Nonextensive Statistical Mechanics: a Brief Review of Its Present Status

Anais da Academia Brasileira de Ciências (2002) 74(3): 393–414 (Annals of the Brazilian Academy of Sciences) ISSN 0001-3765 www.scielo.br/aabc Nonextensive statistical mechanics: a brief review of its present status CONSTANTINO TSALLIS* Centro Brasileiro de Pesquisas Físicas, 22290-180 Rio de Janeiro, Brazil Centro de Fisica da Materia Condensada, Universidade de Lisboa P-1649-003 Lisboa, Portugal Manuscript received on May 25, 2002; accepted for publication on May 27, 2002. ABSTRACT We briefly review the present status of nonextensive statistical mechanics. We focus on (i) the central equations of the formalism, (ii) the most recent applications in physics and other sciences, (iii) the a priori determination (from microscopic dynamics) of the entropic index q for two important classes of physical systems, namely low-dimensional maps (both dissipative and conservative) and long-range interacting many-body hamiltonian classical systems. Key words: nonextensive statistical mechanics, entropy, complex systems. 1 CENTRAL EQUATIONS OF NONEXTENSIVE STATISTICAL MECHANICS Nonextensive statistical mechanics and thermodynamics were introduced in 1988 [1], and further developed in 1991 [2] and 1998 [3], with the aim of extending the domain of applicability of statistical mechanical procedures to systems where Boltzmann-Gibbs (BG) thermal statistics and standard thermodynamics present serious mathematical difficulties or just plainly fail. Indeed, a rapidly increasing number of systems are pointed out in the literature for which the usual functions appearing in BG statistics appear to be violated. Some of these cases are satisfactorily handled within the formalism we are here addressing (see [4] for reviews and [5] for a regularly updated bibliography which includes crucial contributions and clarifications that many scientists have given along the years). Let us start by just reminding the central equations. First of all, the exponential function ex is generalized into the q-exponential function 1 x −q eq ≡[1 + (1 − q)x] 1 (q ∈ R). (1) *Member of Academia Brasileira de Ciências E-mail: [email protected] An Acad Bras Cienc (2002) 74 (3) 394 CONSTANTINO TSALLIS We can trivially verify that this (nonnegative and monotonically increasing) function (i) for q → 1 ex = ex(∀ x) q> x →−∞ yields 1 , (ii) for 1, vanishes as a power-law when and diverges at x = 1/(q − 1), and (iii) for q<1, has a cutoff at x =−1/(1 − q), below which it is defined to x be identically zero. If x → 0wehaveeq ∼ 1 + x(∀ q). The inverse function of the q-exponential is the q-logarithm, defined as follows: x1−q − 1 lnq x ≡ (q ∈ R). (2) 1 − q Of course ln1 x = ln x(∀ x).Ifx → 1wehavelnq x ∼ x − 1(∀ q). The nonextensive entropic form we postulate is − W pq W 1 i=1 i Sq = k pi = 1; q ∈ R , (3) q − 1 i=1 where W is the total number of microscopic configurations, whose probabilities are {pi}. Without k = q → loss of generality we shall from now on assume 1. We can verify that, for 1, this S =− W p p entropy reproduces the usual Boltzmann-Gibbs-Shannon one, namely 1 i=1 i ln i. The continuous and the quantum expressions of Sq are respectively given by 1 − dx[p(x)]q Sq = (4) q − 1 and 1 − Trρq Sq = , (5) q − 1 where ρ is the matrix density. Unless specifically declared in what follows, we shall be using the form of Eq. (3). It is easy to verify that all its generic properties can be straightforwardly adapted to both the continuous and quantum cases. Sq can be written as 1 Sq = lnq , (6) pi (...)≡ W p (...) where the expectation value i=1 i . It can also be written as Sq =−lnq piq , (7) (...) ≡ W pq (...) where the unnormalized q-expectation value is defined to be q i=1 i . Of course (...)1 =(...). This is a good point for defining also the normalized q-expectation value W pq (...) i=1 i (...)q ≡ , (8) W pq i=1 i An Acad Bras Cienc (2002) 74 (3) NONEXTENSIVE STATISTICAL MECHANICS 395 which naturally emerges in the formalism. We verify trivially that (...)1 =(...)1 =(...), and also that (...)q =(...)q /1q . A+B A B If A and B are two independent systems (i.e., pij = pi pj ∀ (i, j)), then we have that Sq (A + B) = Sq (A) + Sq (B) + (1 − q)Sq (A)Sq (B) . (9) It is from this property that the name nonextensive statistical mechanics was coined. The cases q<1 and q>1 respectively correspond to superextensivity and subextensivity of Sq since in all cases Sq ≥ 0. At equiprobability, i.e., pi = 1/W, we obtain Sq = lnq W, (10) which is the basis for the microcanonical ensemble. For the thermal equilibrium corresponding to the canonical ensemble of a Hamiltonian system, S W p = = U { } we optimize q with the constraints i=1 i 1 and i q q , where i are the eigenvalues of the Hamiltonian of the system, and Uq is the generalized internal energy. We obtain [3] e−β(i −Uq ) p = q ∝ 1 ∝ 1 , i 1 1 (11) Zq q− q− 1 + (q − 1)β(i − Uq ) 1 1 + (q − 1)β i 1 W −β(j −Uq ) where β is the Lagrange parameter, Zq ≡ j=q eq and β a well defined function of β. For q = 1 we recover the celebrated BG weight. When β>0 and the energy i increases, the q> q< probability decays like a power law for 1 and exhibits a cutoff for 1. Analogously, if we optimize Sq as given by Eq. (4) with the constraints dxp(x) = 1 and 2 2 x q = σ (σ > 0), we obtain the q-generalization of the Gaussian distribution, namely [6] −βx¯ 2 eq 1 pq (x) = ∝ (q < ), −βy¯ 2 1 3 (12) ¯ q− dyeq [1 + (q − 1)βx2] 1 where β¯ can be straightforward and explicitly related to σ. The variance of these distributions is finite if q<5/3 and diverges if 5/3 <q<3. For q = 2 we have the Lorentzian distribution. For q ≥ 3 the function is not normalizable, and therefore is unacceptable as a distribution of probabilities. Let us now address typical time dependences. Let us assume that ξ(t)is a quantity characteriz- ing an exponential behavior and satisfying ξ(0) = 1. Such is the typical case for the sensitivity to the initial conditions of a one-dimensional chaotic system, where ξ(t) ≡ limx(0)→0[x(t)/x(0)], where x(t) is the discrepancy at time t of two trajectories which, at t = 0, started at x(0) and at x (0). Another example is a population which relaxes to zero. If N(t) is the number of elements, then we can define ξ(t) ≡ N(t)/N(0). The quantity ξ(t) monotonically increases in our first An Acad Bras Cienc (2002) 74 (3) 396 CONSTANTINO TSALLIS example (sensitivity), whereas it decreases in the second one (relaxation). The basic equation that ξ satisfies is generically ˙ ξ = λ1ξ, (13) λ1t hence ξ(t) = e . In our example of the chaotic system, λ1 is the Lyapunov exponent. In our population example, we have λ1 ≡−1/τ1, where τ1 is the relaxation time. What happens in the marginal case λ1 = 0? Typically we have ˙ q ξ = λq ξ , (14) hence λ t 1 1 ξ = e q = + ( − q)λ t 1−q = . q 1 1 q 1 (15) q− 1 + (q − 1)(−λq )t 1 This quantity monotonically increases if λq > 0 and q<1, and decreases if λq ≡−1/τq < 0 and q>1. In both cases it does so as a power law, instead of exponentially. In the limit t → 0, we have ξ ∼ 1 + λq t(∀q). A more general situation might occur when both λ1 and λq are different from zero. In such case, many phenomena will be described by the following differential equation: ˙ q ξ = λ1ξ + (λq − λ1)ξ , (16) hence 1 −q λq λq ( −q)λ t 1 ξ = 1 − + e 1 1 . (17) λ1 λ1 1 −q If q<1 and 0 <λ1 << λq , ξ increases linearly with t for small times, as t 1 for intermediate λ1t times, and like e for large times. If q>0 and 0 >λ1 >> λq , ξ decreases linearly with t for 1 −|λ |t small times, as 1/t q−1 for intermediate times, and like e 1 for large times. 2 APPLICATIONS IN AND OUT FROM EQUILIBRIUM A considerable amount of applications and connections have been advanced in the literature using, in a variety of manners, the above formalism. They concern physics, astrophysics, geophysics, chemistry, biology, mathematics, economics, linguistics, engineering, medicine, physiology, cog- nitive psychology, sports and others [5]. It seems appropriate to say that the fact that the range of applications is so wide probably is deeply related to and reflects the ubiquity of self-organized criticality [7], fractal structures [8] and, ultimately, power laws in nature. In particular, a natural arena for this statistical mechanics appears to be the so called complex systems [9]. We shall briefly review here four recent applications, namely fully developed turbulence [10- 12], hadronic jets produced by electron-positron annihilation [13], motion of Hydra viridissima [14], and quantitative linguistics [15]. An Acad Bras Cienc (2002) 74 (3) NONEXTENSIVE STATISTICAL MECHANICS 397 Fully developed turbulence: As early as in 1996 Boghosian made the first application of the present formalism to turbulence [16]. That was for plasma. What we shall instead focus on here is fully developed turbulence in normal fluids. Ramos et al advanced in 1999 [10] the possibility of nonextensive statistical mechanics being useful for such systems.

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