWe present a particle-in-cell code accounting for the magnetic dipole force and for the magnetization currents associated with the electron spin. The electrons are divided into spin-up and spin-down populations relative to the magnetic field, where the magnetic dipole force acts in opposite directions for the two species. To validate the code, we study wakefield generation by an electromagnetic pulse propagating parallel to an external magnetic field. The properties of the generated wakefield are shown to be in good agreement with previous theoretical results. Generalizations of the code to account for other quantum effects are discussed.

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8

Haugbølle, Troels, Jacob Trier Frederiksen y Åke Nordlund. "photon-plasma: A modern high-order particle-in-cell code". Physics of Plasmas 20, n.º 6 (junio de 2013): 062904. http://dx.doi.org/10.1063/1.4811384.

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9

Shalaby, Mohamad, Avery E. Broderick, Philip Chang, Christoph Pfrommer, Astrid Lamberts y Ewald Puchwein. "SHARP: A Spatially Higher-order, Relativistic Particle-in-cell Code". Astrophysical Journal 841, n.º 1 (23 de mayo de 2017): 52. http://dx.doi.org/10.3847/1538-4357/aa6d13.

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10

sci, global. "EMPIRE-PIC: A Performance Portable Unstructured Particle-in-Cell Code". Communications in Computational Physics 30, n.º 4 (junio de 2021): 1232–68. http://dx.doi.org/10.4208/cicp.oa-2020-0261.

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11

WANG, J., D. KONDRASHOV, P. C. LIEWER y S. R. KARMESIN. "Three-dimensional deformable-grid electromagnetic particle-in-cell for parallel computers". Journal of Plasma Physics 61, n.º 3 (abril de 1999): 367–89. http://dx.doi.org/10.1017/s0022377899007552.

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We describe a new parallel, non-orthogonal-grid, three-dimensional electromagnetic particle-in-cell (EMPIC) code based on a finite-volume formulation. This code uses a logically Cartesian grid of deformable hexahedral cells, a discrete surface integral (DSI) algorithm to calculate the electromagnetic field, and a hybrid logical–physical space algorithm to push particles. We investigate the numerical instability of the DSI algorithm for non-orthogonal grids, analyse the accuracy for EMPIC simulations on non-orthogonal grids, and present performance benchmarks of this code on a parallel supercomputer. While the hybrid particle push algorithm has a second-order accuracy in space, the accuracy of the DSI field solve algorithm is between first and second order for non-orthogonal grids. The parallel implementation of this code, which is almost identical to that of a Cartesian-grid EMPIC code using domain decomposition, achieved a high parallel efficiency of over 96% for large-scale simulations.

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12

Vay, J.-L., D. P. Grote, R. H. Cohen y A. Friedman. "Novel methods in the Particle-In-Cell accelerator Code-Framework Warp". Computational Science & Discovery 5, n.º 1 (26 de diciembre de 2012): 014019. http://dx.doi.org/10.1088/1749-4699/5/1/014019.

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13

Germaschewski, Kai, William Fox, Stephen Abbott, Narges Ahmadi, Kristofor Maynard, Liang Wang, Hartmut Ruhl y Amitava Bhattacharjee. "The Plasma Simulation Code: A modern particle-in-cell code with patch-based load-balancing". Journal of Computational Physics 318 (agosto de 2016): 305–26. http://dx.doi.org/10.1016/j.jcp.2016.05.013.

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14

Haggerty, Colby C. y Damiano Caprioli. "dHybridR: A Hybrid Particle-in-cell Code Including Relativistic Ion Dynamics". Astrophysical Journal 887, n.º 2 (18 de diciembre de 2019): 165. http://dx.doi.org/10.3847/1538-4357/ab58c8.

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15

Wolfheimer, Felix, Erion Gjonaj y Thomas Weiland. "A parallel 3D particle-in-cell code with dynamic load balancing". Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 558, n.º 1 (marzo de 2006): 202–4. http://dx.doi.org/10.1016/j.nima.2005.11.003.

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16

Gassama, Salimou, Éric Sonnendrücker, Kai Schneider, Marie Farge y Margarete O. Domingues. "Wavelet denoising for postprocessing of a 2D Particle - In - Cell code". ESAIM: Proceedings 16 (2007): 195–210. http://dx.doi.org/10.1051/proc:2007013.

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17

Hae Jin Kim, Jung Uk Shin y Jin Joo Choi. "Particle-in-cell code simulations on a rising-sun magnetron oscillator". IEEE Transactions on Plasma Science 30, n.º 3 (junio de 2002): 956–61. http://dx.doi.org/10.1109/tps.2002.801535.

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18

Deca, J., G. Lapenta, R. Marchand y S. Markidis. "Spacecraft charging analysis with the implicit particle-in-cell code iPic3D". Physics of Plasmas 20, n.º 10 (octubre de 2013): 102902. http://dx.doi.org/10.1063/1.4826951.

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19

Meierbachtol, Collin S., Daniil Svyatskiy, Gian Luca Delzanno, Louis J. Vernon y J. David Moulton. "An electrostatic Particle-In-Cell code on multi-block structured meshes". Journal of Computational Physics 350 (diciembre de 2017): 796–823. http://dx.doi.org/10.1016/j.jcp.2017.09.016.

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20

Sáez, Xavier, Alejandro Soba, Edilberto Sánchez, Ralf Kleiber, Francisco Castejón y José M. Cela. "Improvements of the particle-in-cell code EUTERPE for petascaling machines". Computer Physics Communications 182, n.º 9 (septiembre de 2011): 2047–51. http://dx.doi.org/10.1016/j.cpc.2010.12.038.

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21

Konstantinov, Alexander B. y Steven A. Orszag. "Extended Lagrangian particle-in-cell (ELPIC) code for inhomogeneous compressible flows". Journal of Scientific Computing 10, n.º 2 (junio de 1995): 191–231. http://dx.doi.org/10.1007/bf02089950.

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22

Markidis, S., G. Lapenta, W. B. VanderHeyden y Z. Budimli? "Implementation and performance of a particle-in-cell code written in Java". Concurrency and Computation: Practice and Experience 17, n.º 7-8 (2005): 821–37. http://dx.doi.org/10.1002/cpe.856.

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23

Joyce, Glenn, Jonathan Krall y Steven Slinker. "ELBA (electron beams in accelerators) particle simulation code". Laser and Particle Beams 12, n.º 2 (junio de 1994): 273–82. http://dx.doi.org/10.1017/s0263034600007734.

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ELBA is a three-dimensional, particle-in-cell, simulation code that has been developed to study the propagation and transport of relativistic charged particle beams. The code is particularly suited to the simulation of relativistic electron beams propagating through collisionless or slightly collisional plasmas or through external electric or magnetic fields. Particle motion is followed via a coordinate “window” in the laboratory frame that moves at the speed of light. This scheme allows us to model only the immediate vicinity of the beam. Because no information can move in the forward direction in these coordinates, particle and field data can be handled in a simple way that allows for very large scale simulations. A mapping scheme has been implemented that, with corrections to Maxwell's equations, allows the inclusion of bends in the simulation system.

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24

Wang, Bei, Stephane Ethier, William Tang, Khaled Z. Ibrahim, Kamesh Madduri, Samuel Williams y Leonid Oliker. "Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers". International Journal of High Performance Computing Applications 33, n.º 1 (29 de junio de 2017): 169–88. http://dx.doi.org/10.1177/1094342017712059.

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The gyrokinetic toroidal code at Princeton (GTC-P) is a highly scalable and portable particle-in-cell (PIC) code. It solves the 5-D Vlasov–Poisson equation featuring efficient utilization of modern parallel computer architectures at the petascale and beyond. Motivated by the goal of developing a modern code capable of dealing with the physics challenge of increasing problem size with sufficient resolution, new thread-level optimizations have been introduced as well as a key additional domain decomposition. GTC-P’s multiple levels of parallelism, including internode 2-D domain decomposition and particle decomposition, as well as intranode shared memory partition and vectorization, have enabled pushing the scalability of the PIC method to extreme computational scales. In this article, we describe the methods developed to build a highly parallelized PIC code across a broad range of supercomputer designs. This particularly includes implementations on heterogeneous systems using NVIDIA GPU accelerators and Intel Xeon Phi (MIC) coprocessors and performance comparisons with state-of-the-art homogeneous HPC systems such as Blue Gene/Q. New discovery science capabilities in the magnetic fusion energy application domain are enabled, including investigations of ion–temperature–gradient driven turbulence simulations with unprecedented spatial resolution and long temporal duration. Performance studies with realistic fusion experimental parameters are carried out on multiple supercomputing systems spanning a wide range of cache capacities, cache-sharing configurations, memory bandwidth, interconnects, and network topologies. These performance comparisons using a realistic discovery-science-capable domain application code provide valuable insights on optimization techniques across one of the broadest sets of current high-end computing platforms worldwide.

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25

Giffin, Gregory B., Daniel E. Hastings, Gabriel I. Font, Graeme B. Shaw y David L. Cooke. "Particle-in-Cell Code Analysis of Charging Hazards and Wake Studies Experiment". Journal of Spacecraft and Rockets 35, n.º 3 (mayo de 1998): 395–402. http://dx.doi.org/10.2514/2.3341.

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26

Shon, C. H., H. J. Lee y J. K. Lee. "Method to increase the simulation speed of particle-in-cell (PIC) code". Computer Physics Communications 141, n.º 3 (diciembre de 2001): 322–29. http://dx.doi.org/10.1016/s0010-4655(01)00417-9.

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27

Burau, Heiko, Renée Widera, Wolfgang Honig, Guido Juckeland, Alexander Debus, Thomas Kluge, Ulrich Schramm, Tomas E. Cowan, Roland Sauerbrey y Michael Bussmann. "PIConGPU: A Fully Relativistic Particle-in-Cell Code for a GPU Cluster". IEEE Transactions on Plasma Science 38, n.º 10 (octubre de 2010): 2831–39. http://dx.doi.org/10.1109/tps.2010.2064310.

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28

Barsamian, Yann, Sever A. Hirstoaga y Éric Violard. "Efficient data layouts for a three-dimensional electrostatic Particle-in-Cell code". Journal of Computational Science 27 (julio de 2018): 345–56. http://dx.doi.org/10.1016/j.jocs.2018.06.004.

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29

Plimpton, Steven J., David B. Seidel, Michael F. Pasik, Rebecca S. Coats y Gary R. Montry. "A load-balancing algorithm for a parallel electromagnetic particle-in-cell code". Computer Physics Communications 152, n.º 3 (mayo de 2003): 227–41. http://dx.doi.org/10.1016/s0010-4655(02)00795-6.

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30

Melzani, Mickaël, Christophe Winisdoerffer, Rolf Walder, Doris Folini, Jean M. Favre, Stefan Krastanov y Peter Messmer. "Apar-T: code, validation, and physical interpretation of particle-in-cell results". Astronomy & Astrophysics 558 (octubre de 2013): A133. http://dx.doi.org/10.1051/0004-6361/201321557.

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31

Copplestone, S. M., P. Ortwein, C. D. Munz, K. A. Avramidis y J. Jelonnek. "Simulation of gyrotrons using the high-order particle-in-cell code PICLas". EPJ Web of Conferences 149 (2017): 04019. http://dx.doi.org/10.1051/epjconf/201714904019.

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32

Delzanno, Gian Luca, Enrico Camporeale, J. David Moulton, Joseph E. Borovsky, Elizabeth A. MacDonald y Michelle F. Thomsen. "CPIC: A Curvilinear Particle-in-Cell Code for Plasma–Material Interaction Studies". IEEE Transactions on Plasma Science 41, n.º 12 (diciembre de 2013): 3577–87. http://dx.doi.org/10.1109/tps.2013.2290060.

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33

Lapenta, Giovanni. "DEMOCRITUS: An adaptive particle in cell (PIC) code for object-plasma interactions". Journal of Computational Physics 230, n.º 12 (junio de 2011): 4679–95. http://dx.doi.org/10.1016/j.jcp.2011.02.041.

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34

Tonge, J., D. E. Dauger y V. K. Decyk. "Two-dimensional semiclassical Particle-In-Cell code for simulation of quantum plasmas". Computer Physics Communications 164, n.º 1-3 (diciembre de 2004): 279–85. http://dx.doi.org/10.1016/j.cpc.2004.06.039.

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35

Idomura, Yasuhiro, Masato Ida, Shinji Tokuda y Laurent Villard. "New conservative gyrokinetic full-f Vlasov code and its comparison to gyrokinetic δf particle-in-cell code". Journal of Computational Physics 226, n.º 1 (septiembre de 2007): 244–62. http://dx.doi.org/10.1016/j.jcp.2007.04.013.

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36

Leboeuf, Jean-Noel G., Viktor K. Decyk, David E. Newman y Raul Sanchez. "Implementation of 2D Domain Decomposition in the UCAN Gyrokinetic Particle-in-Cell Code and Resulting Performance of UCAN2". Communications in Computational Physics 19, n.º 1 (enero de 2016): 205–25. http://dx.doi.org/10.4208/cicp.070115.030715a.

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AbstractThe massively parallel, nonlinear, three-dimensional (3D), toroidal, electrostatic, gyrokinetic, particle-in-cell (PIC), Cartesian geometry UCAN code, with particle ions and adiabatic electrons, has been successfully exercised to identify non-diffusive transport characteristics in present day tokamak discharges. The limitation in applying UCAN to larger scale discharges is the 1D domain decomposition in the toroidal (or z-) direction for massively parallel implementation using MPI which has restricted the calculations to a few hundred ion Larmor radii or gyroradii per plasma minor radius. To exceed these sizes, we have implemented 2D domain decomposition in UCAN with the addition of the y-direction to the processor mix. This has been facilitated by use of relevant components in the P2LIB library of field and particle management routines developed for UCLA's UPIC Framework of conventional PIC codes. The gyro-averaging specific to gyrokinetic codes is simplified by the use of replicated arrays for efficient charge accumulation and force deposition. The 2D domain-decomposed UCAN2 code reproduces the original 1D domain nonlinear results within round-off. Benchmarks of UCAN2 on the Cray XC30 Edison at NERSC demonstrate ideal scaling when problem size is increased along with processor number up to the largest power of 2 available, namely 131,072 processors. These particle weak scaling benchmarks also indicate that the 1 nanosecond per particle per time step and 1 TFlops barriers are easily broken by UCAN2 with 1 billion particles or more and 2000 or more processors.

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37

Petrov, George M. y Jack Davis. "Parallelization of an Implicit Algorithm for Multi-Dimensional Particle-in-Cell Simulations". Communications in Computational Physics 16, n.º 3 (septiembre de 2014): 599–611. http://dx.doi.org/10.4208/cicp.070813.280214a.

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AbstractThe implicit 2D3V particle-in-cell (PIC) code developed to study the interaction of ultrashort pulse lasers with matter [G. M. Petrov and J. Davis, Computer Phys. Comm. 179, 868 (2008); Phys. Plasmas 18, 073102 (2011)] has been parallelized using MPI (Message Passing Interface). The parallelization strategy is optimized for a small number of computer cores, up to about 64. Details on the algorithm implementation are given with emphasis on code optimization by overlapping computations with communications. Performance evaluation for 1D domain decomposition has been made on a small Linux cluster with 64 computer cores for two typical regimes of PIC operation: “particle dominated”, for which the bulk of the computation time is spent on pushing particles, and “field dominated”, for which computing the fields is prevalent. For a small number of computer cores, less than 32, the MPI implementation offers a significant numerical speed-up. In the “particle dominated” regime it is close to the maximum theoretical one, while in the “field dominated” regime it is about 75-80 % of the maximum speed-up. For a number of cores exceeding 32, performance degradation takes place as a result of the adopted 1D domain decomposition. The code parallelization will allow future implementation of atomic physics and extension to three dimensions.

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38

Moritaka, Toseo, Robert Hager, Michael Cole, Samuel Lazerson, Choong-Seock Chang, Seung-Hoe Ku, Seikichi Matsuoka, Shinsuke Satake y Seiji Ishiguro. "Development of a Gyrokinetic Particle-in-Cell Code for Whole-Volume Modeling of Stellarators". Plasma 2, n.º 2 (12 de mayo de 2019): 179–200. http://dx.doi.org/10.3390/plasma2020014.

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We present initial results in the development of a gyrokinetic particle-in-cell code for the whole-volume modeling of stellarators. This is achieved through two modifications to the X-point Gyrokinetic Code (XGC), originally developed for tokamaks. One is an extension to three-dimensional geometries with an interface to Variational Moments Equilibrium Code (VMEC) data. The other is a connection between core and edge regions that have quite different field-line structures. The VMEC equilibrium is smoothly extended to the edge region by using a virtual casing method. Non-axisymmetric triangular meshes in which triangle nodes follow magnetic field lines in the toroidal direction are generated for field calculation using a finite-element method in the entire region of the extended VMEC equilibrium. These schemes are validated by basic benchmark tests relevant to each part of the calculation cycle, that is, particle push, particle-mesh interpolation, and field solver in a magnetic field equilibrium of Large Helical Device including the edge region. The developed code also demonstrates collisionless damping of geodesic acoustic modes and steady states with residual zonal flow in the core region.

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39

Ibano, K., S. Togo, T. L. Lang, Y. Ogawa, H. T. Lee, Y. Ueda y T. Takizuka. "Simulations of Tungsten Re-deposition Using a Particle-In-Cell Code with Non-uniform Super Particle Sizes". Contributions to Plasma Physics 56, n.º 6-8 (24 de junio de 2016): 705–10. http://dx.doi.org/10.1002/ctpp.201610040.

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40

PUKHOV, A. "Three-dimensional electromagnetic relativistic particle-in-cell code VLPL (Virtual Laser Plasma Lab)". Journal of Plasma Physics 61, n.º 3 (abril de 1999): 425–33. http://dx.doi.org/10.1017/s0022377899007515.

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The three-dimensional particle-in-cell (PIC) code VLPL (Virtual Laser Plasma Lab) allows, for the first time, direct fully electromagnetic simulations of relativistic laser–plasma interactions. Physical results on relativistic self-focusing in under-dense plasma are presented. It is shown that background plasma electrons are accelerated to multi-MeV energies and 104 T magnetic fields are generated in the process of self-focusing at high laser intensities. This physics is crucial for the fast ignitor concept in inertial confinement fusion. Advances in the numerical PIC algorithm used in the code VLPL are reviewed here.

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41

Gallo, Giuseppe, Adriano Isoldi, Dario Del Gatto, Raffaele Savino, Amedeo Capozzoli, Claudio Curcio y Angelo Liseno. "Numerical Aspects of Particle-in-Cell Simulations for Plasma-Motion Modeling of Electric Thrusters". Aerospace 8, n.º 5 (15 de mayo de 2021): 138. http://dx.doi.org/10.3390/aerospace8050138.

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The present work is focused on a detailed description of an in-house, particle-in-cell code developed by the authors, whose main aim is to perform highly accurate plasma simulations on an off-the-shelf computing platform in a relatively short computational time, despite the large number of macro-particles employed in the computation. A smart strategy to set up the code is proposed, and in particular, the parallel calculation in GPU is explored as a possible solution for the reduction in computing time. An application on a Hall-effect thruster is shown to validate the PIC numerical model and to highlight the strengths of introducing highly accurate schemes for the electric field interpolation and the macroparticle trajectory integration in the time. A further application on a helicon double-layer thruster is presented, in which the particle-in-cell (PIC) code is used as a fast tool to analyze the performance of these specific electric motors.

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42

Shirkov, G., V. Alexandrov, V. Preisendorf, V. Shevtsov, A. Filippov, R. Komissarov, V. Mironov et al. "Particle-in-cell code library for numerical simulation of the ECR source plasma". Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 205 (mayo de 2003): 215–19. http://dx.doi.org/10.1016/s0168-583x(03)00938-8.

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43

Tuckmantel, Tobias, Alexander Pukhov, Jalo Liljo y Marlis Hochbruck. "Three-Dimensional Relativistic Particle-in-Cell Hybrid Code Based on an Exponential Integrator". IEEE Transactions on Plasma Science 38, n.º 9 (septiembre de 2010): 2383–89. http://dx.doi.org/10.1109/tps.2010.2056706.

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44

Sturtevant, Judy E., Phil M. Campbell y Arthur B. Maccabe. "Performance of a particle-in-cell plasma simulation code on the BBN TC2000". Concurrency: Practice and Experience 4, n.º 1 (febrero de 1992): 1–18. http://dx.doi.org/10.1002/cpe.4330040102.

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45

Shirkov, G., V. Alexandrov, V. Preisendorf, V. Shevtsov, A. Filippov, R. Komissarov, V. Mironov et al. "Particle-in-cell code library for numerical simulation of the ECR source plasma". Review of Scientific Instruments 73, n.º 2 (febrero de 2002): 644–46. http://dx.doi.org/10.1063/1.1430864.

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46

Zhao, L., B. Cluggish, J. S. Kim y E. G. Evstatiev. "A particle-in-cell Monte Carlo code for electron beam ion source simulation". Review of Scientific Instruments 83, n.º 2 (febrero de 2012): 02A508. http://dx.doi.org/10.1063/1.3672469.

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47

Kunz, Matthew W., James M. Stone y Xue-Ning Bai. "Pegasus: A new hybrid-kinetic particle-in-cell code for astrophysical plasma dynamics". Journal of Computational Physics 259 (febrero de 2014): 154–74. http://dx.doi.org/10.1016/j.jcp.2013.11.035.

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48

Meyers, M. D., C. K. Huang, Y. Zeng, S. A. Yi y B. J. Albright. "On the numerical dispersion of electromagnetic particle-in-cell code: Finite grid instability". Journal of Computational Physics 297 (septiembre de 2015): 565–83. http://dx.doi.org/10.1016/j.jcp.2015.05.037.

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49

Smith, Joseph R., Chris Orban, Nashad Rahman, Brendan McHugh, Ricky Oropeza y Enam A. Chowdhury. "A particle-in-cell code comparison for ion acceleration: EPOCH, LSP, and WarpX". Physics of Plasmas 28, n.º 7 (julio de 2021): 074505. http://dx.doi.org/10.1063/5.0053109.

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Wang, Hui Hui, Da Gang Liu, La Qun Liu y Lin Meng. "PIC/MCC Simulations for the Oxygen Microwave Breakdown at Atmospheric Conditions". Advanced Materials Research 981 (julio de 2014): 859–62. http://dx.doi.org/10.4028/www.scientific.net/amr.981.859.

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In this paper, the code of Particle-In-Cell/Monte Carlo Collision (PIC/MCC) for oxygen microwave breakdown is developed. This code is based on the three dimensional particle-in-cell platform CHIPIC, and with a module for increasing the charge of each super-particle. With this PIC/MCC code, the multiplication rate of the electron density and the delay time in oxygen breakdown at atmospheric conditions are researched. The results show: the multiplication rate of the electron density is periodic, and its period is the half of the electric field period; the breakdown delay time in the gas breakdown increases while the frequency of electric field or the gas pressure increases.

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