# Fractional calculus

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"Fractional derivative" redirects here.

Fractional calculus is a branch of mathematical analysis that studies the possibility of taking real number powers or complex number powers of the differentiation operator

$D={\dfrac {d}{dx}},$ and the integration operator J. (Usually J is used instead of I to avoid confusion with other I-like glyphs and identities.)

In this context, the term powers refers to iterative application of a linear operator acting on a function, in some analogy to function composition acting on a variable, e.g., f 2(x) = f(f(x)). For example, one may ask the question of meaningfully interpreting

${\sqrt {D}}=D^{\frac {1}{2}}$ as an analog of the functional square root for the differentiation operator (an operator half iterated), i.e., an expression for some linear operator that when applied twice to any function will have the same effect as differentiation.

More generally, one can look at the question of defining the linear functional

$D^{a}$ for real-number values of a in such a way that when a takes an integer value, n, the usual power of n-fold differentiation is recovered for n > 0, and the −nth power of J when n < 0.

The motivation behind this extension to the differential operator is that the semigroup of powers Da will form a continuous semigroup with parameter a, inside which the original discrete semigroup of Dn for integer n can be recovered as a subgroup. Continuous semigroups are prevalent in mathematics, and have an interesting theory. Notice here that fraction is then a misnomer for the exponent a, since it need not be rational; the use of the term fractional calculus is merely conventional.

Fractional differential equations (also known as extraordinary differential equations) are a generalization of differential equations through the application of fractional calculus.

## Nature of the fractional derivative

An important point is that the fractional derivative at a point x is a local property only when a is an integer; in non-integer cases we cannot say that the fractional derivative at x of a function f depends only on values of f very near x, in the way that integer-power derivatives certainly do. Therefore it is expected that the theory involves some sort of boundary conditions, involving information on the function further out. To use a metaphor, the fractional derivative requires some peripheral vision.

As far as the existence of such a theory is concerned, the foundations of the subject were laid by Liouville in a paper from 1832. The fractional derivative of a function to order a is often now defined by means of the Fourier or Mellin integral transforms.

## Heuristics

A fairly natural question to ask is whether there exists a linear operator H, or half-derivative, such that

$H^{2}f(x)=Df(x)={\dfrac {d}{dx}}f(x)=f'(x)$ .

It turns out that there is such an operator, and indeed for any a > 0, there exists an operator P such that

$(P^{a}f)(x)=f'(x),$ or to put it another way, the definition of dny/dxn can be extended to all real values of n.

Let f(x) be a function defined for x > 0. Form the definite integral from 0 to x. Call this

$(Jf)(x)=\int _{0}^{x}f(t)\;dt$ .

Repeating this process gives

$(J^{2}f)(x)=\int _{0}^{x}(Jf)(t)dt=\int _{0}^{x}\left(\int _{0}^{t}f(s)\;ds\right)\;dt,$ and this can be extended arbitrarily.

The Cauchy formula for repeated integration, namely

$(J^{n}f)(x)={1 \over (n-1)!}\int _{0}^{x}(x-t)^{n-1}f(t)\;dt,$ leads in a straightforward way to a generalization for real n.

Using the gamma function to remove the discrete nature of the factorial function gives us a natural candidate for fractional applications of the integral operator.

$(J^{\alpha }f)(x)={1 \over \Gamma (\alpha )}\int _{0}^{x}(x-t)^{\alpha -1}f(t)\;dt$ This is in fact a well-defined operator.

It is straightforward to show that the J operator satisfies

$(J^{\alpha })(J^{\beta }f)(x)=(J^{\beta })(J^{\alpha }f)(x)=(J^{\alpha +\beta }f)(x)={1 \over \Gamma (\alpha +\beta )}\int _{0}^{x}(x-t)^{\alpha +\beta -1}f(t)\;dt$ This relationship is called the semigroup property of fractional differintegral operators. Unfortunately the comparable process for the derivative operator D is significantly more complex, but it can be shown that D is neither commutative nor additive in general.{{ safesubst:#invoke:Unsubst||date=__DATE__ |B= {{#invoke:Category handler|main}}{{#invoke:Category handler|main}}[citation needed] }} ## Fractional derivative of a basic power function The half derivative (purple curve) of the function f(x) = x (blue curve) together with the first derivative (red curve). Let us assume that f(x) is a monomial of the form $f(x)=x^{k}\;.$ The first derivative is as usual $f'(x)={\dfrac {d}{dx}}f(x)=kx^{k-1}\;.$ Repeating this gives the more general result that ${\dfrac {d^{a}}{dx^{a}}}x^{k}={\dfrac {k!}{(k-a)!}}x^{k-a}\;,$ Which, after replacing the factorials with the gamma function, leads us to ${\dfrac {d^{a}}{dx^{a}}}x^{k}={\dfrac {\Gamma (k+1)}{\Gamma (k-a+1)}}x^{k-a},\qquad k\geq 0$ ${\dfrac {d^{\frac {1}{2}}}{dx^{\frac {1}{2}}}}x={\dfrac {\Gamma (1+1)}{\Gamma (1-{\frac {1}{2}}+1)}}x^{1-{\frac {1}{2}}}={\dfrac {1!}{\Gamma ({\frac {3}{2}})}}x^{\frac {1}{2}}={\dfrac {2x^{\frac {1}{2}}}{\sqrt {\pi }}}.$ Repeating this process yields ${\dfrac {d^{\frac {1}{2}}}{dx^{\frac {1}{2}}}}{\dfrac {2x^{\frac {1}{2}}}{\sqrt {\pi }}}={\frac {2}{\sqrt {\pi }}}{\dfrac {\Gamma (1+{\frac {1}{2}})}{\Gamma ({\frac {1}{2}}-{\frac {1}{2}}+1)}}x^{{\frac {1}{2}}-{\frac {1}{2}}}={\frac {2}{\sqrt {\pi }}}{\dfrac {\Gamma ({\frac {3}{2}})}{\Gamma (1)}}x^{0}={\dfrac {2{\sqrt {\pi }}x^{0}}{2{\sqrt {\pi }}0!}}=1,$ which is indeed the expected result of $\left({\dfrac {d^{\frac {1}{2}}}{dx^{\frac {1}{2}}}}{\dfrac {d^{\frac {1}{2}}}{dx^{\frac {1}{2}}}}\right)x={\dfrac {d}{dx}}x=1.$ For negative integer power k, the gamma function is undefined and we have to use the following relation: ${\dfrac {d^{a}}{dx^{a}}}x^{-k}=(-1)^{a}{\dfrac {\Gamma (k+a)}{\Gamma (k)}}x^{-(k+a)}$ for $k\geq 0$ This extension of the above differential operator need not be constrained only to real powers. For example, the (1 + i)th derivative of the (1 − i)th derivative yields the 2nd derivative. Also notice that setting negative values for a yields integrals. For a general function f(x) and 0 < α < 1, the complete fractional derivative is $D^{\alpha }f(x)={\frac {1}{\Gamma (1-\alpha )}}{\frac {d}{dx}}\int _{0}^{x}{\frac {f(t)}{(x-t)^{\alpha }}}dt$ For arbitrary α, since the gamma function is undefined for arguments whose real part is a negative integer and whose imaginary part is zero, it is necessary to apply the fractional derivative after the integer derivative has been performed. For example, $D^{\frac {3}{2}}f(x)=D^{\frac {1}{2}}D^{1}f(x)=D^{\frac {1}{2}}{\frac {d}{dx}}f(x)$ ## Laplace transform We can also come at the question via the Laplace transform. Noting that ${\mathcal {L}}\left\{Jf\right\}(s)={\mathcal {L}}\left\{\int _{0}^{t}f(\tau )\,d\tau \right\}(s)={\frac {1}{s}}({\mathcal {L}}\left\{f\right\})(s)$ and ${\mathcal {L}}\left\{J^{2}f\right\}={\frac {1}{s}}({\mathcal {L}}\left\{Jf\right\})(s)={\frac {1}{s^{2}}}({\mathcal {L}}\left\{f\right\})(s)$ etc., we assert $J^{\alpha }f={\mathcal {L}}^{-1}\left\{s^{-\alpha }({\mathcal {L}}\{f\})(s)\right\}$ . For example $J^{\alpha }\left(t^{k}\right)={\mathcal {L}}^{-1}\left\{{\dfrac {\Gamma (k+1)}{s^{\alpha +k+1}}}\right\}={\dfrac {\Gamma (k+1)}{\Gamma (\alpha +k+1)}}t^{\alpha +k}$ as expected. Indeed, given the convolution rule ${\mathcal {L}}\{f*g\}=({\mathcal {L}}\{f\})({\mathcal {L}}\{g\})$ and shorthanding p(x) = xα−1 for clarity, we find that {\begin{aligned}(J^{\alpha }f)(t)&={\frac {1}{\Gamma (\alpha )}}{\mathcal {L}}^{-1}\left\{\left({\mathcal {L}}\{p\}\right)({\mathcal {L}}\{f\})\right\}\\&={\frac {1}{\Gamma (\alpha )}}(p*f)\\&={\frac {1}{\Gamma (\alpha )}}\int _{0}^{t}p(t-\tau )f(\tau )\,d\tau \\&={\frac {1}{\Gamma (\alpha )}}\int _{0}^{t}(t-\tau )^{\alpha -1}f(\tau )\,d\tau \\\end{aligned}} which is what Cauchy gave us above. Laplace transforms "work" on relatively few functions, but they are often useful for solving fractional differential equations. ## Fractional integrals ### Riemann–Liouville fractional integral The classical form of fractional calculus is given by the Riemann–Liouville integral, which is essentially what has been described above. The theory for periodic functions (therefore including the 'boundary condition' of repeating after a period) is the Weyl integral. It is defined on Fourier series, and requires the constant Fourier coefficient to vanish (thus, it applies to functions on the unit circle whose integrals evaluate to 0). $_{a}D_{t}^{-\alpha }f(t)={}_{a}I_{t}^{\alpha }f(t)={\frac {1}{\Gamma (\alpha )}}\int _{a}^{t}(t-\tau )^{\alpha -1}f(\tau )d\tau$ By contrast the Grünwald–Letnikov derivative starts with the derivative instead of the integral. ### Hadamard fractional integral The Hadamard fractional integral is introduced by J. Hadamard  and is given by the following formula, $_{a}\mathbf {D} _{t}^{-\alpha }f(t)={\frac {1}{\Gamma (\alpha )}}\int _{a}^{t}\left(\log {\frac {t}{\tau }}\right)^{\alpha -1}f(\tau ){\frac {d\tau }{\tau }},\qquad t>a.$ ## Fractional derivatives Not like classical Newtonian derivatives, a fractional derivative is defined via a fractional integral. ### Riemann–Liouville fractional derivative The corresponding derivative is calculated using Lagrange's rule for differential operators. Computing n-th order derivative over the integral of order (nα), the α order derivative is obtained. It is important to remark that n is the nearest integer bigger than α. $_{a}D_{t}^{\alpha }f(t)={\frac {d^{n}}{dt^{n}}}{}_{a}D_{t}^{-(n-\alpha )}f(t)={\frac {d^{n}}{dt^{n}}}{}_{a}I_{t}^{n-\alpha }f(t)$ ### Caputo fractional derivative There is another option for computing fractional derivatives; the Caputo fractional derivative. It was introduced by M. Caputo in his 1967 paper. In contrast to the Riemann Liouville fractional derivative, when solving differential equations using Caputo's definition, it is not necessary to define the fractional order initial conditions. Caputo's definition is illustrated as follows. ${}_{a}^{C}D_{t}^{\alpha }f(t)={\frac {1}{\Gamma (n-\alpha )}}\int _{a}^{t}{\frac {f^{(n)}(\tau )d\tau }{(t-\tau )^{\alpha +1-n}}}.$ ## Generalizations ### Erdélyi–Kober operator The Erdélyi–Kober operator is an integral operator introduced by Arthur Erdélyi (1940). and Hermann Kober (1940) and is given by ${\frac {x^{-\nu -\alpha +1}}{\Gamma (\alpha )}}\int _{0}^{x}(t-x)^{\alpha -1}t^{-\alpha -\nu }f(t)dt,$ which generalizes the Riemann fractional integral and the Weyl integral. A recent generalization is the following, which generalizes the Riemann-Liouville fractional integral and the Hadamard fractional integral. It is given by, $\left({}^{\rho }{\mathcal {I}}_{a+}^{\alpha }f\right)(x)={\frac {\rho ^{1-\alpha }}{\Gamma ({\alpha })}}\int _{a}^{x}{\frac {\tau ^{\rho -1}f(\tau )}{(x^{\rho }-\tau ^{\rho })^{1-\alpha }}}\,d\tau ,\qquad x>a.$ ## Functional calculus In the context of functional analysis, functions f(D) more general than powers are studied in the functional calculus of spectral theory. The theory of pseudo-differential operators also allows one to consider powers of D. The operators arising are examples of singular integral operators; and the generalisation of the classical theory to higher dimensions is called the theory of Riesz potentials. So there are a number of contemporary theories available, within which fractional calculus can be discussed. See also Erdélyi–Kober operator, important in special function theory Template:Harv, Template:Harv. ## Applications ### Fractional conservation of mass As described by Wheatcraft and Meerschaert (2008), a fractional conservation of mass equation is needed to model fluid flow when the control volume is not large enough compared to the scale of heterogeneity and when the flux within the control volume is non-linear. In the referenced paper, the fractional conservation of mass equation for fluid flow is: $-\rho \left(\nabla ^{\alpha }\cdot {\vec {u}}\right)=\Gamma (\alpha +1)\Delta x^{1-\alpha }\rho \left(\beta _{s}+\phi \beta _{w}\right){\frac {\partial p}{\partial t}}$ ### Fractional advection dispersion equation This equation has been shown useful for modeling contaminant flow in heterogenous porous media. ### Time-space fractional diffusion equation models Anomalous diffusion processes in complex media can be well characterized by using fractional-order diffusion equation models. The time derivative term is corresponding to long-time heavy tail decay and the spatial derivative for diffusion nonlocality. The time-space fractional diffusion governing equation can be written as ${\frac {\partial ^{\alpha }u}{\partial t^{\alpha }}}=K(-\triangle )^{\beta }u.$ A simple extension of fractional derivative is the variable-order fractional derivative, the α, β are changed into α(x, t), β(x, t). Its applications in anomalous diffusion modeling can be found in reference. ### Structural damping models Fractional derivatives are used to model viscoelastic damping in certain types of materials like polymers. ### Acoustical wave equations for complex media The propagation of acoustical waves in complex media, e.g. biological tissue, commonly implies attenuation obeying a frequency power-law. This kind of phenomenon may be described using a causal wave equation which incorporates fractional time derivatives: $\nabla ^{2}u-{\dfrac {1}{c_{0}^{2}}}{\frac {\partial ^{2}u}{\partial t^{2}}}+\tau _{\sigma }^{\alpha }{\dfrac {\partial ^{\alpha }}{\partial t^{\alpha }}}\nabla ^{2}u-{\dfrac {\tau _{\epsilon }^{\beta }}{c_{0}^{2}}}{\dfrac {\partial ^{\beta +2}u}{\partial t^{\beta +2}}}=0.$ See also  and the references therein. Such models are linked to the commonly recognized hypothesis that multiple relaxation phenomena give rise to the attenuation measured in complex media. This link is further described in  and in the survey paper, as well as the acoustic attenuation article. See  for a recent paper which compares fractional wave equations which model power-law attenuation. ### Fractional Schrödinger equation in quantum theory The fractional Schrödinger equation, a fundamental equation of fractional quantum mechanics discovered by Nick Laskin, has the following form: $i\hbar {\frac {\partial \psi (\mathbf {r} ,t)}{\partial t}}=D_{\alpha }(-\hbar ^{2}\Delta )^{\frac {\alpha }{2}}\psi (\mathbf {r} ,t)+V(\mathbf {r} ,t)\psi (\mathbf {r} ,t).$ where the solution of the equation is the wavefunction ψ(r, t) - the quantum mechanical probability amplitude for the particle to have a given position vector r at any given time t, and ħ is the reduced Planck constant. The potential energy function V(r, t) depends on the system. Further, Δ = {{ safesubst:#invoke:Unsubst||B=2/r2}} is the Laplace operator, and Dα is a scale constant with physical dimension [Dα] = erg1 − α·cmα·secα, (at α = 2, D2 = 1/2m for a particle of mass m), and the operator (−ħ2Δ)α/2 is the 3-dimensional fractional quantum Riesz derivative defined by

$\left(-\hbar ^{2}\Delta \right)^{\frac {\alpha }{2}}\psi (\mathbf {r} ,t)={\frac {1}{(2\pi \hbar )^{3}}}\int d^{3}pe^{{\frac {i}{\hbar }}\mathbf {p} \cdot \mathbf {r} }|\mathbf {p} |^{\alpha }\varphi (\mathbf {p} ,t).$ The index α in the fractional Schrödinger equation is the Lévy index, 1 < α ≤ 2.