PIC Simulation Library

Introduction

libpic is a high-performance Particle-In-Cell (PIC) simulation framework implemented in Python. The core functionalities of libpic include electromagnetic field solvers, particle pushers, interpolators, and current depositors.

libpic serves as the backend for λPIC (will be released soon). Performance optimizations are achieved through the use of Numba JIT and Cython.

This project is under construction.

Project Roadmap

• Functionalities
  • Maxwell solver
  • Particle pusher
  • Interpolator
  • Current depositor
  • QED
    • Photon emission
    • Pair production
  • CPML boundary
  • Collision
  • Nuclear physics
• Replace Numba JIT and Cython with C extensions
  • Current depositor
  • Patch synchronizer
  • Maxwell solver
  • Particle pusher
    • unified pusher
  • Interpolator
  • sorter
  • PML
• Remove dependence on numba.typed.List
• MPI
• 3D
  • QED
• GPU acceleration
• Documentation

Installation

From PyPI:

pip install libpic

From source:

git clone https://github.com/xsgeng/libpic.git
pip install -e ./libpic

Core Classes

classDiagram
    Patches --> Patch : contains

    Patch --> ParticlesBase : contains
    Patch --> Fields : contains
    Patch --> PML : contains

    Patch <|-- Patch2D~Patch~
    Patch <|-- Patch3D~Patch~

    RadiationBase --> Patches : contains
    PairProductionBase --> Patches : contains
    CurrentDeposition --> Patches : contains
    PusherBase --> Patches : contains
    FieldInterpolation --> Patches : contains
    MaxwellSolver --> Patches : contains

    Pydantic.BaseModel <|-- Species
    Species <|-- XXX~Species~
    Species <|-- Electron~Species~
    Species --> ParticlesBase : creates

    class Patch {
        index: int
        *_neighbor_index: int
    }

    class Patches {
        sync_particles()
        sync_guard_fields()
        sync_currents()
    }

    class ParticlesBase {
        x,y,z ...: NDArray[float]
        is_dead: NDArray[bool]
    }

    class Fields {
        ex, ey, ...: NDArray[float]
    }

    class Species {
        name, q, m, ...
        density: Callable
    }

Acknowledgments

This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 12304384.

This project was inspired by and adapted elements from the EPOCH and the Smilei projects.