Abstract
The description of plasma using fluid model is mostly insufficient and requires the consideration of velocity distribution which leads to kinetic theory. Kinetic theory of plasma describes and predicts the condition of plasma from microscopic interactions and motions of its constituents. It provides an essential basis for an introductory course on plasma physics as well as for advanced kinetic theory. Plasma kinetics deals with the relationship between velocity and forces and the study of continua in velocity space. Plasma kinetics mathematical equations provide aid to the readers in understanding simple tools to determine the plasma dynamics and kinetics as described in this chapter. Kinetic theory provides the basics and essential introduction to plasma physics and subsequently advanced kinetic theory. Plasma waves, oscillations, frequencies, and applications are the subjects of kinetic theory. In this chapter, mathematical formulations essential for exploring plasma kinetics are compiled and described simplistically along with a precise discussion on basic plasma parameters in simple language with illustrations in some cases.
Keywords
- plasma parameters
- kinetic theory
- particle distribution
1. Introduction
Plasma is the fourth state of matter, and it is defined as “a quasineutral gas of charged and neutral particles which exhibits collective behavior.” As plasma contains charged particles, these charged particles move around and generate local concentrations of positive or negative charges (collective behavior) which give rise to electric fields. Motion of these charges also generates currents and hence magnetic fields [1]. Therefore, the macroscopic forces acting in plasma are totally different from ordinary gasses and hence remarkable differences in their physical properties are observed. The salient features of the plasma can be understood by investigating the behavior of the electrons, by far the most mobile-charged particle in plasma [2]. Plasma physics deals with the equilibrium and non-equilibrium properties of a statistical system of charged particles. Microscopic degrees of freedom arising from the motion of individual particles describe the system. These statistics therefore theoretically treat the macroscopic behavior of such a system [3].
The knowledge of plasma parameters helps to understand the dynamics of plasma. Electrons being dominant mobile species play an important role in the behavior of the plasma. The most important of these parameters include plasma temperature, electron density, Debye shielding, and Debye length. Plasma is transient in nature. Therefore, the plasma is generally characterized on the basis of instantaneous observations. Charged particles, neutrals, and molecules coexist in plasma under various circumstances. Conditions in the plasma strongly depend on the distribution of charged particles, where electrons being lighter and highly mobile play a dominant role. Therefore, plasma is generally represented through parameters which are derived from the behavior of electrons in the plasma. When an external point charge is introduced or a localized unbalanced charge is formed in the plasma, readjustment of charge density occurs to neutralize the effect by shielding its electric field. The electrons being more mobile than heavier ions move toward or away from the unbalanced charge faster than ions. It gives rise to oscillations which are referred to as electron oscillations or plasma oscillations. The frequency at which these oscillations take place is called as plasma frequency [4]. This phenomenon of shielding or screening a foreign charge or an unbalanced charge inside the plasma is known as Debye shielding or sometimes referred to as Debye screening. It is specific for plasma. Charges keep accumulating around the foreign or unbalanced charge until the static electric field of the unbalanced charge is screened and the balance is restored. A sphere of charges that is created around the unbalanced charge is called as Debye sphere and its radius is known as Debye length. A detailed discussion on two of the most important plasma parameters electron density and plasma temperature is provided in Sections 2.7 and 2.8.
Comprehensive mathematical details on certain aspects of plasma are found in published literature. The authors aim to provide readers with an overall view of fundamental mathematical relations explaining the kinetics of plasma that are compiled simplistically in one chapter. This can be an easy reference for the researchers interested in plasma kinetics.
2. Plasma kinetic equations
Plasma physics involves phenomena that are related to dynamical processes in statistical mechanics. It is thus very significant to study the properties and structure of the basic kinetic equations governing the dynamical behavior of plasma [5]. The dynamical behavior of a system of N-interacting particles is generally investigated using the Liouville equation. A microscopic distribution function could be used to describe the behavior of such a system. A six-dimensional phase-space distribution function called “Klimontovich distribution function,” which obeys a continuity equation in the phase space, is defined. The system of charged particles can then be described by Bogoliubov-Born-Green-Kirkwood-Yvon (BBGKY) hierarchy equations.
2.1. Klimontovich equation
To further formalize the kinetic theory, we introduce Klimontovich’s microscopic description and derivation of the Bogoliubov-Born-Green-Kirkwood-Yvon equations [6]. To introduce the Klimontovich equation, we consider a classical system containing N identical particles in a box of volume V; n ≡ N/V denoting the average number density. Each particle in the box is characterized by an electric charge q and mass m.
In the six-dimensional phase space consisting of the position r and velocity v, each of the particle has its own trajectory; for ith particle,
The microscopic density of the particles in the phase space may be expressed by the summation of the six-dimensional delta functions as
where X ≡ (r, v). N(X; t) is known as the Klimontovich distribution function which satisfies the continuity equation in the phase space,
In phase-space coordinates, Eq. (3) can be written as
where
The electromagnetic acceleration is very important in plasma physics,
The electric and magnetic fields E(r, t) and B(r, t) consist of two separate contributions: those applied from the external sources and those produced from the microscopic fine-grained distribution of the charged particles.
The microscopic fine-grained fields e(r, t) and b(r, t) are determined from a solution of Maxwell equations,
For a given N(X; t), the solution to these set of equations can generally be written; the solution, when substituted in Eq. (5), would amount to taking account of both electromagnetic and electrostatic interactions between the particles. The electromagnetic interactions are usually negligible as compared with the electrostatic interactions for a nonrelativistic plasma; hence, the microscopic fields become.
Substituting Eq. (8) into Eq. (6), we get an expression for the acceleration in terms of N(X; t). Eq. (3) can be written with the aid of such an expression as
L(X), as a single particle operator is defined by
And V(X, X’) is a two-particle operator arising from the Coulomb interaction defined by
Eq. (9) is known as Klimontovich equation. The equation describes the space–time evolution of the microscopic distribution function.
2.2. Liouville distribution
The fine-grained distribution function, which is precise in describing the microscopic conditions of many particles, would not by itself correspond to the coarse-grained quantities in the macroscopic view. There is a need to introduce an averaging process based on the Liouville distribution over the 6 N–dimensional phase space to establish a connection between them.
In T-space, the microscopic state of the system is expressed by a point.
{Xi} ≡ (X1, X2, ……., Xn), called a system point.
By following a normal procedure of the ensemble theory in statistical mechanics, it can assume N replicas which are microscopically identical to the system under consideration. N can be chosen to be very large so that it can approach infinity when it requires. These N replicas are characterized by different microscopic configurations; the system points are scattered over the T-space. Liouville distribution function [7] can then be defined as D({Xi}; t) in the T-space as
which by definition satisfies the normalization condition.
The N system points distributed in the T-space do not interact with each other, behaving like an ideal gas. The distribution function D({Xi}; t) therefore satisfies a Liouville-type continuity equation
The distribution is conserved along a trajectory in the phase-space distribution.
We can now perform a statistical averaging of a fine-grained quantity A(X, X ’ , ……; {Xi(t)} defined at a set of points (X, X’, …) in the six-dimensional phase space. With the aid of Liouville distribution, we follow this way:
With respect to the conservation property, this average can be transformed equivalently into an average over the initial distribution, such that
where {Xi(0)}; t)} represents the coordinates of the system points in T-space at t under the condition that it is located at {Xi(0)} when t = 0.
2.3. BBGKY hierarchy
The distribution functions can be obtained through a statistical average of products of Klimontovich functions. A shorthand notation and numerals 1, 2, 3……, etc., in place of X, X’, X′′……., etc., can be used to simplify the presentations.
The Klimontovich Eq. (9) can therefore be written as
The Liouville average of this equation can be obtained by using the methods in Eq. (16). The averaging process commutes with differential operators involved in Eq. (17). Now, with the aid of a single-particle distribution function
The average of the second term defines the two-particle distribution function:
For an arbitrary function y(1, 2, …; t), it can be proved from symmetry considerations that
Consequently,
It can start from an equation as well
Eq. (23) can be derived from a combination of Klimontovich equations. After averaging this equation with respect to the Liouville distribution and Eqs. (16) and (17), an equation involving f1, f2, and f2 can be obtained. This equation can then be simplified with the aid of Eqs. (21) and (22), the result yields
Similarly, it is considered that a Klimontovich equation for a product of an arbitrary number of the Klimontovich functions performs a statistical average of the equation. We therefore obtain the BBGKY hierarchy equations expressed as
The set of equations in Eq. (25) is the basis for the kinetic theory of plasmas.
2.4. Vlasov’s equation
For identical non-interacting particles, Liouville’s equation can be written in T-space. Introducing two properties of identical non-interacting particles such as the distribution function f and the Hamiltonian function q simplifies the problem. The distribution function written as a function of 6N variables and time factorizes to a product of N functions, each involving only the coordinates and momenta of one particle, and time.
The Hamiltonian function of N non-interacting particles is the sum of N terms, each involving only the coordinates and momenta of one particle. For identical particles, the terms of the Hamiltonian are also identical. For weakly or occasionally interacting particles, the decomposition of f into a product of factors and of q into a sum of terms is identical.
For a collection of N identical interacting particles, Liouville’s theorem can be written in the μ-space as
The right-hand side of Eq. (26) can be evaluated using the exact form of the interaction terms in the 6N + 1 Hamiltonian function variable. It is assumed that the Hamiltonian expression involves no magnetic terms. Under such conditions, p = Mv. If the coordinate system in the μ-space is changed from x, y, z, px, py, pz to x, y, z, vx, vy, vz, then the corresponding volume elements will be in the ratio M3. Hence, if the figurative points density in the (r, p) space is constant according to Eq. (26),
If magnetic terms are included in the Hamiltonian function, then p = Mv + qA. When the coordinates are changed, the ratio of the corresponding volume elements can be calculated by using Jacobian. The Jacobian is a determinant calculated by taking the partial derivative of any coordinate of one system with respect to all the coordinates of the second system. For instance, in the physical space, the Jacobian is
The value of the determinant is equal to the ratio of the corresponding volume elements. The ratio of the volume elements, M3, is constant even in the presence of magnetic forces.
where i, j, and k are the unit vectors in the vx, vy, and vz directions, respectively. In a vectorial form, Eq. (27) now becomes
Eq. (29) is known as Vlasov’s equation. F is the sum of the electric, magnetic, and gravitational forces resulting from external fields and the macroscopic forces resulting from the plasma itself. If we consider the viscous-like forces, Vlasov’s equation becomes
2.5. Maxwell’s equations
Maxwell’s equations express the relations between electric and magnetic fields in a medium. Consider a current I flowing in an element of length dl. The magnetic flux density dB produced by this current at a point P, a distance r from the element, and making an angle θ with its axis is known as Ampere’s law
where K is a constant of proportionality defined as
where μ = permeability of the medium. For vacuum, μ = μ0 = 4π ⨯ 10−7 H/m. The total magnetic flux density B produced at point P by the current flowing in a long conductor is
For infinite and linear conductor,

Figure 1.
Flux density near a straight wire in which current I flows where sinθdl = rdθ and r0 = r sin θ.
Figure 1. Flux density near a straight wire in which current I flows where sinθdl = rdθ and r0 = r sin θ.
If B is integrated around the path that encloses the wire, then
A magnetic field vector H is introduced to make the equation independent of the medium. It is such that
Introducing Eq. (35) into Eq. (34) and the current I by the surface integral of the conduction current density J over the area described by the path of integration of H,
The total current density = conduction current density σE; σ = conductivity of the wire and E = electric field. ∂D/∂t = displacement current density; D = electric flux density. Applying Stokes’ theorem, Eq. (36) can now be written in a general form as
According to Faraday’s law, the total e.m.f (V) induced in a closed loop as a function of the total flux Φm/dt producing the e.m.f is given as.
If the total flux linkage Φt is nΦm, then V = −dΦt/dt. The total flux through the circuit is equal to the integral of B over the area bounded by the circuit. Therefore,
The change in magnetic field produces an electric field E, thus
Combining Eqs. (39) and (40), the induced e.m.f is
Applying Stokes’ theorem on Eq. (41),
Gauss’ law states that the surface integral of the normal component of the electric flux density D over any closed surface equals the total enclosed charge q [8]. D is proportional to the electric field with permittivity ɛ of the medium as the constant of proportionality (D ∝ ɛE). ɛ = ɛ0 in free space.
Replacing q with the integral of the charge density ɐe over the volume enclosed by the surface S, the vectorial form
For magnetic field, the integral of B over a closed surface is always equal to zero, thus
Eqs. (37) and (42)–(44) are known as Maxwell’s equations. The equations are satisfied in all plasma physics phenomena.
2.6. Liouville’s theorem
In relation with the Boltzmann approach, most of the problems of statistical mechanics are best studied in multidimensional spaces called “phase spaces.” Consider a μ-space, which is a six-dimensional and makes use of coordinates and the three components of momentum x, y, z, px, py, pz or any set of Lagrangian coordinates for a point together with the associated generalized momenta. In this space, each plasma particle is represented by a point. If only one degree of freedom exists, the μ-space can be represented on a plane of Figure 2.

Figure 2.
Trajectory of an oscillating point in the μ-space.
Figure 2. Trajectory of an oscillating point in the μ-space.
In the μ-space, the distribution function f is a function of seven variables. Thus, the probability of finding a particle in a given volume element depends only on the coordinates and momenta of this particle, not on those of the other particles. This is a simplified version of Liouville’s theorem for a large number of non-interacting particles.
In the six-dimensional μ-space, the particles are conservative just as they are in the ordinary space. Hence, the conservation theorem may be applied in the phase space,
where ∇6 = six-dimensional divergence and v6 is a six-dimensional velocity vector whose components are exact time derivatives of the six coordinates of the μ-space. We now write ∇ temporarily x1, x2, x3 instead of x, y, z,
or
Hamilton’s canonical equations yield
where q = Hamiltonian. Eq. (47) now becomes
Eq. (49) is known as Liouville’s equation.
2.7. Boltzmann’s equation
The Boltzmann equation provides the statistical analysis of all the individual positions and momenta of each particle in the fluid (macro-system) at an instant, that is, number of particles in a particular level and their distribution among different levels [9]. It gives relative number of atoms in different excitation states as a function of temperature and refers to certain number of atoms or ions in a particular excitation state with respect to the ground state. Boltzmann equation gives a mathematical description of the state of a system and how it changes. It describes a quantity called the distribution function, f, which depends on a position, velocity, and the time. The function f determines the average number of particles having velocities within a small range from ν to ν + Δν and coordinates within a small range from r to r + Δr in time Δt.
In a hot dense gas, the atoms constantly experience collisions with each other, which lead to excitation to the different possible energy levels. The collisional excitation follows radiative de-excitation in timescales of the order of nanoseconds. For a constant temperature and pressure, a dynamic equilibrium is established between collisional excitations and radiative de-excitations, which lead to particular distribution of the atoms among different energy levels. Most of the atoms are at low-lying levels. The number of atoms at higher levels decreases exponentially with energy level. At low temperature, the faster the population drops at the higher levels. Only at very high temperatures, high-lying energy levels are occupied by an appreciable number of atoms. Boltzmann’s equation gives the distribution of the atoms among the various energy levels as a function of energy and temperature.
Let us consider a system at local thermal equilibrium (LTE) with a constant volume consisting of “N” atoms and each of atoms has “m” possible energy levels. Suppose there are “Nj” atoms in energy level “Ej.” The total number N of atoms is given as
The total energy “E” of the system can be written as
A number of ways in which “N1” atoms from total atoms “N” can occupy the first level are
By solving the above binomial
Taking log on both sides of Eq. (53),
By applying Stirling’s approximations to the factorials of all variables,
Let us maximize the lnX with respect to one microstate “Nj,” in a manner that is consistent with constrains of Eqs. (50) and (51). Lagrangian multiplier for the most probable occupation of the jth level is given as
where μ and λ are Lagrangian’s multipliers.
By adding values from Eqs. (50), (51), and (56) in Eq. (58),
On operating differential,
In general form by multiplying both sides by “Nj”, Eq. (60) can be written as
The change in the internal energy of the system in terms of thermodynamics equation can be written as
where “T” is the temperature, “P” is the pressure, and “S” is the entropy of the system.
The change in the internal energy at a constant volume is given as
Boltzmann’s equation for entropy is
Differentiate with respect to the total energy at a constant volume
By comparing Eqs. (70) and (74)
By adding value of “μ” in Eq. (64)
To calculate the value of “C”, let us change the subscript “j” to “i” for Eq. (77) and take summation from “1” to “m”.
and
Thus, Eq. (64) can be written as
In a system, most of the energy levels in an atom are degenerated, that is, atoms have several states with the same energy. To find out the population of an atom at a particular level, the population of each constituent state is required to be added together. Thus, each term in Eq. (81) must be multiplied by the statistical weight (degeneracy) “ϖ” of the level
The term “
and the number of atoms in level 2 relative to level 1, where level 2 is higher than level 1
The Einstein A coefficient gives the probability of spontaneous emission. A quantum of radiation is emitted by an atom when it de-excites from an excited level to a lower level, which is given as
where “ν” is the frequency of emitted radiation and “ΔE = E2-E1” is the energy difference between two atomic states (or level) “E2” higher level and “E1” lower level.
Suppose the number of downward transitions per unit time is merely proportional to the number of atoms “N2” at a higher state, then, the number of transition per unit time is given as
where “A21” is proportionality constant known as Einstein coefficient for spontaneous emission for transition from level “E2” to level “E1”.
As “A21N2” is the downward transition per unit time from “E2” to “E1”, thus the rate of emission of energy from these “N2”, that is, radiant power or flux, is given as
Here, “ν21” represents the frequency of radiation due to transition from level “E2” to level “E1”. As the radiation is emitted isotropically, thus the intensity is
2.7.2. Intensity ratio method
Consider two different emission lines from level i → j and m → n, where i and m are higher energy levels, j and n are lower energy levels. By using Eq. (92),
Taking ratio of Eqs. (94) and (95) and solving for temperature “T”,
2.8. Saha equation
The Boltzmann equation gives only the relative number of atoms or ions in a particular excitation state with respect to the ground state and it does not provide the total number of atoms that have been ionized. In order to determine the total abundance of a given element, it is necessary to know how the atoms are distributed among their several ionization stages. To quantify the number of atoms/ions in different ionization states, Saha’s equation is used which gives an expression for the total number of ions in an ionization state relative to lower ionization state.
For a system at local thermal equilibrium with a constant volume, the Boltzmann equation for the number of ions “Ni” relative to atoms/ions “Ni1” in the ground state of ionization state “i” can be written as (by using Eq. (85))
Taking the sum of all the excited states “j” of ionization state “i”, Eq. (98) can be written as
where
The ionization potential of the ion “i” can be defined as
Thus, we can write
Eq. (101) will become
where
There are two possible distinguishable electron states within phase space of
If the distribution of electron momenta is isotropic, then
If “ne” is the number density of electron, then the differential volume per electron will be
Thus, Eq. (108) can be written as
We can write the integral in Eq. (106) as
The integral can be transformed into an integral over variable “z” such that
By replacing values of Pe and dPe in Eq. (112)
The integral on the right-hand side of Eq. (116) is the Gamma function of the argument 3/2, which is
From Eqs. (106) and (118),
By dividing Eqs. (100) and (119),
For a particular state,
Eq. (90) can be written as
From Eqs. (124)–(126),
3. Summary
Kinetic theory provides the essential material for an introductory course on plasma physics as well as the basis for advanced kinetic theory. It offers a wide-range coverage of the field. Plasma kinetics deals with the relationship between velocity and forces and the study of continua in velocity space. The understanding of the most important plasma parameters, that is, plasma oscillations, plasma frequency, Debye shielding, Debye length, plasma temperature, and electron density, is important for studying plasmas. Kinetic theory has a wide scope. Plasma kinetics mathematical equations that will aid the readers in understanding simple techniques on how to investigate plasma dynamics and kinetics are discussed in this chapter. Kinetic theory provides the basics and essential introduction to plasma physics and subsequently advanced kinetic theory. Plasma understanding, waves, oscillations, frequencies, and applications are covered in kinetic theory. In fact, we have attempted to present a precise discussion of plasma kinetic theory which includes the basic plasma parameters mathematical formulation for an easy understanding to the reader.