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mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, in the study of
dynamical systems In mathematics, a dynamical system is a system in which a function describes the time dependence of a point in an ambient space. Examples include the mathematical models that describe the swinging of a clock pendulum, the flow of water in a p ...
, the Hartman–Grobman theorem or linearisation theorem is a theorem about the local behaviour of dynamical systems in the neighbourhood of a hyperbolic equilibrium point. It asserts that
linearisation In mathematics, linearization is finding the linear approximation to a function at a given point. The linear approximation of a function is the first order Taylor expansion around the point of interest. In the study of dynamical systems, lineariz ...
—a natural simplification of the system—is effective in predicting qualitative patterns of behaviour. The theorem owes its name to
Philip Hartman Philip Hartman (May 16, 1915 – August 28, 2015) was an American mathematician at Johns Hopkins University working on differential equations who introduced the Hartman–Grobman theorem In mathematics, in the study of dynamical systems, ...
and David M. Grobman. The theorem states that the behaviour of a dynamical system in a domain near a hyperbolic equilibrium point is qualitatively the same as the behaviour of its linearization near this equilibrium point, where hyperbolicity means that no eigenvalue of the linearization has real part equal to zero. Therefore, when dealing with such dynamical systems one can use the simpler linearization of the system to analyse its behaviour around equilibria.


Main theorem

Consider a system evolving in time with state u(t)\in\mathbb R^n that satisfies the differential equation du/dt=f(u) for some smooth map f: \mathbb^n \to \mathbb^n. Suppose the map has a hyperbolic equilibrium state u^*\in\mathbb R^n: that is, f(u^*)=0 and the
Jacobian matrix In vector calculus, the Jacobian matrix (, ) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. When this matrix is square, that is, when the function takes the same number of variables as ...
A= partial f_i/\partial x_j/math> of f at state u^* has no eigenvalue with real part equal to zero. Then there exists a neighbourhood N of the equilibrium u^* and a homeomorphism h : N \to \mathbb^n, such that h(u^*)=0 and such that in the neighbourhood N the
flow Flow may refer to: Science and technology * Fluid flow, the motion of a gas or liquid * Flow (geomorphology), a type of mass wasting or slope movement in geomorphology * Flow (mathematics), a group action of the real numbers on a set * Flow (psych ...
of du/dt=f(u) is topologically conjugate by the continuous map U=h(u) to the flow of its linearisation dU/dt=AU. Even for infinitely differentiable maps f, the homeomorphism h need not to be smooth, nor even locally Lipschitz. However, it turns out to be Hölder continuous, with an exponent depending on the constant of hyperbolicity of A. The Hartman–Grobman theorem has been extended to infinite-dimensional Banach spaces, non-autonomous systems du/dt=f(u,t) (potentially stochastic), and to cater for the topological differences that occur when there are eigenvalues with zero or near-zero real-part.


Example

The algebra necessary for this example is easily carried out by a web service that computes normal form coordinate transforms of systems of differential equations, autonomous or non-autonomous, deterministic or
stochastic Stochastic (, ) refers to the property of being well described by a random probability distribution. Although stochasticity and randomness are distinct in that the former refers to a modeling approach and the latter refers to phenomena themselv ...
. Consider the 2D system in variables u=(y,z) evolving according to the pair of coupled differential equations : \frac = -3y+yz\quad\text\quad \frac = z+y^2. By direct computation it can be seen that the only equilibrium of this system lies at the origin, that is u^*=0. The coordinate transform, u=h^(U) where U=(Y,Z), given by : \begin y & \approx Y+YZ+\dfrac1Y^3+\dfrac1 2Y Z^2 \\ ptz & \approx Z-\dfrac1 7Y^2-\dfrac1 3Y^2 Z \end is a smooth map between the original u=(y,z) and new U=(Y,Z) coordinates, at least near the equilibrium at the origin. In the new coordinates the dynamical system transforms to its linearisation : \frac=-3Y\quad\text\quad \frac = Z. That is, a distorted version of the linearisation gives the original dynamics in some finite neighbourhood.


See also

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Stable manifold theorem In mathematics, especially in the study of dynamical systems and differential equations, the stable manifold theorem is an important result about the structure of the set of orbits approaching a given hyperbolic fixed point. It roughly states that t ...


References


Further reading

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External links

* * * {{DEFAULTSORT:Hartman-Grobman Theorem Theorems in analysis Theorems in dynamical systems Approximations