Boltzmann’s Kinetic Theory
Boltzmann’s Kinetic Theory
Abstract and Keywords
Kinetic theory is the branch of statistical physics dealing with the dynamics of non-equilibrium processes and their relaxation to thermodynamic equilibrium. Established by Ludwig Boltzmann (1844–1906) in 1872, his eponymous equation stands as its mathematical cornerstone. Originally developed in the framework of dilute gas systems, the Boltzmann equation has spread its wings across many areas of modern statistical physics, including electron transport in semiconductors, neutron transport, quantum-relativistic fluids in condensed matter and even subnuclear plasmas. In this Chapter, a basic introduction to the Boltzmann equation in the context of classical statistical mechanics shall be provided.
I am conscious of being only an individual struggling weakly against the stream of time. But it still remains in my power to contribute in such a way that, when the theory of gases is again revived, not too much will have to be rediscovered.
2.1 Atomistic Dynamics
Let us consider a collection of N molecules moving in a box of volume V at temperature T and mutually interacting via a two-body intermolecular potential , being the intermolecular separation between two generic molecules.2
If the linear size s of the molecules, basically the effective range of the short-range interaction potential, is much smaller than their mean-interparticle separation , (p.18) the molecules can, to a good approximation, be treated like point-like structureless particles.
To the extent where the De Broglie length of these particles is much smaller than any other relevant length scale, their dynamics is governed by the classical Newton’s equations:
where is the position coordinate of the i-th particle, its velocity and is the force experienced by the i-th particle as a result of intermolecular interactions and possibly external fields (gravity, electric field, etc.).
Upon specifying initial and boundary conditions, equations (27.50) can in principle be solved in time, to yield a fully exhaustive knowledge of the state of the system, namely a set of functions of time .
This programme is totally unviable and, fortunately, needless as well. Unviability stems from two main reasons: first, N is generally of the order of the Avogadro number , far too big for any foreseeable computer. Second, even if one could store it, tracking so much information for sufficiently long times would be utopia, since any tiny uncertainity on the initial conditions would blow up in the long run because of dynamical instability of phase space. By dynamical instability, we refer to the fact that any uncertainity δ0 on the initial positions and/or momenta grows exponentially in time as . The coefficient λ, known as Lyapunov exponent, is a measure of the temporal horizon of deterministic behavior of the N-body system, in that at times greater than λ−1, the growth of uncertainity is such to prevent any deterministic prediction of the state of the system. It is estimated that a centimeter cube of Argon in standard conditions (300 K, 1 Atm) produces as much as 1029 digits of information per second. This means that in order to keep an exact record of the state of the system over a 1s lifespan, we need a number with nothing less than 1029 digits. Fortunately, we manage to survive with less than that, reason being that we are much larger than the molecules our body is made of !
The physical observables we are interested in, say the fluid pressure, temperature, visible flow originate from a statistical average over a large number of individual molecular histories.
A rigorous definition of what is meant by statistical average is not trivial, but here we shall be content with the intuitive notion of spatial average over a thermodynamic volume, namely a region of space sufficiently small with respect to the global dimensions of the macroscopic domain, and yet large enough to contain a statistically meaningful sample of molecules.
Typical numbers help getting the picture. The density of air in standard conditions is about molecules/m3 (known as as Loschmidt number). Hence, a centimeter cube of air contains about molecules, corresponding to a statistical error of less than one part per billion.
Given the very huge numbers involved, it appears therefore wise to approach the collective behavior of the ensemble of molecules from a statistical point of view.
This can be done at various levels of complexity, but, for a start, we shall begin with the simplest one: the single-particle kinetic level.
The chief question of single-particle kinetic theory is: What is the probability of finding a molecule around position at time t with velocity ?
Let the probability density, more often simply denoted as distribution function.
The quantity represents the mean number of molecules in a finite volume , centered about in the so-called single-particle phase space:
Integration upon the velocity degrees of freedom delivers the number of particles per unit volume, i.e., the number density of the system at any given time t:
which recovers the continuum density in the limit .
As a result, integration upon the entire phase space delivers the total number of molecules in the system at any given time t,
The distribution function is the pivotal object of Boltzmann’s kinetic theory.
In 1872, Ludwig Boltzmann (1844–1906) was able to derive an equation describing the evolution of in terms of the underlying microdynamic interactions. This is the celebrated Boltzmann equation (BE), one of the greatest achievements of theoretical physics of the nineteenth century (1).
The BE represents the first quantitative effort to attack the grand-issue of why time goes “one-way only” on a macroscopic scale while the underlying microdynamics is apparently perfectly reversible.3 In this book, we shall not be much concerned with fundamental issues, but rather keep the focus on the BE as a mathematical tool to investigate, analytically or numerically, the properties of fluid flows far from equilibrium.
(p.20) The kinetic equation for the one-body distribution function in the presence of an external force reads as follows (2):
where is the particle acceleration due to external and internal forces.
The left-hand side represents the streaming of the molecules along the trajectories associated with the force field (straight lines if ) and C12 represents the effects of intermolecular (two-body) collisions taking molecules in/out the streaming trajectory.
Let us comment on the two sides separately.
Once it is accepted that the cloud of N molecules moves like a lump of fluid in phase space Γ1, the streaming term reduces to a mere mirror of Newtonian mechanics.
To convince oneself, simply rewrite the streaming term as a Lagrangian derivative along the trajectory ,
Using Newton’s equations, , , this returns precisely the left-hand side of the Boltzmann equation. The streaming term carries the information contained in the distribution function untouched from place to place in phase-space.
Indeed, the solution of the collisionless Boltzmann equation , with initial conditions , is simply
where and is the solution of the Newton’s equations with initial conditions and . The key physical point is the following: the streaming term moves the distribution function in phase space with no loss of information, hence no loss of memory of the initial conditions: reversible motion.
2.3 The Born–Bogoliubov–Green–Kirkwood–Yvon (BBGKY) Hierarchy
The right-hand side of the BE, on the other hand, takes care of exchanging information across different trajectories, through intermolecular interactions.
The collision operator encodes two-body collisions, between, say molecule one, sitting at point with speed and molecule two, sitting at with speed , both at time t.
Formally, this information is stored in the two-body distribution function
(p.21) expressing the joint probability of finding molecule one around with speed and molecule two at with speed , both at time t (see Fig. 2.1).
More precisely, the quantity
gives the average number of pairs of molecules sitting at points and of phase space at time t.
Living as it does in a -dimensional phase space (13 with time), it goes without saying that f12 is a very heavy-duty object to work with.
The one-body distribution is recovered by integrating over the second particle phase-space coordinates:
where the factor 2 accounts for the fact that there are symmetric pairs out of a pool of N particles.
Clearly, this projection from 13 to 7 dimensions erases a huge amount of information, the two-body correlations. The loss of this information prevents an exact reconstruction of f12 from and , separately.
However, as we shall see shortly, educated guesses on the physical nature of the system under consideration, can (partially) make up for this fundamental limitation. In principle, it is not difficult to write down the dynamic equation for f12, the only trouble being that this equation calls into play the three-body distribution function f123, which in turn depends on f1234 and so on, down an endless line known as the BBGKY hierarchy, after Bogoliubov, Born, Green, Kirkwood and Yvon (4).
The physical origin of such open structure is that a N-body system can in principle host molecular collisions at all orders, from binary onward up to order N. If one could solve the BBGKY hierarchy, one would obtain a complete statistical knowledge of the full N-body problem described by the Newtonian equations for the N molecules. This is again utopia, only in statistical rather than dynamic vests!
Consequently, one must settle for less ambitious goals, i.e., approximate descriptions. The loss of information inevitably associated with such approximations is responsible for irreversibility, to be literally intended as our inability to reconstruct the initial conditions exactly (loss of memory).
Indeed, in actual practice, the probability of a simultaneous interaction between, say, k molecules, decays very fast with k, approximately like , where
is the mean-intermolecular separation and n is the number density, the two being related via , i.e., one particle on average in a cublet of volume d3.
sometimes called “granularity,” provides a direct measure of the degree of diluteness of the system. Indeed, in a system at density n, each molecule inhabits a volume d3, and is the fraction of that volume occupied by the molecule itself (here a cublet of side s).
From its very definition, it is clear that controls the strength of many-body interactions, which fade away as . For instance, air at standard conditions features , so that many-body interactions are largely negligible. Water in standard conditions, on the other hand, provides , which surely calls for careful consideration of many-body effects. Nevertheless, as we shall see in Chapter 3, the structure of the Navier–Stokes equations of continuum fluid dynamics is to a large extent independent of many-body effects. This is a great gift of mother nature, known as Universality.
2.4 Back to Boltzmann
The simple, yet basic, considerations previously suggested, set the stage for Boltzmann’s clever way out of the BBGKY hierarchy.
To close equation (2.2), Boltzmann made a few stringent assumptions on the nature of the physical system: a dilute gas of point-like, structureless molecules interacting via a short-range two-body potential.
Under such conditions, intermolecular interactions can be described solely in terms of localized binary collisions, with molecules spending most of their lifespan on free trajectories (in the absence of external fields), merrily unaware of each other.
Within this picture, the collision term splits into Loss and Gain components:
corresponding to direct(inverse) collisions taking molecules out(in) the volume element respectively (see Fig. 2.2).
The right-hand side requires a number of detailed comments.
First, the shorthand f12 stands for .
In the above, vr is the magnitude of the relative speed between particle 1 and particle 2 and denotes the solid angle associated with the scattering event (see Fig. 2.3). The (p.23) symbol σ denotes the differential cross section, i.e. the effective area presented by a particle in the plane across its center and perpendicular to the relative velocity.
Likewise, stands for , where prime indicates the molecular positions and velocities after a direct collision.
These two factors are purely statistical in nature. Note that all four spatial coordinates, both pre- and post-collisional, lie within a sphere of radius , on account of the diluteness assumption. Therefore, in the Boltzmann limit , they can be reconduced to the same spatial location .
This is a major simplification of the Boltzmann equation, with far-reaching consequences on theoretical as well as computational aspects.
The pre- and post-collisional velocities and are related through the three basic Mass–Momentum–Energy conservation laws, that is
Since mass can be assumed invariant across a collision, and , the first equation is basically a statement of number conservation, , two molecules before collisions, two molecules after.
The other two conservation laws, however, deliver a great deal of information, as we shall see in the sequel.
2.4.1 Two-Body Scattering
The two-body collision problem is best treated as the scattering of a single particle of reduced mass mr impinging on a target particle of mass , sitting at the median position , with median velocity , defined as follows:
The reduced mass is given by
The two-body scattering problem is best treated in a frame with the origin located at .
Using a polar representation for the interparticle separation
the total energy writes as
is the angular momentum and V(r) the interparticle potential.
After noting that mass-momentum conservation yields
it is readily appreciated that energy conservation implies that the relative velocity vector
is conserved in magnitude.
As a result, the only effect of the collision is to rotate the relative velocity by an angle χ in the scattering plane defined by and .
The kinematic identity , , , delivers the following mapping between post- and pre-collisional velocities:
It can be checked that this one-to-one mapping preserves the volume element in velocity space, i.e.,
a property which shall prove very useful in the sequel.
With the two-body kinematics in place, one can compute the number of molecules, dN, scattered around the solid angle , where α fixes the orientation of the scattering plane in three-dimensional space.
defines the so-called differential cross section σ.
The next task is to compute the scattering angle as a function of the impact parameter and the relative velocity (see Fig. 2.3).
To this purpose, let us consider all impinging particles sitting in the annulus of radius b and thickness db. The conservation of the number of these particles implies, namely:
This reveals that the differential cross section is fixed by the functional relation , which in turn depends on the details of the scattering potential V(r).
A quantity of major interest is the cross section:
and its integral version:
also known as total cross section. Note that , as defined above, is generally a function of the temperature T, so that one can write
s being the size of the molecule, identified with the range of the potential. For short-range potentials one can assume further assume , i.e., the effective cross section does not differ drastically from the geometrical one.
(p.26) The total cross section defines the molecular mean-free path (see Fig. 2.4):
and the associated collisional timescale
is the thermal speed.
The mean-free path is the mean distance traveled by a molecule before colliding with another molecule and represents the pivotal lengthscale of kinetic theory and transport phenomena.
2.4.2 Spatial Ordering in Dilute Gases
indicating that by construction, the so-called collisional cylinder of volume contains just a single colliding molecule.
Recalling the definition of the mean-interparticle distance, , the previous section yields
Based on the relation (2.20) with , one further obtains
It is of interest to note that the proper meaning of “dilute gas” in the Boltzmann framework does not correspond at all to a gas in the ordinary sense, i.e., a fluid of vanishingly small density. Quite on the contrary, the proper limit is the one where density is formally sent to infinity! The point is that, at the same time, the size s is sent to zero, in such a way as to keep the product constant. In other words, size goes to zero, density goes to infinity and the mean-free path is left constant. Putting all together, the mean-intermolecular distance scales like while the molecular size scales like , so that the diluteness parameter scales like and goes to zero in the limit , (see Fig. 2.5).
Summarizing, the dilute gas limit corresponds to the following limiting scenario:
This further witnesses the crucial role of the mean-free path as the fundamental length scale of Boltzmann kinetic theory and shows that is the appropriate smallness parameter describing many-body effects in dense gases and liquids. We shall return to these matters in Chapter 7 devoted to the kinetic theory of dense fluids.
2.4.3 Two-Body Scattering Problem
To sort out the explicit dependence , one needs to solve the two-body scattering problem. To this aim, it proves expedient to move to polar coordinates in the scattering plane.
The equations of motion resulting from conservation of energy E and angular momentum J read as follows:
where the right-hand side corresponds to the limit .
Dividing the two, one obtains
is the ratio of potential to kinetic energy in the rest frame.
For purely repulsive potentials, there exists a minimum-approach distance, rmin defined by the condition .
Some algebra delivers the implicit relation:
Note that for repulsive potentials, , , while the opposite is true for attractive ones.
Integrating upon r from rmin to infinity, one obtains
which is known as the apse angle.
The scattering angle is finally derived as
This procedure shows that the dependence of the scattering angle on the potentials is generally pretty involved. As a general rule, however, small-impact parameters correspond to large scattering angles.
2.4.4 Distinguished Potentials
Once the atomistic potential is known, the procedure already outlined permits us to compute the scattering differential cross section σ, hence the collisional relaxation time and the mean-free path, starting from the atomistic potentials. This accomplishes the fundamental task of transferring information from the atomistic world of trajectories and intermolecular potentials to the kinetic world of statistical distributions, scattering cross sections and mean-free path.
Symbolically, the kinetic micro-meso bridge reads as follows:
Given that some specific potentials stand out for their importance, either from the mathematical point of view or for their applicability to realistic fluids, in the sequel we provide a cursory coverage of such potentials.
A particularly important and analytically solvable case is provided by the hard-sphere potential,
where R is the sphere radius (see Fig 2.6).
Detailed calculations yield , i.e., the geometrical area of the particle cross section, as it should be.
Despite their simplicity hard-sphere potentials have played a major role in the kinetic theory of fluids and continue to provide valuable information for molecular dynamics simulations with hard-core repulsive interactions.
18.104.22.168 Lennard-Jones potential
Another potential which plays a prominent role in the physics of non-ideal fluids, is the so-called 12–6 Lennard-Jones potential, after the British physicist John Edward Lennard-Jones (1894–1954):
This potential consists of a hard-core repulsion (-12 branch), plus soft-core attraction (-6 branch) (see Fig. 2.7). The former stems for the strong repulsion between incipient overlap of electronic orbitals, when nuclei get seriously close together at distances around one third of nanometer and below. The latter is due to cohesive forces arising from screened multipole electrostatic interactions (Van der Waals interactions) and plays a defining role on the thermodynamic properties of the fluid.
The competition between short-range repulsion and long-range attraction leads to a minimum of depth at a distance , which fixes the typical scale of intermolecular separation in the fluid.
where N is the number of molecules in the volume V.
The attractive branch echoes the soft-core tail and the covolume b is related to the spatial scale, , of the hard-core repulsion .
22.214.171.124 Maxwell molecules
A special case is provided by the so-called Maxwell molecules, characterized by a power-law decay:
The calculations show that for such power-law potential , so that the collision time scale is a constant, see eqn (2.22).
This constitutes a major simplification of the Boltzmann collision integral, whence the special role of this potential in kinetic theory.
(p.31) Even though Maxwell’s molecules do not appear to have any realistic counterpart in the physical world, they provide nonetheless a very fruitful theoretical idealization for several mathematical developments in kinetic theory.
In particular, under appropriate simplifications, they permit us to obtain exact solutions of the Boltzmann equation.
Calculations in three spatial dimensions for inverse power-law potentials of the form
This highlights that Maxwell molecules, , mark an qualitative borderline: for , i.e., slower decay than for Maxwell molecules, the collision rate
turns from an increasing to a decreasing function of the relative speed vr, i.e., essentially the fluid temperature.
A moment’s thought reveals that a collision frequency decreasing with the molecular speed implies that fast molecules experience less friction than the slow ones, which is clearly a portal to collective instability.
Indeed, this opens up non-hydrodynamic scenarios, whereby particles accelerated beyond a given critical speed by, say, a constant external field, do not experience a sufficient collisional drag to be drained back to the bulk distribution. As a result, no local equilibrium can be established and the system enters various sorts of unstable regimes, some of which are of great relevance to fusion and astrophysical plasmas and other states of matter typically governed by long-range microscopic interactions.
126.96.36.199 Long-range potentials
An important example of strongly non-hydrodynamic conditions is provided by long-range potentials, such as r−1 unscreened Coulomb electrostatics, or gravitation, formally corresponding to α.
For such potentials, the calculations provide a divergent cross section, due to the unbounded accumulation of many small-angle deflections (grazing collisions).
This is not surprising: the mean-free path is virtually zero, because owing to the infinitely long range of the acting force, the molecules are constantly interacting and the accumulation of very numerous small deflections leads to a logarithmic divergence of the cross section.
The Debye length, λ, marks the scale above which electrostatic interactions are screened out due to polarization effects, a condition typical of quasi-neutral plasmas, composed by a mixture of oppositely charged species, say ions and electrons.
The kinetic theory of such screened systems is described by a different collision operator, due to Landau and Balescu–Lenard, after the Hungarian–Belgian physicist Radu Balescu (1932–96) and the German, Philipp Lenard (one “n” only, not to be confused with Lennard-Jones!) (1862–1947) (5).
This takes the following form:
where is a suitable-tensorial collision kernel.
This expression is obtained from the Boltzmann collision operator by expanding upon the velocity change, , under the assumption of small deflections:
as it is appropriate for soft-core grazing collisions.
The Balescu–Lenard collision operator belongs to the general class of Fokker–Planck kinetic equations, which we shall discuss in chapter 9. For the case of unscreened long-range interactions, say self-gravitating systems, the derivation of a suitable collision operator is still an open issue in modern statistical mechanics, with important implications in plasma physics, astrophysics, and cosmology.
2.4.5 Molecular Chaos (Stosszahlansatz)
Having discussed the details of the two-body scattering problem inherent to Boltzmann’s collision operator, we next move on to consider the all-important statistical aspects of this operator.
In the first place, in order to derive a closed equation, one has to express the two-body distributions and f12, in terms of the one-body ones f1 and f2.
The simplest such closure, which is precisely the one taken by Boltzmann reads as follows:
and same for .
This closure is tantamount to assuming no correlations between molecules entering a collision (molecular chaos or Stosszahlansatz).
(p.33) This assumption is fairly plausible for a dilute gas with short-range interactions, in which molecules spend most of their lifetime traveling in free space, only to meet occasionally for very short lived, in fact instantaneous, interactions.
Note that molecules are assumed to be correlated only prior to the collision, whereas after collision, they become strongly correlated on account of mass, momentum and energy conservation.
Within this picture, the probability for two molecules that met at time t, to meet again at some subsequent time , with the same velocities and , decays exponentially with τ.
More precisely, this probability scales like where is the duration of a collisional event. Since in Boltzmann’s theory (the thermal speed vT is taken to be a typical particle speed and s a typical effective molecular diameter) is negligibly small, so is the (auto)correlation function at time τ.
The situation is obviously completely different in a liquid, where, due to the much higher density, the molecules are in constant interaction.
Violations of Boltzmann’s molecular chaos can occur due to the onset of nonlinear correlations. A most notable example are the famous long-time tails, first detected by Alder and Wainwright (6), where molecular correlations exhibit anomalous persistence due to self-sustained vortices generated by the molecular motion itself.4
Summarizing, in view of the molecular chaos assumption, the Boltzmann equation takes the following form:
The left-hand side is a mirror of reversible Newtonian single-particle dynamics, while the right-hand side describes intermolecular interactions, under the Stosszahlansatz approximation.
2.5 Local and Global Equilibria
Given that the collision operator naturally splits into a Gain minus Loss components, it is only natural to ask under what conditions would the two antagonists come to an exact balance.
This singles out a very special distribution function, characterizing the attainment of local equilibrium, a notion which proves central to the purpose of deriving hydrodynamic equations from Boltzmann’s kinetic theory.
Mathematically, the local equilibrium is defined by the condition
where superscript “e” denotes “equilibrium.”
This leads to the so-called detailed balance condition:
which holds regardless of the details of the molecular interactions.
This is a strong statement of universality: microscopic details affect the rate at which local equilibrium is reached, not the equilibrium itself, which depends only on conserved quantities.
Of course, detailed balance does by no means imply that molecules sit idle, but rather that any direct (inverse) collision is dynamically balanced by an inverse (direct) partner collision.
For instance, in a room at standard temperature, with no appreciable macroscopic flow, the typical molecule moves at the speed of sound, that is, about three times faster than a Ferrari!
For a fluid at rest, along any given spatial direction, there is, on average, another molecule doing exactly the same along the opposite direction, so that no net macroscopic flow results.
The detailed balance condition has far-reaching consequences on the shape of the equilibrium distribution in velocity space.
To appreciate this, let us first take the logarithm of the eqn (2.47), to obtain
This shows that the quantity is an additive collision invariant, i.e., a microscopic additive property which does not change under the effect of collisions.
The immediate consequence is that, at thermodynamic equilibrium, must be a function of the five collision invariants
associated with the conservation of number (mass), momentum and energy.
This yields (repeated Latin indices, denoting spatial directions, are summed upon):
namely density of mass, momentum and energy.
These Lagrangian parameters can be computed by imposing conservation of mass-momentum energy:
where, is the mass density, ua, , is the macroscopic flow speed and ρe is the energy density.5
Elementary quadrature of Gaussian integrals delivers the celebrated Maxwell–Boltzmann equilibrium distribution.
In D spatial dimensions, this reads as follows:
where c is the magnitude of the peculiar speed
namely the relative speed of the molecules with respect to the fluid, and
is the thermal speed associated with the fluid temperature T, kB being the Boltzmann constant. With this definition, each direction carries units of energy.
2.5.1 Local Equilibria and Equation of State
Local equilibria associate with perfect (or inviscid) fluids, i.e., fluids in which dissipative effects can be neglected.
At equilibrium, density, temperature and pressure are related through an equation of state:
where c is the magnitude of the peculiar velocity and is the mass density.
The definition shows that temperature is basically the variance of the kinetic distribution function, or, in different terms, the peculiar kinetic energy of the molecules with respect to the mean-flow motion (see Figs. 2.8 and 2.9).
Another quantity of chief interest for hydrodynamics is the momentum-flux tensor, often called pressure tensor for short:
The definition indicates that the component Pab of the pressure tensor represents the amount of momentum mva along direction xa, fluxing across the unit surface with normal oriented along direction xb.
The ordinary pressure is given by the diagonal components of the pressure tensor, evaluated at zero-flow conditions .
It is now instructive to compute the value of the macroscopic quantities corresponding to the local equilibrium distribution.
Elementary gaussian integration yields
It is also of interest to note that, under such conditions, the thermal speed corresponds exactly to the sound speed, defined as the derivative of the pressure with respect to the density at a constant temperature, namely
Knowledge of the ratio of thermal to sound speed, , as a function of density and temperature is just another way of specifying the equation of state of the fluid, denoting the ideal gas.
2.5.2 The Evershifting Battle
As shown in Section 2.5.1, local Maxwell equilibria are the result of a statistical balance between forward and backward collisions.
This balance between gain and loss terms annihilates the effect of the collision operator on the distribution function.
Quite remarkably, such balance holds true independently of whether or not the macroscopic fields exhibit a variation in space and/or time (whence the label “local”), as long as such variation occurs on scales longer than the mean-free path.
This property stems directly from the assumption that collisions take place in the limit , or, more precisely, .
A natural, and indeed often-asked question is:
Do local equilibria annihilate the effects of the streaming operator too?
A moment’s thought reveals that this is not the case, unless the macroscopic fields are totally flat, i.e., constant in space and time, a condition which defines global equilibria, hence equilibrium thermodynamics.
To appreciate the point in a little more detail, let us compute the effect of the streaming operator on local equilibria.
A simple application of the chain rule yields
By evaluating the partial derivatives of fe with respect to ρ, and T, simple algebra delivers
is the peculiar speed in units of the thermal speed.
Expression (2.53) clearly shows that, by construction, local equilibria are not preserved upon streaming, i.e., they can only be conserved if all macroscopic fields are constant in space and time, which, by definition means they are no longer local, but global ones.
Of course, this is all but a coincidence. The broken-invariance of local equilibria upon streaming, reflects a profound physical mechanism: space-time inhomogeneity is the source of non-equilibrium.
Differently restated, collisions act so as to achieve detailed balance, thereby couching the distribution function into the universal local Maxwell–Boltzmann distribution.
Streaming, on the other hand, works exactly in the opposite direction; it destroys the delicate (detailed) balance established by collisions, and revives non-equilibrium through inhomogeneity.
This is the famous “evershifting battle” between equilibrium and non-equilibrium, as evoked by Boltzmann, a battle which is not over until a featureless uniform macroscopic scenario is attained.
For those versed in philosophical aspects of science, the evershifting battle between equilibrium and non-equilibrium can be seen as a sort of metaphor of Life itself, which depends crucially on the ability to function far from equilibrium in local and temporary elusion of the Second Law (“life on borrowed time”).
It is sometimes heard that the depth of any given equation is measured by the conceptual distance between its left- and right-hand side. If such criterion is anything to go by, there is little doubt that the Boltzmann equation scores very highly indeed.
Back to the ground. Broken invariance of local equilibria under streaming reflects the broken symmetries of classical mechanics. To this purpose, we note that Maxwellian equilibria inherit two basic symmetries of Newtonian mechanics, namely (7):
— Space and time translational invariance
where τ and are arbitrary constants.
The invariance under such transformation reflects the homogeneity of space and time. For the case where , Va being a constant velocity, (2.63) reflect invariance under Galilean transformations.
— Rotational invariance
Rotational invariance, which applies to the particle velocities as well, is ensured by the fact that the peculiar speed appears through its magnitude alone, so that any sense of preferential direction is erased.
These symmetries are built-in in continuum kinetic theory, but it would be a gross mistake to take them for granted also when space time and velocity are made discrete.
Actually, this is the leading theme of Discrete Kinetic Theory.
The hydrodynamic probe of rotational symmetry is the momentum-flux tensor Pab, which plays a pivotal role in Discrete Kinetic Theory and most notably in Lattice Gas Cellular Automata and Lattice Boltzmann theories.
Summarizing, Boltzmann kinetic theory describes the dynamics of dilute gases in terms of a probability distribution function including, besides space and time. molecular velocities. The result is a complicated quadratic integro-differential equation describing the competition between free streaming and interparticle collisions. For sufficiently well-behaved (short-ranged) atomistic potentials, such competition ultimately ends up into a universal local equilibrium, which depends only on the local conserved fluid quantities, mass, momentum and energy. This local equilibrium plays a crucial role in the derivation of hydrodynamics from Boltzmann’s kinetic theory.
1. L. Boltzmann, Lectures on Gas Theory, University of California Press, California, 1964.
2. C. Cercignani, Theory and Application of the Boltzmann Equation, Elsevier, New York, 1975.
3. C. Cercignani, Mathematical Methods in Kinetic Theory, Plenum Press, New York, 1969.
4. K. Huang, Statistical Mechanics, Wiley, New York, 1987.
5. R. Balescu, Equilibrium and non equilibrium statistical mechanics, John Wiley and sons, New York, 1975.
6. B. Alder and J. Wainwright, Decay of the velocity autocorrelation function, Phys. Rev., A 1, 18, 1970.
7. S. Goldstein, Classical Mechanics, Addison–Wesley, London, 1959.
(2) The symbol denotes the interparticle potential, not to be confused with plain V, the volume of the system, and the barycentric velocity of the two-body problem.
(3) We shall stick to the common tenet that microscopic equations, either classical or quantum, are invariant under time reversal.
(4) This is amazingly reminiscent of the mechanisms invoked by Aristoteles to explain the motion of arrows in air!
(5) The Latin subscript a denotes cartesian components of a vector, so that the notation va is an equivalent substitute for and shall be used interchangeably throughout the text, see Appendix on Notation.