The overview of the principles of quantum statistical mechanics are given, emphasizing the fundamental differences with respect to classical statistical mechanics, as well as the analogies prevailing for the formulation of the properties. A functional time-reversal symmetry relation is presented, allowing the deduction of response theory. The Kubo formula is obtained for the linear response properties and the fluctuation–dissipation theorem is established. For weakly coupled systems, the quantum master equation and the corresponding stochastic Schrödinger equation are deduced. The slippage of initial conditions is discussed in relation to the positivity of the reduced statistical operator. The results are illustrated with the spin-boson model.

The subject here is the absorption coefficient, expressing the net power loss from the field over a unit path. At its heart is the line shape, which may be identified with the power spectral density function for fluctuations of the active dipole in the presence of an equilibrium bath of perturbers, and, as such, should satisfy the fluctuation–dissipation theorem. The more general properties of the absorption coefficient, which must reflect this balance, are first examined in some detail, particularly for the Van Vleck–Huber form. It is then shown that this, when expanded as a sum over individual lines, may be folded into more compact expressions. Outside the line core, these expressions must incorporate the fluctuation–dissipation theorem, and special attention is given to distinguish this case and that of the core itself, where it is of no consequence. Even the very general Fano theory does not, as it stands, satisfy the theorem, and can be used for the far-wing line shape only if these expressions are modified. Finally, some account is given of how they may be used with a molecular line database, and how a calculation of radiative transfer might proceed in the simplest of cases.

Starting from the very general Fano theory of pressure broadening, ways are sought to express the shape of a band of lines in a form that is more amenable to calculation. Initially, the far-wing is considered, and care is taken to ensure, by an adjustment, that the fluctuation–dissipation theorem is satisfied, despite Fano’s neglect of the initial correlations between the states of the radiator and the bath of its perturbers. The far-wing also requires, in a Fourier sense, the use of a very fine time scale, which allows the approach taken by Rosenkranz and Ma & Tipping, described first, to adopt the quasi-static approximation. In obtaining the overall line shape, the average over collisions may then be run across an ensemble of essentially static binary configurations. In the line core, the initial correlations may be ignored anyway, and, because a much coarser time scale is appropriate, the impact approximation may be invoked. Here, Fano’s theory is shown to reduce to that of Baranger, yielding expressions for fixed line shifts and widths, and allowing, through a perturbative approximation due to Rosenkranz, a simple expression to be derived to take account of line coupling.

This chapter presents microscopic models of diffusion (Brownian motion). The discussed diffusion models explicitly describe the dynamics of solvent molecules. Such molecular dynamics models provide many more details than the models discussed in Chapter 4 (which simply postulate that the diffusing molecule is subject to a random force) and can be used to assess the accuracy of the stochastic diffusion models from Chapter 4. The analysis starts with theoretical solvent models, including a simple “one-particle” description of the solvent (heat bath), which is used to introduce the generalized Langevin equation and the generalized fluctuation–dissipation theorem. Analytical insights are provided by theoretical models with short- and long-range interactions. The chapter concludes with less analytically tractable, but more realistic, computational models, introducing molecular dynamics (molecular mechanics) and applying it to the Lennard-Jones fluid and to simulations of ions in aquatic solutions.