Fractional calculus

The classical form of fractional calculus is given by the Riemann–Liouville integral, which is essentially what has been described above. The theory of fractional integration for periodic functions (therefore including the "boundary condition" of repeating after a period) is given by 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 zero). The Riemann–Liouville integral exists in two forms, upper and lower. Considering the interval [a,b], the integrals are defined as

$${\displaystyle {\begin{alignedat}{2}_{a}D_{t}^{-\alpha }f(t)&={}_{a}I_{t}^{\alpha }f(t)&&={\frac {1}{\Gamma (\alpha )}}\int _{a}^{t}\left(t-\tau \right)^{\alpha -1}f(\tau )\,d\tau \\_{t}D_{b}^{-\alpha }f(t)&={}_{t}I_{b}^{\alpha }f(t)&&={\frac {1}{\Gamma (\alpha )}}\int _{t}^{b}\left(\tau -t\right)^{\alpha -1}f(\tau )\,d\tau \end{alignedat}}}$$

Where the former is valid for t > a and the latter is valid for t < b.[12]

It has been suggested[13] that the integral on the positive real axis (i.e. ${\displaystyle a=0}$) would be more appropriately named the Abel–Riemann integral, on the basis of history of discovery and use, and in the same vein the integral over the entire real line be named Liuoville–Weyl integral.

By contrast the Grünwald–Letnikov derivative starts with the derivative instead of the integral.

The Hadamard fractional integral was introduced by Jacques Hadamard[14] and is given by the following formula,

$${\displaystyle _{a}\mathbf {D} _{t}^{-\alpha }f(t)={\frac {1}{\Gamma (\alpha )}}\int _{a}^{t}\left(\log {\frac {t}{\tau }}\right)^{\alpha -1}f(\tau ){\frac {d\tau }{\tau }},\qquad t>a\,.}$$

The Atangana–Baleanu fractional integral of a continuous function is defined as:

$${\displaystyle ^{AB}{}_{a}I_{t}^{\alpha }f(t)={\frac {1-\alpha }{AB(\alpha )}}f(t)+{\frac {\alpha }{AB(\alpha )\Gamma (\alpha )}}\int _{a}^{t}\left(t-\tau \right)^{\alpha -1}f(\tau )\,d\tau }$$

The corresponding derivative is calculated using Lagrange's rule for differential operators. Computing nth order derivative over the integral of order (n − α), the α order derivative is obtained. It is important to remark that n is the smallest integer greater than α (that is, n = ⌈α⌉). The Riemann–Liouville fractional derivative and integral has multiple applications such as in case of solutions to the equation in the case of multiple systems such as the tokamak systems, and Variable order fractional parameter.[15][16] Similar to the definitions for the Riemann–Liouville integral, the derivative has upper and lower variants.[17]

$${\displaystyle {\begin{alignedat}{2}_{a}D_{t}^{\alpha }f(t)&={\frac {d^{n}}{dt^{n}}}{}_{a}D_{t}^{-(n-\alpha )}f(t)&&={\frac {d^{n}}{dt^{n}}}{}_{a}I_{t}^{n-\alpha }f(t)\\_{t}D_{b}^{\alpha }f(t)&={\frac {d^{n}}{dt^{n}}}{}_{t}D_{b}^{-(n-\alpha )}f(t)&&={\frac {d^{n}}{dt^{n}}}{}_{t}I_{b}^{n-\alpha }f(t)\end{alignedat}}}$$

Another option for computing fractional derivatives is the Caputo fractional derivative. It was introduced by Michele Caputo in his 1967 paper.[18] 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, where again n = ⌈α⌉:

$${\displaystyle {}^{C}D_{t}^{\alpha }f(t)={\frac {1}{\Gamma (n-\alpha )}}\int _{0}^{t}{\frac {f^{(n)}(\tau )}{\left(t-\tau \right)^{\alpha +1-n}}}\,d\tau .}$$

There is the Caputo fractional derivative defined as:

$${\displaystyle {}D^{\nu }f(t)={\frac {1}{\Gamma (n-\nu )}}\int _{0}^{t}(t-u)^{(n-\nu -1)}f^{(n)}(u)\,du\qquad (n-1)<\nu <n}$$

which has the advantage that is zero when f(t) is constant and its Laplace Transform is expressed by means of the initial values of the function and its derivative. Moreover, there is the Caputo fractional derivative of distributed order defined as

$${\displaystyle {}_{a}^{b}D^{\nu }f(t)=\int _{a}^{b}\phi (\nu )\left[D^{(\nu )}f(t)\right]\,d\nu =\int _{a}^{b}\left[{\frac {\phi (\nu )}{\Gamma (1-\nu )}}\int _{0}^{t}\left(t-u\right)^{-\nu }f'(u)\,du\right]\,d\nu }$$

where φ(v) is a weight function and which is used to represent mathematically the presence of multiple memory formalisms.

In a paper of 2015, M. Caputo and M. Fabrizio presented a definition of fractional derivative with a non singular kernel, for a function ${\displaystyle f(t)}$ of ${\displaystyle C^{1}}$ given by:

$${\displaystyle _{a}^{CF}D_{t}^{\alpha }f(t)={\frac {1}{1-\alpha }}\int _{a}^{t}f'(\tau )\ e^{\left(-\alpha {\frac {t-\tau }{1-\alpha }}\right)}\ d\tau ,}$$

where ${\displaystyle a<0,\alpha \in (0,1]}$[19]

In 2016, Atangana and Baleanu suggested differential operators based on the generalized Mittag-Leffler function. The aim was to introduce fractional differential operators with non-singular nonlocal kernel. Their fractional differential operators are given below in Riemann–Liouville sense and Caputo sense respectively. For a function ${\displaystyle f(t)}$ of ${\displaystyle C^{1}}$ given by [20][21]

$${\displaystyle _{a}^{ABC}D_{t}^{\alpha }f(t)={\frac {AB(\alpha )}{1-\alpha }}\int _{a}^{t}f'(\tau )E_{\alpha }\left(-\alpha {\frac {(t-\tau )^{\alpha }}{1-\alpha }}\right)d\tau ,}$$

If the function is continuous, the Atangana–Baleanu derivative in Riemann–Liouville sense is given by:

$${\displaystyle _{a}^{ABC}D_{t}^{\alpha }f(t)={\frac {AB(\alpha )}{1-\alpha }}{\frac {d}{dt}}\int _{a}^{t}f(\tau )E_{\alpha }\left(-\alpha {\frac {(t-\tau )^{\alpha }}{1-\alpha }}\right)d\tau ,}$$

The kernel used in Atangana–Baleanu fractional derivative has some properties of a cumulative distribution function.  For example, for all ${\displaystyle \alpha \in (0,1]}$, the function ${\displaystyle E_{\alpha }}$ is increasing on the real line, converges to ${\displaystyle 0}$ in ${\displaystyle -\infty }$, and ${\displaystyle E_{\alpha }(0)=1}$. Therefore, we have that, the function ${\displaystyle x\mapsto 1-E_{\alpha }(-x^{\alpha })}$ is the cumulative distribution function of a probability measure on the positive real numbers. The distribution is therefore defined, and any of its multiples, is called a Mittag-Leffler distribution of order ${\displaystyle \alpha }$. It is also very well-known that, all these probability distributions are absolutely continuous. In particular, the function Mittag-Leffler has a particular case ${\displaystyle E_{1}}$, which is the exponential function, the Mittag-Leffler distribution of order ${\displaystyle 1}$ is therefore an exponential distribution. However, for ${\displaystyle \alpha \in (0,1)}$, the Mittag-Leffler distributions are heavy-tailed. Their Laplace transform is given by:

$${\displaystyle \mathbb {E} (e^{-\lambda X_{\alpha }})={\frac {1}{1+\lambda ^{\alpha }}},}$$

This directly implies that, for ${\displaystyle \alpha \in (0,1)}$, the expectation is infinite. In addition, these distributions are geometric stable distributions.

The Riesz derivative is defined as

$${\displaystyle {\mathcal {F}}\left\{{\frac {\partial ^{\alpha }u}{\partial \left|x\right|^{\alpha }}}\right\}(k)=-\left|k\right|^{\alpha }{\mathcal {F}}\{u\}(k),}$$

where ${\displaystyle {\mathcal {F}}}$ denotes the Fourier transform.[22][23]

Classical fractional derivatives include:

• Grünwald–Letnikov derivative[24][25]
• Sonin–Letnikov derivative[25]
• Liouville derivative[24]
• Caputo derivative[24]
• Hadamard derivative[24][26]
• Marchaud derivative[24]
• Riesz derivative[25]
• Miller–Ross derivative[24]
• Weyl derivative[27][28][24]
• Erdélyi–Kober derivative[24]
• ${\displaystyle F^{\alpha }}$-derivative[29]

New fractional derivatives include:

• Coimbra derivative[24]
• Katugampola derivative[30]
• Hilfer derivative[24]
• Davidson derivative[24]
• Chen derivative[24]
• Caputo Fabrizio derivative[20][31]
• Atangana–Baleanu derivative[20][21]

The Erdélyi–Kober operator is an integral operator introduced by Arthur Erdélyi (1940).[32] and Hermann Kober (1940)[33] and is given by

$${\displaystyle {\frac {x^{-\nu -\alpha +1}}{\Gamma (\alpha )}}\int _{0}^{x}\left(t-x\right)^{\alpha -1}t^{-\alpha -\nu }f(t)\,dt\,,}$$

which generalizes the Riemann–Liouville fractional integral and the Weyl integral.

As described by Wheatcraft and Meerschaert (2008),[34] 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:

$${\displaystyle -\rho \left(\nabla ^{\alpha }\cdot {\vec {u}}\right)=\Gamma (\alpha +1)\Delta x^{1-\alpha }\rho \left(\beta _{s}+\phi \beta _{w}\right){\frac {\partial p}{\partial t}}}$$

When studying the redox behavior of a substrate in solution, a voltage is applied at an electrode surface to force electron transfer between electrode and substrate. The resulting electron transfer is measured as a current. The current depends upon the concentration of substrate at the electrode surface. As substrate is consumed, fresh substrate diffuses to the electrode as described by Fick's laws of diffusion. Taking the Laplace transform of Fick's second law yields an ordinary second-order differential equation (here in dimensionless form):

$${\displaystyle {\frac {d^{2}}{dx^{2}}}C(x,s)=sC(x,s)}$$

whose solution C(x,s) contains a one-half power dependence on s. Taking the derivative of C(x,s) and then the inverse Laplace transform yields the following relationship:

$${\displaystyle {\frac {d}{dx}}C(x,t)={\frac {d^{\scriptstyle {\frac {1}{2}}}}{dt^{\scriptstyle {\frac {1}{2}}}}}C(x,t)}$$

which relates the concentration of substrate at the electrode surface to the current.[35] This relationship is applied in electrochemical kinetics to elucidate mechanistic behavior. For example, it has been used to study the rate of dimerization of substrates upon electrochemical reduction.[36]

In 2013–2014 Atangana et al. described some groundwater flow problems using the concept of a derivative with fractional order.[37][38] In these works, the classical Darcy law is generalized by regarding the water flow as a function of a non-integer order derivative of the piezometric head. This generalized law and the law of conservation of mass are then used to derive a new equation for groundwater flow.

This equation has been shown useful for modeling contaminant flow in heterogenous porous media.[39][40][41]

Atangana and Kilicman extended the fractional advection dispersion equation to a variable order equation. In their work, the hydrodynamic dispersion equation was generalized using the concept of a variational order derivative. The modified equation was numerically solved via the Crank–Nicolson method. The stability and convergence in numerical simulations showed that the modified equation is more reliable in predicting the movement of pollution in deformable aquifers than equations with constant fractional and integer derivatives[42]

Anomalous diffusion processes in complex media can be well characterized by using fractional-order diffusion equation models.[43][44] The time derivative term corresponds to long-time heavy tail decay and the spatial derivative for diffusion nonlocality. The time-space fractional diffusion governing equation can be written as

$${\displaystyle {\frac {\partial ^{\alpha }u}{\partial t^{\alpha }}}=-K(-\Delta )^{\beta }u.}$$

A simple extension of the fractional derivative is the variable-order fractional derivative, α and β are changed into α(x, t) and β(x, t). Its applications in anomalous diffusion modeling can be found in the reference.[42][45][46]

Fractional derivatives are used to model viscoelastic damping in certain types of materials like polymers.[13]

Generalizing PID controllers to use fractional orders can increase their degree of freedom. The new equation relating the control variable u(t) in terms of a measured error value e(t) can be written as

$${\displaystyle u(t)=K_{\mathrm {p} }e(t)+K_{\mathrm {i} }D_{t}^{-\alpha }e(t)+K_{\mathrm {d} }D_{t}^{\beta }e(t)}$$

where α and β are positive fractional orders and K_p, K_i, and K_d, all non-negative, denote the coefficients for the proportional, integral, and derivative terms, respectively (sometimes denoted P, I, and D).[47]

The propagation of acoustical waves in complex media, such as in 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:

$${\displaystyle \nabla ^{2}u-{\dfrac {1}{c_{0}^{2}}}{\frac {\partial ^{2}u}{\partial t^{2}}}+\tau _{\sigma }^{\alpha }{\dfrac {\partial ^{\alpha }}{\partial t^{\alpha }}}\nabla ^{2}u-{\dfrac {\tau _{\epsilon }^{\beta }}{c_{0}^{2}}}{\dfrac {\partial ^{\beta +2}u}{\partial t^{\beta +2}}}=0\,.}$$

See also Holm & Näsholm (2011)[48] 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 Näsholm & Holm (2011b)[49] and in the survey paper,[50] as well as the Acoustic attenuation article. See Holm & Nasholm (2013)[51] for a paper which compares fractional wave equations which model power-law attenuation. This book on power-law attenuation also covers the topic in more detail.[52]

Pandey and Holm gave a physical meaning to fractional differential equations by deriving them from physical principles and interpreting the fractional-order in terms of the parameters of the acoustical media, example in fluid-saturated granular unconsolidated marine sediments.[53] Interestingly, Pandey and Holm derived Lomnitz's law in seismology and Nutting's law in non-Newtonian rheology using the framework of fractional calculus.[54] Nutting's law was used to model the wave propagation in marine sediments using fractional derivatives.[53]

The fractional Schrödinger equation, a fundamental equation of fractional quantum mechanics, has the following form:[55][56]

$${\displaystyle i\hbar {\frac {\partial \psi (\mathbf {r} ,t)}{\partial t}}=D_{\alpha }\left(-\hbar ^{2}\Delta \right)^{\frac {\alpha }{2}}\psi (\mathbf {r} ,t)+V(\mathbf {r} ,t)\psi (\mathbf {r} ,t)\,.}$$

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, ${\textstyle \Delta ={\frac {\partial ^{2}}{\partial \mathbf {r} ^{2}}}}$ is the Laplace operator, and D_α is a scale constant with physical dimension [D_α] = J^{1 − α}·m^α·s^−α = kg^{1 − α}·m^{2 − α}·s^{α − 2}, (at α = 2, ${\textstyle D_{2}={\frac {1}{2m}}}$ for a particle of mass m), and the operator (−ħ²Δ)^α/2 is the 3-dimensional fractional quantum Riesz derivative defined by

$${\displaystyle (-\hbar ^{2}\Delta )^{\frac {\alpha }{2}}\psi (\mathbf {r} ,t)={\frac {1}{(2\pi \hbar )^{3}}}\int d^{3}pe^{{\frac {i}{\hbar }}\mathbf {p} \cdot \mathbf {r} }|\mathbf {p} |^{\alpha }\varphi (\mathbf {p} ,t)\,.}$$

The index α in the fractional Schrödinger equation is the Lévy index, 1 < α ≤ 2.

As a natural generalization of the fractional Schrödinger equation, the variable-order fractional Schrödinger equation has been exploited to study fractional quantum phenomena:[57]

$${\displaystyle i\hbar {\frac {\partial \psi ^{\alpha (\mathbf {r} )}(\mathbf {r} ,t)}{\partial t^{\alpha (\mathbf {r} )}}}=\left(-\hbar ^{2}\Delta \right)^{\frac {\beta (t)}{2}}\psi (\mathbf {r} ,t)+V(\mathbf {r} ,t)\psi (\mathbf {r} ,t),}$$

where ${\textstyle \Delta ={\frac {\partial ^{2}}{\partial \mathbf {r} ^{2}}}}$ is the Laplace operator and the operator (−ħ²Δ)^β(t)/2 is the variable-order fractional quantum Riesz derivative.

• Fractional-order system
• Fractional Fourier transform

• Ross, B. (1975). "A brief history and exposition of the fundamental theory of fractional calculus". Fractional Calculus and Its Applications. pp. 1–36. doi:10.1007/BFb0067096. ISBN 978-3-540-07161-7. {{cite book}}: |journal= ignored (help)
• Debnath, L. (2004). "A brief historical introduction to fractional calculus". International Journal of Mathematical Education in Science and Technology. 35 (4): 487–501. doi:10.1080/00207390410001686571. S2CID 122198977.
• Tenreiro Machado, J.; Kiryakova, V.; Mainardi, F. (2011). "Recent history of fractional calculus". Communications in Nonlinear Science and Numerical Simulation. 16 (3): 1140–1153. Bibcode:2011CNSNS..16.1140M. doi:10.1016/j.cnsns.2010.05.027. hdl:10400.22/4149.
• Tenreiro Machado, J.A.; Galhano, A.M.; Trujillo, J.J. (2013). "Science metrics on fractional calculus development since 1966". Fractional Calculus and Applied Analysis. 16 (2): 479–500. doi:10.2478/s13540-013-0030-y. hdl:10400.22/3773. S2CID 122487513.
• Tenreiro Machado, J.A.; Galhano, A.M.S.F.; Trujillo, J.J. (2014). "On development of fractional calculus during the last fifty years". Scientometrics. 98 (1): 577–582. doi:10.1007/s11192-013-1032-6. hdl:10400.22/3769. S2CID 16879651.
• Ramirez, L.E.S.; Coimbra, C.F.M. (2010). "On the Selection and Meaning of Variable Order Operators for Dynamic Modeling". International Journal of Differential Equations. 2010 (1): 846107. doi:10.1155/2010/846107. hdl:10.1155/6314. S2CID 16501850.

• Oldham, Keith B.; Spanier, Jerome (1974). The Fractional Calculus; Theory and Applications of Differentiation and Integration to Arbitrary Order. Mathematics in Science and Engineering. Vol. V. Academic Press. ISBN 978-0-12-525550-9.
• Miller, Kenneth S.; Ross, Bertram, eds. (1993). An Introduction to the Fractional Calculus and Fractional Differential Equations. John Wiley & Sons. ISBN 978-0-471-58884-9.
• Samko, S.; Kilbas, A.A.; Marichev, O. (1993). Fractional Integrals and Derivatives: Theory and Applications. Taylor & Francis Books. ISBN 978-2-88124-864-1.
• Carpinteri, A.; Mainardi, F., eds. (1998). Fractals and Fractional Calculus in Continuum Mechanics. Springer-Verlag Telos. ISBN 978-3-211-82913-4.
• Igor Podlubny (27 October 1998). Fractional Differential Equations: An Introduction to Fractional Derivatives, Fractional Differential Equations, to Methods of Their Solution and Some of Their Applications. Elsevier. ISBN 978-0-08-053198-4.
• West, Bruce J.; Bologna, Mauro; Grigolini, Paolo (2003). Physics of Fractal Operators. p. 65. Bibcode:2003PhT....56l..65W. doi:10.1063/1.1650234. ISBN 978-0-387-95554-4. {{cite book}}: |journal= ignored (help)
• Mainardi, F. (2010). Fractional Calculus and Waves in Linear Viscoelasticity: An Introduction to Mathematical Models. Imperial College Press. doi:10.1142/p614. ISBN 978-1-84816-329-4.
• Tarasov, V.E. (2010). Fractional Dynamics: Applications of Fractional Calculus to Dynamics of Particles, Fields and Media. Nonlinear Physical Science. Springer. doi:10.1007/978-3-642-14003-7. ISBN 978-3-642-14003-7.
• Zhou, Y. (2010). Basic Theory of Fractional Differential Equations. Singapore: World Scientific. doi:10.1142/9069. ISBN 978-981-4579-89-6.
• Uchaikin, V.V. (2012). Fractional Derivatives for Physicists and Engineers. Nonlinear Physical Science. Higher Education Press. Bibcode:2013fdpe.book.....U. doi:10.1007/978-3-642-33911-0. ISBN 978-3-642-33911-0.
• Daftardar-gejji, Varsha (2013). Fractional Calculus: Theory and Applications. Narosa Publishing House. ISBN 978-8184873337.
• Srivastava, Hari M (2014). Special Functions in Fractional Calculus and Related Fractional Differintegral Equations. Singapore: World Scientific. doi:10.1142/8936. ISBN 978-981-4551-10-6.
• Li, C P; Zeng, F H (2015). Numerical Methods for Fractional Calcuus. USA: CRC Press.
• Umarov, S. (2015). Introduction to Fractional and Pseudo-Differential Equations with Singular Symbols. Developments in Mathematics. Vol. 41. Switzerland: Springer. doi:10.1007/978-3-319-20771-1. ISBN 978-3-319-20770-4.
• Herrmann, R. (2018). Fractional Calculus – An Introduction for Physicists (3rd ed.). Singapore: World Scientific. doi:10.1142/11107. ISBN 978-981-3274-57-0. S2CID 242068092.