Derivation of the Onsager symmetry

In summary, the Onsager symmetry is derived by assuming that the correlation function of two state variables satisfies certain conditions for a small time interval. By transforming the expressions, it can be shown that the Onsager coefficients are symmetric. However, there is some discrepancy in the use of the relation for small time intervals in the derived equations, which may result in a contradiction with Onsager's general results. It is unclear why this relation was incorporated into the papers being read.
  • #1
Efil_Kei
1
0
Derivation of the Onsager symmetry in many textbooks and papers is as follows: First, assume that the correlation function of two state variables,##a_i## and ##a_j## satifsies for sufficiently small time interval ##t## that
$$\langle a_i(t) a_j(0) \rangle = \langle a_i(-t) a_j(0) \rangle = \langle a_i(0) a_j(t) \rangle. $$
Then, transforming leftmost and rightmost expressions yields
$$\langle a_i(t) a_j(0) \rangle = \langle a_i(0) a_j(0) \rangle -k_B L_{ij},$$
and
$$\langle a_i(0) a_j(t) \rangle = \langle a_i(0) a_j(0) \rangle -k_B L_{ji},$$
respectively, since ## \langle \dot{a_i}a_j \rangle= -k_B L_{ij}##, where ##k_B## is the Boltzmann constant. It follows from the two expressions that
$$L_{ij}=L_{ji},$$
I have a question here. If we equate the leftmost one with the one in the center, not with the rightmost one, in the first equation, it can be obtained that
$$\langle a_i(0) a_j(0) \rangle -k_B L_{ij}=\langle a_i(0) a_j(0) \rangle +k_B L_{ij},$$
then this leads to
$$L_{ij}=-L_{ij}.$$
This means ##L_{ij}## must be 0 and contradicts the Onsager's general results.

Am I mathematically wrong somewhere above or am I missing some physical logic?
 
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  • #2
This is very odd. In Onsager's original paper:
https://journals.aps.org/pr/abstract/10.1103/PhysRev.38.2265
he simply uses the relation:
$$\langle a_i(t) a_j(0) \rangle = \langle a_i(0) a_j(t) \rangle$$
to denote the condition of microscopic reversibility (equation 1.2, ibid). The relation:
$$\langle a_i(t) a_j(0) \rangle = \langle a_i(-t) a_j(0) \rangle $$
for small ##t## is only true at a local extremum; that is, where the derivative vanishes. In fact, looking at your derivation of Onsager's relations in post 1, this second relation is not used anywhere. I'm not sure why it would have been incorporated into the papers you're reading.
 

1. What is the Onsager symmetry?

The Onsager symmetry is a fundamental principle in statistical mechanics that states that the kinetic coefficients of a system are symmetric with respect to time reversal. In other words, the behavior of a system is the same whether time moves forward or backward.

2. Who discovered the Onsager symmetry?

The Onsager symmetry was discovered by the American physicist Lars Onsager in 1931. He was awarded the Nobel Prize in Chemistry in 1968 for his contributions to the understanding of irreversible processes.

3. What is the importance of the Onsager symmetry?

The Onsager symmetry is important because it provides a theoretical basis for understanding the behavior of systems in equilibrium and out of equilibrium. It also allows for the prediction of transport properties, such as electrical conductivity and thermal conductivity, in various systems.

4. How is the Onsager symmetry derived?

The Onsager symmetry is derived using the principles of statistical mechanics, specifically the Boltzmann equation and the fluctuation-dissipation theorem. It involves considering the behavior of a system under time reversal and using mathematical transformations to show that the kinetic coefficients are symmetric.

5. What are some real-world applications of the Onsager symmetry?

The Onsager symmetry has been applied in various fields, including thermodynamics, fluid dynamics, and materials science. It has also been used in the development of efficient energy conversion devices, such as fuel cells and thermoelectric generators, and in the study of biological systems. Additionally, the Onsager symmetry has implications for understanding the behavior of complex systems, such as climate dynamics and financial markets.

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