**Topic/Type**:
1. Plasma Simulation, Invited

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PIC-MCC (Particle In Cell with Monte Carlo Collisions) simulations of low temperature plasmas

**
M. M. Turner
**

*
School of Physical Sciences and National Centre for Plasma Science and Technology, Dublin City University, Ireland *

The particle-in-cell method is a classical approach to plasma simulation. Al-

though this technique ﬁrst appeared more than forty years ago, it remains the

preferred approach for many problems where a kinetic treatment is desired.

This is especially true in low-temperature plasma physics, where violently

non-Maxwellian electron energy distributions are common, often featuring

bumps, holes and other curious structures. Such complicated distribution

functions are typically formed by a subtle interplay between collisional effects

and non-local interactions with electric and magnetic ﬁelds. It is important to

get this right in a simulation, because the electron energy distribution func-

tion affects the ionization rate, transport processes, radiative processes, etc.

These parameters are of great importance in low-temperature plasma appli-

cations, which motivate much work in this ﬁeld. Consequently, one wants to

have a simulation method that in principle captures these effects accurately.

As a direct solution of the coupled system of the Boltzmann equation and

Maxwell?s equations, particle-in-cell simulation combined with Monte Carlo

collisions is such a method. This approach should capture the physics ac-

curately, provided that the numerical parameters are properly chosen. The

numerical parameters in question are three: the time step , the cell size

and the number of super-particles per cell, . The literature contains

various heuristics for choosing these parameters, and it is usually assumed

that these heuristics apply whether or not Monte Carlo collisions are em-

ployed. We will show here that this is not always so?Monte Carlo collisions

in fact change the kinetic properties of a particle-in-cell simulation, such that

the rate of numerical thermalisation may increase by orders of magnitude.

This is in turn means that numerical effects may distort the electron energy

distribution function (in particular) to a much greater extent than is often

realised. These effects means that new heuristics are needed, especially for

choosing the number of particles. We will discuss the implications of these

results.