Physics:Kaniadakis statistics

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Short description: Statistical physics approach

Kaniadakis statistics (also known as κ-statistics) is a generalization of Boltzmann–Gibbs statistical mechanics,[1] based on a relativistic[2][3][4] generalization of the classical Boltzmann–Gibbs–Shannon entropy (commonly referred to as Kaniadakis entropy or κ-entropy). Introduced by the Greek Italian physicist Giorgio Kaniadakis in 2001,[5] κ-statistical mechanics preserve the main features of ordinary statistical mechanics and have attracted the interest of many researchers in recent years. The κ-distribution is currently considered one of the most viable candidates for explaining complex physical,[6][7] natural or artificial systems involving power-law tailed statistical distributions. Kaniadakis statistics have been adopted successfully in the description of a variety of systems in the fields of cosmology,[8][9][10] astrophysics,[11][12] condensed matter, quantum physics,[13][14] seismology,[15][16] genomics,[17][18] economics,[19][20] epidemiology,[21] and many others.

Mathematical formalism

The mathematical formalism of κ-statistics is generated by κ-deformed functions, especially the κ-exponential function.

κ-exponential function

Plot of the κ-exponential function expκ(x) for three different κ-values. The solid black curve corresponding to the ordinary exponential function exp(x) (κ=0).

The Kaniadakis exponential (or κ-exponential) function is a one-parameter generalization of an exponential function, given by:

expκ(x)={(1+κ2x2+κx)1κif 0<κ<1.exp(x)if κ=0,

with expκ(x)=expκ(x).

The κ-exponential for 0<κ<1 can also be written in the form:

expκ(x)=exp(1κarcsinh(κx)).

The first five terms of the Taylor expansion of

expκ(x)

are given by:

expκ(x)=1+x+x22+(1κ2)x33!+(14κ2)x44!+

where the first three are the same as a typical exponential function.

Basic properties

The κ-exponential function has the following properties of an exponential function:

expκ(x)()
ddxexpκ(x)>0
d2dx2expκ(x)>0
expκ()=0+
expκ(0)=1
expκ(+)=+
expκ(x)expκ(x)=1

For a real number r, the κ-exponential has the property:

[expκ(x)]r=expκ/r(rx).

κ-logarithm function

Plot of the κ-logarithmic function lnκ(x) for three different κ-values. The solid black curve corresponding to the ordinary logarithmic function ln(x) (κ=0).

The Kaniadakis logarithm (or κ-logarithm) is a relativistic one-parameter generalization of the ordinary logarithm function,

lnκ(x)={xκxκ2κif 0<κ<1,ln(x)if κ=0,

with lnκ(x)=lnκ(x), which is the inverse function of the κ-exponential:

lnκ(expκ(x))=expκ(lnκ(x))=x.

The κ-logarithm for 0<κ<1 can also be written in the form:

lnκ(x)=1κsinh(κln(x))

The first three terms of the Taylor expansion of lnκ(x) are given by:

lnκ(1+x)=xx22+(1+κ22)x33

following the rule

lnκ(1+x)=n=1bn(κ)(1)n1xnn

with b1(κ)=1, and

bn(κ)(x)={1if n=1,12(1κ)(1κ2)...(1κn1),+12(1+κ)(1+κ2)...(1+κn1)for n>1,

where bn(0)=1 and bn(κ)=bn(κ). The two first terms of the Taylor expansion of lnκ(x) are the same as an ordinary logarithmic function.

Basic properties

The κ-logarithm function has the following properties of a logarithmic function:

lnκ(x)(+)
ddxlnκ(x)>0
d2dx2lnκ(x)<0
lnκ(0+)=
lnκ(1)=0
lnκ(+)=+
lnκ(1/x)=lnκ(x)

For a real number r, the κ-logarithm has the property:

lnκ(xr)=rlnrκ(x)

κ-Algebra

κ-sum

For any x,y and |κ|<1, the Kaniadakis sum (or κ-sum) is defined by the following composition law:

xκy=x1+κ2y2+y1+κ2x2,

that can also be written in form:

xκy=1κsinh(arcsinh(κx)+arcsinh(κy)),

where the ordinary sum is a particular case in the classical limit κ0: x0y=x+y.

The κ-sum, like the ordinary sum, has the following properties:

1. associativity:(xκy)κz=xκ(yκz)
2. neutral element:xκ0=0κx=x
3. opposite element:xκ(x)=(x)κx=0
4. commutativity:xκy=yκx

The κ-difference κ is given by xκy=xκ(y).

The fundamental property expκ(x)expκ(x)=1 arises as a special case of the more general expression below: expκ(x)expκ(y)=expκ(xκy)

Furthermore, the κ-functions and the κ-sum present the following relationships:

lnκ(xy)=lnκ(x)κlnκ(y)

κ-product

For any x,y and |κ|<1, the Kaniadakis product (or κ-product) is defined by the following composition law:

xκy=1κsinh(1κarcsinh(κx)arcsinh(κy)),

where the ordinary product is a particular case in the classical limit κ0: x0y=x×y=xy.

The κ-product, like the ordinary product, has the following properties:

1. associativity:(xκy)κz=xκ(yκz)
2. neutral element:xκI=Iκx=xforI=κ1sinhκκx=x
3. inverse element:xκx=xκx=Iforx=κ1sinh(κ2/arcsinh(κx))
4. commutativity:xκy=yκx

The κ-division κ is given by xκy=xκy.

The κ-sum κ and the κ-product κ obey the distributive law: zκ(xκy)=(zκx)κ(zκy).

The fundamental property lnκ(1/x)=lnκ(x) arises as a special case of the more general expression below:

lnκ(xy)=lnκ(x)κlnκ(y)
Furthermore, the κ-functions and the κ-product present the following relationships:
expκ(x)κexpκ(y)=expκ(x+y)
lnκ(xκy)=lnκ(x)+lnκ(y)

κ-Calculus

κ-Differential

The Kaniadakis differential (or κ-differential) of x is defined by:

dκx=dx1+κ2x2.

So, the κ-derivative of a function f(x) is related to the Leibniz derivative through:

df(x)dκx=γκ(x)df(x)dx,

where γκ(x)=1+κ2x2 is the Lorentz factor. The ordinary derivative df(x)dx is a particular case of κ-derivative df(x)dκx in the classical limit κ0.

κ-Integral

The Kaniadakis integral (or κ-integral) is the inverse operator of the κ-derivative defined through

dκxf(x)=dx1+κ2x2f(x),

which recovers the ordinary integral in the classical limit κ0.

κ-Trigonometry

κ-Cyclic Trigonometry

Plot of the κ-sine and κ-cosine functions for {\displaystyle \kappa =0} (black curve) and {\displaystyle \kappa =0.1} (blue curve).
[click on the figure] Plot of the κ-sine and κ-cosine functions for κ=0 (black curve) and κ=0.1 (blue curve).

The Kaniadakis cyclic trigonometry (or κ-cyclic trigonometry) is based on the κ-cyclic sine (or κ-sine) and κ-cyclic cosine (or κ-cosine) functions defined by:

sinκ(x)=expκ(ix)expκ(ix)2i,
cosκ(x)=expκ(ix)+expκ(ix)2,

where the κ-generalized Euler formula is

expκ(±ix)=cosκ(x)±isinκ(x).:

The κ-cyclic trigonometry preserves fundamental expressions of the ordinary cyclic trigonometry, which is a special case in the limit κ → 0, such as:

cosκ2(x)+sinκ2(x)=1
sinκ(xκy)=sinκ(x)cosκ(y)+cosκ(x)sinκ(y).

The κ-cyclic tangent and κ-cyclic cotangent functions are given by:

tanκ(x)=sinκ(x)cosκ(x)
cotκ(x)=cosκ(x)sinκ(x).

The κ-cyclic trigonometric functions become the ordinary trigonometric function in the classical limit κ0.

κ-Inverse cyclic function

The Kaniadakis inverse cyclic functions (or κ-inverse cyclic functions) are associated to the κ-logarithm:

arcsinκ(x)=ilnκ(1x2+ix),
arccosκ(x)=ilnκ(x21+x),
arctanκ(x)=ilnκ(1ix1+ix),
arccotκ(x)=ilnκ(ix+1ix1).

κ-Hyperbolic Trigonometry

The Kaniadakis hyperbolic trigonometry (or κ-hyperbolic trigonometry) is based on the κ-hyperbolic sine and κ-hyperbolic cosine given by:

sinhκ(x)=expκ(x)expκ(x)2,
coshκ(x)=expκ(x)+expκ(x)2,

where the κ-Euler formula is

expκ(±x)=coshκ(x)±sinhκ(x).

The κ-hyperbolic tangent and κ-hyperbolic cotangent functions are given by:

tanhκ(x)=sinhκ(x)coshκ(x)
cothκ(x)=coshκ(x)sinhκ(x).

The κ-hyperbolic trigonometric functions become the ordinary hyperbolic trigonometric functions in the classical limit κ0.

From the κ-Euler formula and the property expκ(x)expκ(x)=1 the fundamental expression of κ-hyperbolic trigonometry is given as follows:

coshκ2(x)sinhκ2(x)=1

κ-Inverse hyperbolic function

The Kaniadakis inverse hyperbolic functions (or κ-inverse hyperbolic functions) are associated to the κ-logarithm:

arcsinhκ(x)=lnκ(1+x2+x),
arccoshκ(x)=lnκ(x21+x),
arctanhκ(x)=lnκ(1+x1x),
arccothκ(x)=lnκ(1x1+x),

in which are valid the following relations:

arcsinhκ(x)=sign(x)arccoshκ(1+x2),
arcsinhκ(x)=arctanhκ(x1+x2),
arcsinhκ(x)=arccothκ(1+x2x).

The κ-cyclic and κ-hyperbolic trigonometric functions are connected by the following relationships:

sinκ(x)=isinhκ(ix),
cosκ(x)=coshκ(ix),
tanκ(x)=itanhκ(ix),
cotκ(x)=icothκ(ix),
arcsinκ(x)=iarcsinhκ(ix),
arccosκ(x)iarccoshκ(ix),
arctanκ(x)=iarctanhκ(ix),
arccotκ(x)=iarccothκ(ix).

Kaniadakis entropy

The Kaniadakis statistics is based on the Kaniadakis κ-entropy, which is defined through:

Sκ(p)=ipilnκ(pi)=ipilnκ(1pi)

where p={pi=p(xi);x;i=1,2,...,N;ipi=1} is a probability distribution function defined for a random variable X, and 0|κ|<1 is the entropic index.

The Kaniadakis κ-entropy is thermodynamically and Lesche stable[22][23] and obeys the Shannon-Khinchin axioms of continuity, maximality, generalized additivity and expandability.

Kaniadakis distributions

A Kaniadakis distribution (or κ-distribution) is a probability distribution derived from the maximization of Kaniadakis entropy under appropriate constraints. In this regard, several probability distributions emerge for analyzing a wide variety of phenomenology associated with experimental power-law tailed statistical distributions.

κ-Exponential distribution

κ-Gaussian distribution

κ-Gamma distribution

κ-Weibull distribution

κ-Logistic distribution

Kaniadakis integral transform

κ-Laplace Transform

The Kaniadakis Laplace transform (or κ-Laplace transform) is a κ-deformed integral transform of the ordinary Laplace transform. The κ-Laplace transform converts a function f of a real variable t to a new function Fκ(s) in the complex frequency domain, represented by the complex variable s. This κ-integral transform is defined as:[24]

Fκ(s)=κ{f(t)}(s)=0f(t)[expκ(t)]sdt

The inverse κ-Laplace transform is given by:

f(t)=κ1{Fκ(s)}(t)=12πicic+iFκ(s)[expκ(t)]s1+κ2t2ds

The ordinary Laplace transform and its inverse transform are recovered as κ0.

Properties

Let two functions f(t)=κ1{Fκ(s)}(t) and g(t)=κ1{Gκ(s)}(t), and their respective κ-Laplace transforms Fκ(s) and Gκ(s), the following table presents the main properties of κ-Laplace transform:[24]

Properties of the κ-Laplace transform
Property f(t) Fκ(s)
Linearity af(t)+bg(t) aFκ(s)+bGκ(s)
Time scaling f(at) 1aFκ/a(sa)
Frequency shifting f(t)[expκ(t)]a Fκ(sa)
Derivative df(t)dt sκ{f(t)1+κ2t2}(s)f(0)
Derivative ddt1+κ2t2f(t) sFκ(s)f(0)
Time-domain integration 11+κ2t20tf(w)dw 1sFκ(s)
f(t)[ln(expκ(t))]n (1)ndnFκ(s)dsn
f(t)[ln(expκ(t))]n s+dwnwn+dwn1...w3+dw2w2+dw1Fκ(w1)
Dirac delta-function δ(tτ) [expκ(τ)]s
Heaviside unit function u(tτ) s1+κ2τ2+κ2τs2κ2[expκ(τ)]s
Power function tν1 s2s2κ2ν2Γκs(ν+1)νsν=ss+|κ|νΓ(ν)|2κ|νΓ(s|2κ|ν2)Γ(s|2κ|+ν2)
Power function t2m1,  mZ+ (2m1)!j=1m[s2(2j)2κ2]
Power function t2m,  mZ+ (2m)!sj=1m+1[s2(2j1)2κ2]

The κ-Laplace transforms presented in the latter table reduce to the corresponding ordinary Laplace transforms in the classical limit κ0.

κ-Fourier Transform

The Kaniadakis Fourier transform (or κ-Fourier transform) is a κ-deformed integral transform of the ordinary Fourier transform, which is consistent with the κ-algebra and the κ-calculus. The κ-Fourier transform is defined as:[25]

κ[f(x)](ω)=12π+f(x)expκ(xκω)idκx

which can be rewritten as

κ[f(x)](ω)=12π+f(x)exp(ix{κ}ω{κ})1+κ2x2dx

where x{κ}=1κarcsinh(κx) and ω{κ}=1κarcsinh(κω). The κ-Fourier transform imposes an asymptotically log-periodic behavior by deforming the parameters x and ω in addition to a damping factor, namely 1+κ2x2.

Real (top panel) and imaginary (bottom panel) part of the kernel hκ(x,ω) for typical κ-values and ω=1.

The kernel of the κ-Fourier transform is given by:

hκ(x,ω)=exp(ix{κ}ω{κ})1+κ2x2

The inverse κ-Fourier transform is defined as:[25]

κ[f^(ω)](x)=12π+f^(ω)expκ(ωκx)idκω

Let uκ(x)=1κcosh(κln(x)), the following table shows the κ-Fourier transforms of several notable functions:[25]

κ-Fourier transform of several functions
f(x) κ[f(x)](ω)
Step function θ(x) 2πδ(ω)+12πiω{κ}
Modulation cosκ(aκx) π2uκ(expκ(a))(δ(ω+a)+δ(ωa))
Causal κ-exponential θ(x)expκ(aκx) 12π1a{κ}+iω{κ}
Symmetric κ-exponential expκ(aκ|x|) 2πa{κ}a{κ}2+ω{κ}2
Constant 1 2πδ(ω)
κ-Phasor expκ(aκx)i 2πuκ(expκ(a))δ(ωa)
Impuslse δ(xa) 12πexpκ(ωκa)iuκ(expκ(a))
Signum Sgn(x) 2π1iω{κ}
Rectangular Π(xa) 2πa{κ}sincκ(ωκa)

The κ-deformed version of the Fourier transform preserves the main properties of the ordinary Fourier transform, as summarized in the following table.

κ-Fourier properties
f(x) κ[f(x)](ω)
Linearity κ[αf(x)+βg(x)](ω)=ακ[f(x)](ω)+βκ[g(x)](ω)
Scaling κ[f(αx)](ω)=1ακ[f(x)](ω)
where κ=κ/α and ω=(a/κ)sinh(arcsinh(κω)/a2)
κ-Scaling κ[f(ακx)](ω)=1α{κ}κ[f(x)](1ακω)
Complex conjugation κ[f(x)](ω)=κ[f(x)](ω)
Duality κ[κ[f(x)](ν)](ω)=f(ω)
Reverse κ[f(x)](ω)=κ[f(x)](ω)
κ-Frequency shift κ[expκ(ω0κx)if(x)](ω)=κ[f(x)](ωκω0)
κ-Time shift κ[f(xκx0)](ω)=expκ(ωκx0)iκ[f(x)](ω)
Transform of κ-derivative κ[df(x)dκx](ω)=iω{κ}κ[f(x)](ω)
κ-Derivative of transform ddκωκ[f(x)](ω)=iω{κ}κ[x{κ}f(x)](ω)
Transform of integral κ[xf(y)dy](ω)=1iω{κ}κ[f(x)](ω)+2πκ[f(x)](0)δ(ω)
κ-Convolution κ[(fκg)(x)](ω)=2πκ[f(x)](ω)κ[g(x)](ω)
where (fκg)(x)=+f(y)g(xκy)dκy
Modulation κ[f(x)g(x)](ω)=12π(κ[f(x)]κκ[g(x)])(ω)

The properties of the κ-Fourier transform presented in the latter table reduce to the corresponding ordinary Fourier transforms in the classical limit κ0.

See also

References

  •  This article incorporates text available under the CC BY 3.0 license.
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