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Research Article

Generalized entropies and logarithms and their duality relations

Rudolf Hanel, Stefan Thurner, and Murray Gell-Mann
PNAS November 20, 2012 109 (47) 19151-19154; https://doi.org/10.1073/pnas.1216885109
Rudolf Hanel
aSection for Science of Complex Systems, Medical University of Vienna, 1090 Vienna, Austria; and
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Stefan Thurner
aSection for Science of Complex Systems, Medical University of Vienna, 1090 Vienna, Austria; and
bSanta Fe Institute, Santa Fe, NM 87501
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Murray Gell-Mann
bSanta Fe Institute, Santa Fe, NM 87501
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  • For correspondence: mgm@santafe.edu
  1. Contributed by Murray Gell-Mann, September 28, 2012 (sent for review August 6, 2012)

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Abstract

For statistical systems that violate one of the four Shannon–Khinchin axioms, entropy takes a more general form than the Boltzmann–Gibbs entropy. The framework of superstatistics allows one to formulate a maximum entropy principle with these generalized entropies, making them useful for understanding distribution functions of non-Markovian or nonergodic complex systems. For such systems where the composability axiom is violated there exist only two ways to implement the maximum entropy principle, one using escort probabilities, the other not. The two ways are connected through a duality. Here we show that this duality fixes a unique escort probability, which allows us to derive a complete theory of the generalized logarithms that naturally arise from the violation of this axiom. We then show how the functional forms of these generalized logarithms are related to the asymptotic scaling behavior of the entropy.

  • classical statistical mechanics
  • correlated systems

The concept of “superstatistics” (1⇓–3) provides a formal framework for a wide class of generalizations of statistical mechanics that were introduced recently. Within this framework it is possible to formulate a maximum entropy principle, even for nonergodic or non-Markovian systems, including many complex systems. From an axiomatic point of view, nonadditive systems are characterized by the fact that the fourth Shannon–Khinchin (SK) axiom governing composability of statistical systems is violated.† For systems where all four SK axioms hold, the entropy is uniquely determined as the Boltzmann–Gibbs–Shannon (BGS) entropy (4, 5), Graphic. In the case where only the first three axioms are valid (e.g., non-Markovian systems), the entropy has a more general form (6). In the thermodynamic limit, which captures the asymptotic behavior for small values of the pi, the entropy is given by the formulaEmbedded Imagewhere Γ is the incomplete gamma function and (c, d) are constants that are uniquely determined by the scaling properties of the statistical system in its thermodynamic limit. In previous work (7) we were able to show that for systems where the first three SK axioms hold, there exist only two ways to formulate a consistent maximum entropy principle. Starting with an entropy of “trace form,”Embedded Imagethe maximization condition becomes δ Φ = 0, withEmbedded Imagewhere the last two terms are the constraints. The first of the two possible approaches [Hanel–Thurner (HT) approach] (8, 9) uses a generalized entropy and the usual form of the constraint, Graphic. The other approach, suggested in Tsallis and Souza (10) (TS approach), uses a generalized entropy and a more general way to impose constraints:Embedded Image

Pi is a so-called escort probability and ν is a real number. Though in the HT case the constraint has the usual interpretation as an energy constraint, we do not attempt to give a physical interpretation of the escort probabilities. The two approaches have been shown to be connected by a duality map *: Graphic with ** (meaning applying * twice) being the identity (7). A special case of this duality has been observed in Ferri et al. (11).

Entropies can be conveniently formulated using their associated generalized logarithms. We first specify the space ℒ of proper generalized logarithms Λ ∈ ℒ. We consider a generalized logarithm to be proper if the following properties hold: (i) Λ is a differentiable function Λ: ℝ+ → ℝ. This is necessary for a finite second derivative of the entropy; (ii) Λ is monotonically increasing, which is a consequence of the second SK axiom; (iii) Λ(1) = 0, which captures the requirement that the entropy of single-state systems is 0; and (iv) Λ′(1) = 1, is needed to fix the units of entropy.

In both approaches (HT and TS) there exist proper generalized logarithms ΛHT and ΛTS such thatEmbedded ImageandEmbedded Imagewith x0 a constant. If both approaches predict the same distribution function Graphic as a result of the maximization of Eq. 3, then it can be shown that the two entropic functions sHT and sTS are one-to-one related byEmbedded Image

In the following, we set k = 1; this can be achieved either by choosing physical units accordingly, or by simply absorbing k into ν, so that ν becomes a dimensionless parameter.

The full implication of Eq. 7, which is related to the essence of this paper, can be summarized as follows. The statistical properties of a physical system—for instance, a superstatistical system as discussed in Hanel et al. (7)—uniquely determine the entropy SHT. A priori, there exists a spectrum of TS entropies, STS,ν, whose boundaries are determined by the properties of the generalized logarithm associated with SHT. Moreover, these properties determine a particular value ν*, so that Graphic and SHT become a pair of dual entropies. This unique duality allows us to derive a complete theory of generalized logarithms naturally arising as a consequence of the fourth SK axiom being violated. We present a full understanding of how the TS and HT approaches are interrelated and derive the most general form of families of generalized logarithms that are compatible with a maximum entropy principle and the first three SK axioms. Finally, we demonstrate how these logarithms can be classified according to their asymptotic scaling properties, following the results presented in Hanel and Thurner (6).

Duality

In contrast to the images of generalized logarithms, which need not span ℝ completely and can differ from one another, the domain of generalized logarithms themselves is always all of ℝ+. For these reasons, one may classify generalized logarithms according to the minimum and maximum values of their images and consider the group G of order-preserving automorphisms on ℝ+ that keep an infinitesimal neighborhood of 1 ∈ ℝ+ invariant, as the means to generate these classes. In the following, we call the elements g of this automorphism group scale transformations. More precisely, g ∈ Embedded Image is a scale transformation if g is differentiable and maps ℝ+ to ℝ+ one-to-one, g′ > 0, g(1) = 1, and g′(1) = 1. From these properties it follows that g(0) = 0 and limx→∞g(x) = ∞. Finally, we use the notation f ○ g(x) = f (g(x)).

Scale transformations leave the image of a generalized logarithm invariant, which allows us to parameterize classes in the following way. Given a proper generalized logarithm Λ ∈ ℒ, we write for its maximum and minimum valuesEmbedded Imageand define two functionalsEmbedded Imagewhich associate numbers ν+ and ν− to any Λ. For their sum we write ν* = ν+ + ν−. Next, we define sets of proper generalized logarithms,Embedded Image

Members of Graphic all have the same maximum and minimum values. In fact, the Graphic are exactly the equivalence classes in ℒ generated by G: Two generalized logarithms Λ(A) and Λ(B) are considered equivalent if there exists a scale transformation g ∈ G such that Λ(B) = Λ(A) ○ g. The space of generalized logarithms can be written as the union of these sets, Graphic.

With these definitions we now analyze the relation between the HT and TS approaches. Assuming that ΛHT is given, Eq. 7 impliesEmbedded Image

Tν is a shift operator with the property Tν ○ Tμ = Tν+μ. We have of course ΛTS,0 = ΛHT. The fact that ΛHT is a proper generalized logarithm does not imply that ΛTS is also proper for all choices of ν.

In fact, given that Λ ∈ ℒ, it can be shown (SI Materials and Methods) that Tν ○ Λ ∈ ℒ if and only if ν−[Λ] ≤ ν ≤ ν+[Λ]. Moreover, for Graphic and for Tν ○ Λ being a proper generalized logarithm, it follows that Graphic. As a consequence ΛTS,ν (x) = Tν ○ ΛHT (x) is proper only for ν−[ΛHT] ≤ ν ≤ ν+[ΛHT], andEmbedded Image

This equation does not uniquely determine a duality relation * on ℒ, yet by imposing the condition that * commute with scale transformations g ∈ Embedded Image, it can be shown (SI Materials and Methods) that * is given byEmbedded Imagewith the propertyEmbedded Image

Thus, for each ΛHT there exists a unique value ν* = ν+[ΛHT] + ν−[ΛHT] such that ΛTS,ν* is a proper generalized logarithm. The duality map * gives Graphic. Furthermore, because * and g commute ((Λ ○ g)* = Λ* ○ g), any proper generalized logarithm Λ can be decomposed into a specific representative Graphic, and a scale transformation g, so thatEmbedded Imagewhich implies that any ΛHT or ΛTS,ν can be decomposed in this way, and that the dual logarithms ΛHT and Graphic transform identically under scale transformations.

Functional Form of the Generalized Logarithms

Eq. 14 implies the existence of transformations that map members of Graphic to members of Graphic. These maps can be used to represent the duality * on specific families Graphic. Λ(x) → −Λ(1/x) is exactly such a map, because Graphic. The same holds for Graphic, which allows us to construct Graphic with the propertiesEmbedded Image

By using Eq. 13 and inserting Graphic into Eq. 7, we getEmbedded Image

This equation may have many solutions Graphic, but we can restrict ourselves to finding a particular one; all of the others can be obtained by scale transformations, which is seen as follows: Suppose Graphic and Graphic are both solutions of Eq. 17; then according to Eq. 15 for any pair (ν+, ν−) there exists a scale transformation Graphic such that Graphic. Because Graphic must leave Eq. 16 invariant (this is not the case for arbitrary scale transformations g ∈ Embedded Image), these scale transformations have two properties. The first property is Graphic, which makes them members of a subgroup Graphic of all possible scale transformations g ∈ Embedded Image. The second property is Graphic and follows from the fact that * commutes with scale transformations.

A particular solution of Eq. 17 is given byEmbedded Imagewith h: ℝ → [−1, 1] a continuous, monotonically increasing, odd function, with limx→∞ h(x) = 1 and h′(0) = 1. It can easily be verified that this solution has all of the required properties: Graphic is a proper logarithm with Graphic (correct minimum and maximum), Graphic, Λν,−ν(x) = h(ν log(x))/ν is self-dual, and Graphic.

The above argument means that we can generate a specific family of logarithms Graphic, following Eq. 16, by choosing one particular function h [e.g., h(x) = tanh(x)] and then using scale transformations to reach all other possibilities. In particular, some family Graphic with the property Graphic can be reached by a family of scale transformations Graphic, where Graphic are generalized exponential functions (inverse functions of logarithms). Moreover, if Graphic also follows Eq. 16, then Graphic.

The family of dual logarithms discussed in Hanel et al. (7) is obtained in the framework presented here by setting either ν+ = 0 or ν− = 0. These classes correspond to logarithms that are unbounded either from below or from above, whereas the duality maps Graphic. Moreover, in Hanel et al. (7), only pairs of dual logarithms have been considered such that Λ*(x) = −Λ(1/x), and the part that scale transformations play in the unique definition of * had not yet been described.

We are now in a position to understand all observable distribution functions emerging from the two approaches in terms of a single two-parameter family of generalized logarithms Graphic and a scale transformation. This result now raises the question of how Graphic is related to the two-parameter logarithms associated with the (c, d) entropies in Eq. 1 (6), and will further clarify the role of the scale transformations.

Graphic Logarithm and (c, d) Entropy

Generalized entropies can be classified with respect to their asymptotic scaling behavior in terms of two scaling exponents, c and d, where 0 < c ≤ 1 and d is a real number (6); they are obtained from the scaling relationsEmbedded Imagewhere s is the summand in Eq. 2. Using Eq. 19, de l’Hôpital’s rule, and the fact that s′(x) = −Λ(x), we find the exponents (c, d) for a given Λ ∈ ℒEmbedded Imagewhere we represent Λ as Graphic. In this way we get the dependence of (c, d) as a function of (ν+, ν−), h, and the scale transformation g. We first compute the asymptotic properties of h and g, defining the exponents ch,g and dh,g byEmbedded Imagewhere φh,g = 1 + h ○log ○g(x). Note that log ○g ∈ ℒ0,0. By defining Λ0 ≡ log ○g, we compute its scaling exponents c0 and d0Embedded Image

With these preparations one can derive the resultsEmbedded ImageEmbedded Imagewhich demonstrate clearly that, given a fixed h, c is controlled by ν−, (for ν+ = 0 and c0 = 1) and d is determined by the scale transformation.

Examples

Example 1.

A simple choice for h:

For example, fix h(x) = tanh(x). From Eq. 18 we get for the generalized logarithmEmbedded Image

The associated generalized exponential (inverse of the generalized logarithm) isEmbedded Image

Example 2.

Power laws:

By setting h(x) = tanh(x) and ν+ = 0, we get from Eq. 24 the so-called q-logarithm, with Graphic, where 0 ≤ q = 1 − ν− ≤ 1. The dual is Graphic, and we recover the well-known duality for q-logarithms. It is also well known that logq results from the use of escort distributions (12, 13, 10), whereas log2−q is a natural result of the HT approach (8, 9).

An example of a generalized logarithm that is not a power is obtained by taking Graphic in Eq. 24. One obtains Graphic, with the dual Graphic.

Example 3.

Scale transformations:

Any proper generalized logarithm can be written as a composition of a representative logarithm from Eq. 18 and a scale transformation, with Graphic. For example, pick Λ0,0(x) = log(x), and Graphic, where d > 0 is a parameter of g. The generalized logarithm then becomesEmbedded Image

The associated generalized exponential is a stretched exponential, Graphic, which is the known result for (c, d) entropies with c = 1 and d > 0 (6, 14).

Example 4.

Different choices for h:

Suppose that a physical situation demands a specific Λ, and two observers, A and B, choose to represent Λ differently. Observer A chooses Graphic to represent Λ, so that Graphic, and observer B chooses hB(x) = tanh(x) to represent Graphic. Then Graphic and Graphic can only differ by a scale transformation Graphic with Graphic, and it follows that Graphic. For the particular functions hA and hB we have chosen, we get Graphic.

Discussion

By studying the two types of entropies that are related to the two possible ways to formulate a maximum entropy principle for systems that explicitly violate the fourth SK axiom, we find that there exists a unique duality that relates the two entropies. Consequently, thermodynamic properties derived from those two entropies will also be related through the duality. We show that the maximum and minimum of ΛHT determine a unique value ν* for which Graphic is the dual of ΛHT. In this way it is possible for an object such as ΛHT, which does not explicitly carry an index ν, to become dual to an object that does, such as ΛTS,ν. The existence of this duality opens the way to characterizing all possible generalized logarithms as compositions of a specific functional form Graphic and scale transformations g. We derive the explicit form of Graphic and show that these logarithms are one-to-one related to two asymptotic scaling exponents (c, d) that allow one to characterize strongly nonergodic or non-Markovian systems in their thermodynamic limit (6). ν− is shown to be directly related to c, and the form of the scale transformation g determines d. In summary, we provide a complete theory of all generalized logarithms that can arise as a consequence of the violation of the fourth SK axiom.

Acknowledgments

R.H. and S.T. thank the Santa Fe Institute and M.G.-M. thanks the Aspen Center for Physics for their hospitality. Support for this work was provided in part by National Science Foundation Grant 1066293, Insight Venture Partners, and the Bryan J. and June B. Zwan Foundation (M.G.-M.).

Footnotes

  • ↵1To whom correspondence should be addressed. E-mail: mgm{at}santafe.edu.
  • Author contributions: R.H., S.T., and M.G.-M. designed research, performed research, and wrote the paper.

  • The authors declare no conflict of interest.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1216885109/-/DCSupplemental.

  • ↵†Shannon–Khinchin axioms: (i) Entropy is a continuous function of the probabilities pi only, i.e., s should not explicitly depend on any other parameters. (ii) Entropy is maximal for the equidistribution pi = 1/W; from this, the concavity of s follows. (iii) Adding a state W + 1 to a system with pW + 1 = 0 does not change the entropy of the system; from this, s(0) = 0 follows. (iv) Entropy of a system composed of two subsystems, A and B, is S(A + B) = S(A) + S(B|A).

Freely available online through the PNAS open access option.

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Generalized entropies and logarithms
Rudolf Hanel, Stefan Thurner, Murray Gell-Mann
Proceedings of the National Academy of Sciences Nov 2012, 109 (47) 19151-19154; DOI: 10.1073/pnas.1216885109

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Generalized entropies and logarithms
Rudolf Hanel, Stefan Thurner, Murray Gell-Mann
Proceedings of the National Academy of Sciences Nov 2012, 109 (47) 19151-19154; DOI: 10.1073/pnas.1216885109
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