 Timescale calculus

In mathematics, timescale calculus is a unification of the theory of difference equations with that of differential equations, unifying integral and differential calculus with the calculus of finite differences, offering a formalism for studying hybrid discrete–continuous dynamical systems. It has applications in any field that requires simultaneous modelling of discrete and continuous data. It gives a new definition of a derivative such that if you differentiate a function which acts on the real numbers then the definition is equivalent to standard differentiation, but if you use a function acting on the integers then it is equivalent to the forward difference operator.
History
It was introduced in 1988 by the German mathematician Stefan Hilger.^{[1]} However, similar ideas have been used before and go back at least to the introduction of the Riemann–Stieltjes integral which unifies sums and integrals.
Dynamic equations
Many results concerning differential equations carry over quite easily to corresponding results for difference equations, while other results seem to be completely different from their continuous counterparts.^{[2]} The study of dynamic equations on time scales reveals such discrepancies, and helps avoid proving results twice — once for differential equations and once again for difference equations. The general idea is to prove a result for a dynamic equation where the domain of the unknown function is a socalled time scale (also known as a timeset), which may be an arbitrary closed subset of the reals. In this way, results apply not only to the set of real numbers or set of integers but to more general time scales such as a Cantor set.
The three most popular examples of calculus on time scales are differential calculus, difference calculus, and quantum calculus. Dynamic equations on a time scale have a potential for applications, such as in population dynamics. For example, it can model insect populations that are continuous while in season, die out in winter—while their eggs are incubating or dormant—and then hatch in a new season, giving rise to a nonoverlapping population.
Formal definitions
A time scale (or measure chain) is a closed subset of the real line . The common notation for a general time scale is .
The two most commonly encountered examples of time scales are the real numbers and the discrete time scale .
A single point in a time scale is defined as:
Operations on time scales
The forward jump and backward jump operators represent the closest point in the time scale on the right and left of a given point t, respectively. Formally:
 (forward shift operator / forward jump operator)
 (backward shift operator / backward jump operator)
The graininess μ is the distance from a point to the closest point on the right and is given by: μ(t) = σ(t) − t.
For a rightdense t, σ(t) = t and μ(t) = 0.
For a leftdense t, ρ(t) = t.Classification of points
For any , t is:
 left dense if ρ(t) = t
 right dense if σ(t) = t
 left scattered if ρ(t) < t
 right scattered if σ(t) > t
 dense if both left dense and right dense
 isolated if both left scattered and right scattered
As illustrated by the figure at right: Point t_{1} is dense
 Point t_{2} is left dense and right scattered
 Point t_{3} is isolated
 Point t_{4} is left scattered and right dense
Continuity
Continuity on a time scale is redefined as equivalent to density. A time scale is said to be rightcontinuous at point t if it is right dense at point t. Similarly, a time scale is said to be leftcontinuous at point t if it is left dense at point t.
Derivative
Take a function:
 ,
(where R could be any Banach space, but set it to be the real line for simplicity).
Definition: The delta derivative (also Hilger derivative) f^{Δ}(t) exists if and only if:
For every there exists a neighborhood U of t such that:
for all s in U.
Take Then σ(t) = t, μ(t) = 0, f^{Δ} = f'; is the derivative used in standard calculus. If (the integers), σ(t) = t + 1, μ(t) = 1, f^{Δ} = Δf is the forward difference operator used in difference equations.
Integration
The delta integral is defined as the antiderivative with respect to the delta derivative. If F(t) has a continuous derivative f(t) = F^{Δ}(t) one sets
Laplace transform and ztransform
A Laplace transform can be defined for functions on time scales, which uses the same table of transforms for any arbitrary time scale. This transform can be used to solve dynamic equations on time scales. If the time scale is the nonnegative integers then the transform is equal^{[2]} to a modified Ztransform:
Partial differentiation
Partial differential equations and partial difference equations are unified as partial dynamic equations on time scales.^{[3]}^{[4]}^{[5]}
Multiple integration
Multiple integration on time scales.^{[6]}
Stochastic dynamic equations on time scales
Stochastic differential equations and Stochastic difference equations can be generalized to Stochastic dynamic equations on time scales.^{[7]}
Measure theory on time scales
Associated with every time scale is a natural measure^{[8]}^{[9]} defined via
 μ^{Δ}(A) = λ(ρ ^{− 1}(A)),
where λ denotes Lebesgue measure and ρ is the backward shift operator defined on . The delta integral turns out to be the usual Lebesgue–Stieltjes integral with respect to this measure
and the delta derivative turns out to be the Radon–Nikodym derivative with respect to this measure^{[10]}
Distributions on time scales
The Dirac delta and Kronecker delta are unified on time scales as the Hilger delta:^{[11]}^{[12]}
Integral equations on time scales
Integral equations and summation equations are unified as integral equations on time scales.^{[13]}
Fractional calculus on time scales
Fractional calculus on time scales^{[14]}
See also
 Analysis on fractals for dynamic equations on a Cantor set.
Notes
 ^ Hilger, Stefan (1998). Ein Maßkettenkalkül mit Anwendung auf Zentrumsmannigfaltigkeiten. Universität Würzburg.
 ^ ^{a} ^{b} Martin Bohner & Allan Peterson (2001). Dynamic Equations on Time Scales. Birkhäuser. ISBN 9780817642259. link
 ^ Partial differential equations on time scales, Calvin D. Ahlbrandt, Christina Morian
 ^ Partial dynamic equations on time scales, B Jackson – Journal of Computational and Applied Mathematics, 2006
 ^ Partial differentiation on time scales, M Bohner, GS Guseinov, Dynamic Systems and Applications 13 (2004) 351–379
 ^ Multiple integration on time scales, M Bohner, GS Guseino – Dynamic Systems and Applications, 2005
 ^ STOCHASTIC DYNAMIC EQUATIONS, SUMAN SANYAL, 2008
 ^ Integration on time scales, GS Guseinov, J. Math. Anal. Appl. 285 (2003), 107–127
 ^ Measure theory on time scales, A Deniz – 2007
 ^ On the connection between the Hilger and Radon–Nikodym derivatives, J Eckhardt and G Teschl, J. Math. Anal. Appl. 385 (2012), 1184–1189
 ^ The Laplace transform on time scales revisited, John M. Davis, Ian A. Gravagne , Billy J. Jackson , Robert J. Marks II , Alice A. Ramos, J. Math. Anal. Appl. 332 (2007) 1291–1307
 ^ Bilateral Laplace Transforms on Time Scales: Convergence, Convolution, and the Characterization of Stationary Stochastic Time Series, John M. Davis, Ian A. Gravagne and Robert J. Marks II
 ^ Volterra integral equations on time scales: Basic qualitative and quantitative results with applications to initial value problems on unbounded domains, Tomasia Kulik and Christopher C. Tisdell, 2007
 ^ Fractional Derivatives and Integrals on Time Scales via the Inverse Generalized Laplace Transform, Nuno R. O. Bastos, Dorota Mozyrska, Delfim F. M. Torres
References
 Dynamic equations on time scales: a survey, Ravi Agarwal, Martin Bohner, Donal O’Regan, Allan Peterson, Journal of Computational and Applied Mathematics 141 (2002) 1–26
Further reading
 The Baylor University Time Scales Group
 Dynamic Equations on Time Scales Special issue of Journal of Computational and Applied Mathematics (2002)
 Dynamic Equations And Applications Special Issue of Advances in Difference Equations (2006)
 Dynamic Equations on Time Scales: Qualitative Analysis and Applications Special issue of Nonlinear Dynamics And Systems Theory (2009)
Categories: Dynamical systems
 Calculus
 Recurrence relations
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