Method of characteristics

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In mathematics, the method of characteristics is a technique for solving partial differential equations. Typically, it applies to first-order equations, although more generally the method of characteristics is valid for any hyperbolic partial differential equation. The method is to reduce a partial differential equation to a family of ordinary differential equations along which the solution can be integrated from some initial data given on a suitable hypersurface.

[edit] Characteristics of first-order partial differential equations

For a first-order PDE, the method of characteristics discovers curves (called characteristic curves or just characteristics) along which the PDE becomes an ordinary differential equation (ODE). Once the ODE is found, it can be solved along the characteristic curves and transformed into a solution for the original PDE.

For the sake of motivation, we confine our attention to the case of a function of two independent variables x and y for the moment. Consider a quasilinear PDE of the form

$a(x,y,u) \frac{\partial u}{\partial x}+b(x,y,u) \frac{\partial u}{\partial y}=c(x,y,u).$

(1)

Suppose that a solution u is known, and consider the surface graph z = u(x,y) in R³. A normal vector to this surface is given by

$(u_x(x,y),u_y(x,y),-1).\,$

As a result,^[1] equation (1) is equivalent to the geometrical statement that the vector field

$(a(x,y,z),b(x,y,z),c(x,y,z))\,$

is tangent to the surface z = u(x,y) at every point. In other words, the graph of the solution must be a union of integral curves of this vector field. These integral curves are called the characteristic curves of the original partial differential equation.

The equations of the characteristic curve may be expressed invariantly by the Charpit-Lagrange equations^[2]

$\frac{dx}{a(x,y,z)} = \frac{dy}{b(x,y,z)} = \frac{dz}{c(x,y,z)},$

or, if a particular parametrization t of the curves is fixed, then these equations may be written as a system of ordinary differential equations for x(t), y(t), z(t):

$\begin{array}{rcl} \frac{dx}{dt}&=&a(x,y,z)\\ \frac{dy}{dt}&=&b(x,y,z)\\ \frac{dz}{dt}&=&c(x,y,z). \end{array}$

These are the characteristic equations for the original system.

[edit] Linear and quasilinear cases

Consider now a PDE of the form

$\sum_{i=1}^n a_i(x_1,\dots,x_n,u) \frac{\partial u}{\partial x_i}=c(x_1,\dots,x_n,u).$

For this PDE to be linear, the coefficients a_i may be functions of the spatial variables only, and independent of u. For it to be quasilinear, a_i may also depend on the value of the function, but not on any derivatives. The distinction between these two cases is inessential for the discussion here.

For a linear or quasilinear PDE, the characteristic curves are given parametrically by

$(x_1,\dots,x_n,u) = (x_1(s),\dots,x_n(s),u(s))$

such that the following system of ODEs is satisfied

$\frac{dx_i}{ds} = a_i(x_1,\dots,x_n,u)$

(2)

$\frac{du}{ds} = c(x_1,\dots,x_n,u).$

(3)

Equations (2) and (3) give the characteristics of the PDE.

[edit] Fully nonlinear case

Consider the partial differential equation

$F(x_1,\dots,x_n,u,p_1,\dots,p_n)=0\qquad\qquad (1)$

where the variables p_i are shorthand for the partial derivatives

$p_i = \frac{\partial u}{\partial x_i}.$

Let (x_i(s),u(s),p_i(s)) be a curve in R²ⁿ⁺¹. Suppose that u is any solution, and that

$u(s) = u(x_1(s),\dots,x_n(s)).$

Along a solution, differentiating (1) with respect to s gives

$\sum(F_{x_i} + F_u p_i)\dot{x}_i + \sum F_{p_i}\dot{p}_i = 0$

$\dot{u} - \sum p_i \dot{x}_i = 0$

$\sum (\dot{x}_i dp_i - \dot{p}_i dx_i)= 0.$

(The second equation follows from applying the chain rule to a solution u, and the third follows by taking an exterior derivative of the relation du-Σp_idx_i=0.) Manipulating these equations gives

$\dot{x}_i=\lambda F_{p_i},\quad\dot{p}_i=-\lambda(F_{x_i}+F_up_i),\quad \dot{u}=\lambda\sum p_iF_{p_i}$

where λ is a constant. Writing these equations more symmetrically, one obtains the Charpit-Lagrange equations for the characteristic

$\frac{\dot{x}_i}{F_{p_i}}=-\frac{\dot{p}_i}{F_{x_i}+F_up_i}=\frac{\dot{u}}{\sum p_iF_{p_i}}.$

Geometrically, the method of characteristics in the fully nonlinear case can be interpreted as requiring that the Monge cone of the differential equation should everywhere be tangent to the graph of the solution.

[edit] Example

As an example, consider the advection equation (this example assumes familiarity with PDE notation, and solutions to basic ODEs).

$a \frac{\partial u}{\partial x} + \frac{\partial u}{\partial t} = 0\,$

where $a\,$ is constant and $u\,$ is a function of $x\,$ and $t\,$ . We want to transform this linear first order PDE into an ODE along the appropriate curve; i.e. something of the form

$\frac{d}{ds}u(x(s), t(s)) = F(u, x(s), t(s))$ ,

where $(x(s),t(s))\,$ is a characteristic line. First, we find

$\frac{d}{ds}u(x(s), t(s)) = \frac{\partial u}{\partial x} \frac{dx}{ds} + \frac{\partial u}{\partial t} \frac{dt}{ds}$

by the chain rule. Now, if we set $\frac{dx}{ds} = a$ and $\frac{dt}{ds} = 1$ we get

$a \frac{\partial u}{\partial x} + \frac{\partial u}{\partial t} \,$

which is the left hand side of the PDE we started with. Thus

$\frac{d}{ds}u = a \frac{\partial u}{\partial x} + \frac{\partial u}{\partial t} = 0.$

So, along the characteristic line $(x(s), t(s))\,$ , the original PDE becomes the ODE $u_s = F(u, x(s), t(s)) = 0\,$ . That is to say that along the characteristics, the solution is constant. Thus, $u(x_s, t_s) = u(x_0, 0)\,$ where $(x_s, t_s)\,$ and $(x_0, 0)\,$ lie on the same characteristic. So to determine the general solution, it is enough to find the characteristics by solving the characteristic system of ODEs:

$\frac{dt}{ds} = 1$ , letting $t(0)=0\,$ we know $t=s\,$ ,
$\frac{dx}{ds} = a$ , letting $x(0)=x_0\,$ we know $x=as+x_0=at+x_0\,$ ,
$\frac{du}{ds} = 0$ , letting $u(0)=f(x_0)\,$ we know $u(x(t), t)=f(x_0)=f(x-at)\,$ .

In this case, the characteristic lines are straight lines with slope $a\,$ , and the value of $u\,$ remains constant along any characteristic line.

[edit] Characteristics of linear differential operators

Let X be a differentiable manifold and P a linear differential operator

$P : C^\infty(X) \to C^\infty(X)$

of order k. In a local coordinate system xⁱ,

$P = \sum_{|\alpha|\le k} P^{\alpha}(x)\frac{\partial}{\partial x^\alpha}$

in which α denotes a multi-index. The principal symbol of P, denoted σ_P, is the function on the cotangent bundle T^∗X defined in these local coordinates by

σ_P(x,ξ) =	∑	P^α(x)ξ_α
	\| α \| = k

where the ξ_i are the fiber coordinates on the cotangent bundle induced by the coordinate differentials dxⁱ. Although this is defined using a particular coordinate system, the transformation law relating the ξ_i and the xⁱ ensures that σ_P is a well-defined function on the cotangent bundle.

The function σ_P is homogeneous of degree k in the ξ variable. The zeros of σ_P, away from the zero section of T^∗X, are the characteristics of P. A hypersurface of X defined by the equation F(x) = c is called a characteristic hypersurface at x if

σ P (x, d F (x)) = 0.

Invariantly, a characteristic hypersurface is a hypersurface whose conormal bundle is in the characteristic set of P.

[edit] Qualitative Analysis of Characteristics

Characteristics are also a powerful tool for gaining qualitative insight into a PDE.

One can use the crossings of the characteristics to find shockwaves. Intuitively, we can think of each characteristic line implying a solution to $u\,$ along itself. Thus, when two characteristics cross two solutions are implied. This causes shockwaves and the solution to $u\,$ becomes a multivalued function. Solving PDEs with this behavior is a very difficult problem and an active area of research.

Characteristics may fail to cover part of the domain of the PDE. This is called a rarefaction, and indicates the solution typically exists only in a weak, i.e. integral equation, sense.

The direction of the characteristic lines indicate the flow of values through the solution, as the example above demonstrates. This kind of knowledge is useful when solving PDEs numerically as it can indicate which finite difference scheme is best for the problem.

[edit] References

Courant, Richard; Hilbert, David (1962), Methods of Mathematical Physics, Volume II, Wiley-Interscience
Delgado, Manuel (1997), "The Lagrange-Charpit Method", SIAM Review 39 (2): 298–304, doi:10.1137/S0036144595293534, http://www.jstor.org/pss/2133111
Evans, Lawrence C. (1998), Partial Differential Equations, Providence: American Mathematical Society, ISBN 0-8218-0772-2
John, Fritz (1991), Partial differential equations (4th ed.), Springer, ISBN 978-0387906096
Polyanin, A. D.; Zaitsev, V. F.; Moussiaux, A. (2002), Handbook of First Order Partial Differential Equations, London: Taylor & Francis, ISBN 0-415-27267-X
Polyanin, A. D. (2002), Handbook of Linear Partial Differential Equations for Engineers and Scientists, Boca Raton: Chapman & Hall/CRC Press, ISBN 1-58488-299-9
Sarra, Scott (2003), "The Method of Characteristics with applications to Conservation Laws", Journal of Online Mathematics and its Applications .
Streeter, VL; Wylie, EB (1998), Fluid mechanics (International $9 t h$ Revised ed.), McGraw-Hill Higher Education

[edit] External links

[0] John 1991

[1] Delgado 1997

[1]

[2]

Method of characteristics

From Wikipedia, the free encyclopedia

Contents

[edit] Characteristics of first-order partial differential equations

[edit] Linear and quasilinear cases

[edit] Fully nonlinear case

[edit] Example

[edit] Characteristics of linear differential operators

[edit] Qualitative Analysis of Characteristics

[edit] Notes

[edit] References

[edit] External links

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