 Master equation

See Lindblad equation for the master equation used in quantum physicsSee also Batalin–Vilkovisky formalism for the classical and quantum master equations in quantum field theory.
In physics and chemistry and related fields, master equations are used to describe the timeevolution of a system that can be modelled as being in exactly one of countable number of states at any given time, and where switching between states is treated probabilistically. The equations are usually a set of differential equations for the variation over time of the probabilities that that the system occupies each different states.
Contents
Introduction
A master equation is a phenomenological set of firstorder^{[citation needed]} differential equations describing the time evolution of (usually) the probability of a system to occupy each one of a discrete set of states^{[citation needed]} with regard to a continuous time variable t. The most familiar form of a master equation is a matrix form:
where is a column vector (where element i represents state i), and is the matrix of connections. The way connections among states are made determines the dimension of the problem; it is either
 a ddimensional system (where d is 1,2,3,...), where any state is connected with exactly its 2d nearest neighbors, or
 a network, where every pair of states may have a connection (depending on the network's properties).
When the connections are timeindependent rate constants, the master equation represents a kinetic scheme, and the process is Markovian (any jumping time probability density function for state i is an exponential, with a rate equal to the value of the connection). When the connections depend on the actual time (i.e. matrix depends on the time, ), the process is not Markovian, and the master equation obeys,
When the connections represent multi exponential jumping time probability density functions, the process is semiMarkovian, and the equation of motion is an integrodifferential equation termed the generalized master equation:
The matrix can also represent birth and death, meaning that probability is injected (birth) or taken from (death) the system, where then, the process is not in equilibrium.
Detailed description of the matrix , and properties of the system
Let be the matrix describing the transition rates (also known, kinetic rates or reaction rates). The element is the rate constant that corresponds to the transition from state k to state ℓ. Since is square, the indices ℓ and k may be arbitrarily defined as rows or columns. Here, the first subscript is row, the second is column. The order of the subscripts, which refer to source and destination states, are opposite of the normal convention for elements of a matrix. That is, in other contexts, A_{12} could be interpreted as the transition. However, it is convenient to write the subscripts in the opposite order when using Einstein notation, so the subscripts in A_{12} should be interpreted as .
For each state k, the increase in occupation probability depends on the contribution from all other states to k, and is given by:
where P_{k}, is the probability for the system to be in the state k, while the matrix is filled with a grid of transitionrate constants. Similarly, P_{k} contributes to the occupation of all other states::
In probability theory, this identifies the evolution as a continuoustime Markov process, with the integrated master equation obeying a Chapman–Kolmogorov equation.
The master equation can be simplified so that the terms with ℓ = k do not appear in the summation. This allows calculations even if the main diagonal of the is not defined or has been assigned an arbitrary value.
The master equation exhibits detailed balance if each of the terms of the summation disappears separately at equilibrium — i.e. if, for all states k and ℓ having equilibrium probabilities and ,
These symmetry relations were proved on the basis of the time reversibility of microscopic dynamics (as Onsager reciprocal relations).
Examples of master equations
Many physical problems in classical, quantum mechanics and problems in other sciences, can be reduced to the form of a master equation, thereby performing a great simplification of the problem (see mathematical model).
The Lindblad equation in quantum mechanics is a generalization of the master equation describing the time evolution of a density matrix. Though the Lindblad equation is often referred to as a master equation, it is not one in the usual sense, as it governs not only the time evolution of probabilities (diagonal elements of the density matrix), but also of variables containing information about quantum coherence between the states of the system (nondiagonal elements of the density matrix).
Another generalization of the master equation is the Fokker–Planck equation which describes the time evolution of a continuous probability distribution.
See also
 Markov process
 Fermi's golden rule
 Detailed balance
 Boltzmann's Htheorem
 Continuoustime Markov process
References
 van Kampen, N. G. (1981). Stochastic processes in physics and chemistry. North Holland. ISBN 9780444529657.
 Gardiner, C. W. (1985). Handbook of Stochastic Methods. Springer. ISBN 3540208828.
 Risken, H. (1984). The FokkerPlanck Equation. Springer. ISBN 345061530X.
External links
 Timothy Jones, A Quantum Optics Derivation (2006)
Categories: Statistical mechanics
 Stochastic processes
 Equations
 Fundamental physics concepts
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