1. Introduction
In a closed thermal system evolving from a non-equilibrium state that is not far from the equilibrium state, the thermodynamic entropic function
can be expanded around the equilibrium state
as
where each
is an extensive variable, and then, we introduce the Ruppeiner metric
[
1]:
The components
are positive definite and symmetric
, if the
is a smooth concave function, i.e.,
is convex. The entropy production rate can be described by
where
are the (conjugate) intensive variables, and
are the thermodynamic fluxes of the variable
. Onsager [
2,
3] expands the fluxes as the linear combinations of the thermodynamic forces:
which are known as Onsager’s phenomenological equations (OPE), the linear constitutive equations relating the fluxes and the forces with the condition that all
when all
. He assumes the coefficients
to be symmetric, i.e.,
whose symmetry is known as the reciprocal relations. Several studies have been performed concerning the OPE, e.g., Doi [
4,
5] extensively studied Onsager’s variational principle in soft matter.
Our previous studies on the gradient flow [
6,
7,
8] in information geometry (IG) [
9] showed some relations to different fields such as thermodynamics [
10], geometric optics [
10,
11], analytical mechanics, and general relativity [
12,
13]. Among them, we pointed out [
13] that Equation (
5) can be regarded as the gradient-flow equation:
with respect to the
-potential function
in IG, if we make the correspondence
where
denotes the components of the Fisher matrix, and
and
are mutually dual affine coordinates in IG (see
Appendix A for the details). In this correspondence, Onsager’s reciprocal relations (
6) can be understood in IG as the symmetry of the metric
, which is due to integrability.
Research focusing on the mathematical scientific structures common to different fields is at the heart of SUURI engineering. SUURI is a Japanese word, which consists of the two Kanji characters: SUU (numbers, or mathematical things) and RI (reason, theory, or laws). SUURI is often translated as mathematics or applied physics, but they are not appropriate, and there is no direct counterpart in other languages. It treats natural and social phenomena as SUURI phenomena and deals with theorems and laws, theorizing and applying them. We explore this type of research on Onsager’s phenomenological equations from the perspective of the gradient-flow equations in IG.
The rest of the paper is organized as follows. In
Section 2, we first consider the simple extension of OPE (
5) based on our studies on the gradient-flow equations in IG. In this simple model, which we call the natural gradient-flow model, Onsager’s phenomenological coefficients are replaced with the Hessian of the negative thermodynamic entropic function
. In
Section 3, we adopt the components of the inverse of the metric
G on a space spanned by the thermodynamic extensive variables
. We call this model the
G-gradient-flow model.
Section 4 applies these two models to the ideal gas and van der Waals gas. The final section is devoted to our conclusions. The basics of IG and the gradient flow in IG are summarized in
Appendix A.
Appendix B explains the connection to the cotangent bundle. This connection
relates the flow
in the tangent space
to the flow
in the cotangent space
.
Appendix C shows the expression of the Levi–Civita connection of a metric
G obtained from Jacobi matrix
J. Throughout the paper, we use Einstein’s summation convention for a repeated index.
2. Natural Gradient-Flow Model
Here, we extend OPE (
5) based on our studies [
10,
11,
12,
13] of the gradient-flow equations in IG. We apply the methods for deriving some important relations in IG to Onsager’s non-equilibrium thermodynamics. From the correspondence (
8), as our first model, we introduce the coefficients
as
It is worth noting that the coefficients
depend on
X in general, whereas the coefficients
in OPE (
5) are independent. One readily confirms the reciprocal relations as follows.
Note that (
9) means that the matrix
is simultaneously a Jacobi matrix whose components are
and a Hessian matrix of
, similar to the distinct feature of the Fisher matrix
g in IG (cf. (
A4)).
We can introduce the total Legendre transform
of the thermodynamic entropic function
, i.e.,
Then, as the dual relation to (
9), we have
Note that since the extensive variables
and the intensive variables
are related through (
11), the coefficient
can be regarded as a function of
, i.e.,
. With the coefficients
, as the gradient-flow equations corresponding to (
A10) in IG, we propose
where
denotes the thermodynamic force at a thermal state
X. We assume that
has a non-zero value in general, whereas in OPE (
5),
is assumed to be zero. Since in the fields of optimization and IG, the operator
is called the natural gradient [
8,
14], we call this model characterized by (
13) the natural gradient-flow model.
Next, by using (
9) and (
13), we have
Consequently, it follows the linearized differential equations:
which are the dual equations to (
13). Note that, whereas the original Equation (
13) is nonlinear in general, the linearized Equation (
15) is readily solved. As is clear from the above derivation process, the key point is that the coefficients
are the components
of the Jacobi matrix.
By using (
13), the entropy production rate (
3) can be expressed as
where we introduced the dissipation function:
It is convenient to introduce the function
:
which corresponds to (
A13b) in IG.
The relation between the gradient flow in IG and Hamilton flow were pointed out in [
6,
7]. Boumuki and Noda [
15] studied this relationship from the perspective of symplectic geometry. Chirco et al. [
16] discussed Lagrangian and Hamiltonian dynamics in their non-parametric formalism. In our previous studies [
11,
13], we proposed the special type of Hamiltonian, which describes the gradient flow in IG. Based on the results, Equation (
A12b) of the Hamilton flow in IG, we can construct the Hamiltonian:
whose Hamilton flow is equivalent to the natural gradient flow (
13) and its dual (
15). Indeed, Hamilton’s equations of motion are
The first equations are equivalent to (
13). For the second equations, from (
18), we have
Substituting this relation into the right-hand side in (
20b), we obtain the linearized Equation (
15).
One may wonder why the Hamiltonian (
19) describes simultaneously the natural gradient-flow
and its dual flow
. In
Appendix B, we explain the connection
with the cotangent bundle. The connection
relates the flow
in the tangent space to the flow
in the cotangent space. The Hamiltonian (
19) is constant along all horizontal curves and satisfies the distinctive relation (
A40), from which the flow
in tangent space and the flow
in cotangent space are related, as shown (
A42), by the transport Equation (
A17). Actually, the natural gradient flow Equation (
13) and the dual linearized Equation (
15) are related by
3. -Gradient-Flow Model
In the natural gradient-flow model, the coefficients
are important ingredients and equivalent to the Hessian of
, and also to the Ruppeiner metric [
1]. However, in order to obtain the coefficients
in (
9), it requires an expression of the thermodynamic entropic function
as a function of the extensive variables
. It is difficult to determine an explicit expression of the thermodynamic entropy, in general. Thermodynamic systems are often characterized by a set of equations of thermodynamic state, which are experimentally determined. Vaz [
17] provided the method for obtaining the metric
G in the space spanned by the extensive variables
from a set of equations of thermodynamic state. Here, we propose another model (
G-gradient-flow equations) based on Vaz’s method.
Let us consider the coordinate transformation from
to a function
of
X,
where
are the components of the Jacobi matrix
J. The meaning of each function
is shown in (
30). Similarly, the inverse relations are given by
The following relations are satisfied.
Thus, (
23) describes the transformation rule from the frame consisting of the coordinate basis
to the frame consisting of the basis
. Their dual bases are
and
, respectively, and they satisfy
In general, equilibrium thermodynamic systems with
n-independent macroscopic variables are completely described by the
n-independent equations of state, which, in some cases, can be cast into the following form [
10,
17],
where
is given in (
4), and each
is an independent constant. We can assign
as the components in an orthogonal basis
with the invertible constant diagonal matrix
. In other words, the frame consisting of the orthogonal basis
is Cartan’s moving frame. In general, the frame
is non-orthogonal and is characterized by a metric tensor
G, whose components
are related by
The Jacobi matrix
J relates the non-orthogonal frame
with the local orthogonal frame
as shown in (
27).
Next, by inverting (
27), we have
which implies that the entropic function is expressed in the form:
except for the constant of integration. In this way, when the thermodynamic equations of state are cast into the form (
27), the thermodynamic entropic function
is decomposed in the form (
30), which consists of the sum of the product of a constant
and a function
.
The inner product in the orthogonal frame
with a diagonal metric tensor
and that in the non-orthogonal frame
with a metric tensor
G are related by
We can regard this relation as the generalized eikonal equation [
10] (or Hamilton–Jacobi equation):
where
is a positive constant. From Equations (
27) and (
31), it follows that
It is worth noting that a Jacobi matrix
is determined by
components, whereas a Riemann metric
has
components. Consequently, the metric
is obtained from a given Jacobi matrix
as (
28) and (
34), whereas the converse is not possible in general, since
for
.
Now, we introduce the
G-gradient-flow model as follows.
Note that, since
is a diagonal matrix,
is symmetric under exchanging of indices, i.e, the reciprocal relations are satisfied. Since the coefficient
comprises the components of the metric
, we call this model the
G-gradient-flow model.
The entropic rate in this model is
From (
29), we obtain the dual equations with respect to (
35) as follows.
Combining (
35) and (
37), we have
which are the transport equations in (
A17). As explained in
Appendix B, the connection
to the cotangent bundle relates the flow
in the tangent space
to the flow
in the cotangent space
. Hence, we find that
plays a role of the connection
to a cotangent bundle.
This relation (
) can be confirmed as follows. As shown in
Appendix C, the coefficients
of the Levi–Civita connection with respect to
G are obtained in (
A47), i.e.,
Then, the associated linear connection
in (
A25) becomes
5. Conclusions
We reconsidered Onsager’s non-equilibrium thermodynamics from the perspective of our previous studies [
10,
11,
12,
13] on the gradient flow in IG. As extensions of the OPE, we proposed the two different gradient-flow equations by replacing Onsager’s phenomenological coefficients with the Hessian of
or with the inverse of the metric
G in the space spanned by the thermodynamic extensive variables
X. We call the former the natural gradient-flow model and the latter
G-gradient-flow model. We considered both gradient-flow models and their relations. In a similar way to how IG works, where the natural gradient-flow equations are nonlinear in the extensive variables
in general, the dual equations are linear in the intensive variables
. We considered the relationship between both models and showed that the coefficients
in the natural gradient-flow model are the (negative of) the connection coefficient
in the cotangent bundle. For both models, the flow
in tangent space and the flow
in cotangent space are related by the transport equations as shown in (
22) and in (
38). We applied both models to the ideal gas and the van der Waals gas models. Since the ideal gas model is too simple, both models for the ideal gas are the same. In contrast, for the van der Waals gas model, both models are different. We performed numerical analysis and obtained the numerical solutions for the natural- and
G-gradient flow equations. Their trajectories are clearly different as shown in
Figure 1 and
Figure 2; hence, they describe different thermodynamic processes.
Recently, Bravetti et al. [
19] studied asymmetric relaxations within the context of IG. In order to obtain a gradient-flow equation within the context of IG, they used the gradient of the internal energy of a system, whereas in this work, the gradient of the entropic function of a system is used as well as IG. Thus, it should be interesting to extend our method to a gradient flow with respect to an internal energy or free energy.