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What a PDE is, and how to classify one

Unknown functions of several variables, order and linearity, and the elliptic, parabolic and hyperbolic types.

A partial differential equation is a relation between an unknown function of two or more variables and its partial derivatives. We write \( u_t = \partial u/\partial t \), \( u_{xx} = \partial^2 u/\partial x^2 \), and \( \Delta u = u_{xx} + u_{yy} + u_{zz} \) for the Laplacian. Four equations carry most of this course: the transport equation \( u_t + c\,u_x = 0 \), the heat equation \( u_t = k\,u_{xx} \), the wave equation \( u_{tt} = c^2 u_{xx} \) and Laplace's equation \( \Delta u = 0 \). A classical solution is a function with enough continuous derivatives that the equation holds at every point of the domain. The example below checks that \( u = x^2 - y^2 \) is one for Laplace's equation: \( u_{xx} = 2 \) and \( u_{yy} = -2 \) cancel.

The order is the highest derivative that appears. The equation is linear when it has the form \( L[u] = f \) with \( L[\alpha u + \beta v] = \alpha L[u] + \beta L[v] \); then, when \( f = 0 \), any combination of solutions is again a solution (superposition), and nearly every explicit method in this course depends on that. Nonlinear equations come in grades. Burgers' equation \( u_t + u\,u_x = 0 \) is quasilinear (linear in its highest derivatives, with coefficients depending on \( u \)). The Navier-Stokes equations \( u_t + (u\cdot\nabla)u - \nu\Delta u + \nabla p = 0 \), \( \nabla\cdot u = 0 \) are semilinear: the second-order term \( \nu\Delta u \) is linear and the nonlinearity involves only first derivatives.

A linear second-order equation in two variables, \( A u_{xx} + 2B u_{xy} + C u_{yy} + \text{(lower order)} = 0 \), is classified by the sign of \( B^2 - AC \): negative means elliptic (Laplace: \( A = C = 1, B = 0 \)), zero means parabolic (heat, written in \( x, t \): \( A = k \), \( B = C = 0 \)), positive means hyperbolic (wave: \( A = c^2, C = -1 \)). The coefficients may depend on position, so the type can change inside one domain: the Tricomi equation \( y\,u_{xx} + u_{yy} = 0 \) is elliptic where \( y > 0 \) and hyperbolic where \( y < 0 \), and it models flow passing through the speed of sound.

Picture it: drop a spike of data into each type. An elliptic equation spreads its influence over the whole domain at once and returns a smooth surface, like a drum skin pushed at one point. A parabolic equation smooths the spike into a bump that widens as time runs forward. A hyperbolic equation sends the spike off along two lines at finite speed, sharp as it started.

Think it: the type tells you which data to give. Elliptic problems want boundary values, parabolic problems want an initial state plus boundary values, and hyperbolic problems want an initial position and velocity. Give the wrong data (initial position and velocity to Laplace's equation, say) and the problem becomes ill-posed, which is the subject of the well-posedness lesson.

Rechenbeispiel · does u = x^2 - y^2 satisfy u_xx + u_yy = 0

Does u = x^2 - y^2 satisfy u_xx + u_yy = 0

u = x^{2} - y^{2},\quad u_{xx} + u_{yy} = 0

Schritt für Schritt

  1. u = x^{2} - y^{2},\qquad u_{xx} + u_{yy} = 0

    To check a solution, compute every derivative the equation uses, substitute, and see whether both sides agree.

  2. u_{xx} = 2

    Differentiate 2 times with respect to x.

  3. u_{yy} = -2

    Differentiate 2 times with respect to y.

  4. \text{LHS} = 0,\quad \text{RHS} = 0

    Substitute the derivatives into both sides.

  5. \text{LHS} - \text{RHS} = 0

    Subtract and simplify.

  6. \text{LHS} - \text{RHS} = 0\ \checkmark

    The two sides agree for every value of the variables, so it is a solution.

Antwort aufdecken
\text{Yes: } u = x^{2} - y^{2} \text{ satisfies } u_{xx} + u_{yy} = 0

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Wie man: What a PDE is, and how to classify one

  1. Identify the unknown function and its independent variables.
  2. Read off the order: the highest derivative present.
  3. Decide linearity: is every term linear in u and its derivatives?
  4. For a second-order linear equation in two variables, compute B^2 - AC from the coefficients of u_xx, u_xy (halved) and u_yy.
  5. Negative: elliptic; zero: parabolic; positive: hyperbolic. Check whether the sign changes across the domain.

Fragen, die die Leute stellen

Why halve the coefficient of u_xy?

Because the principal part is the quadratic form A ξ² + 2B ξη + C η², and its type (definite, degenerate, indefinite) is decided by the determinant AC - B² of the symmetric matrix [[A, B], [B, C]].

Is a PDE with a constant term still linear?

Yes. u_t - u_xx = f(x, t) is linear but inhomogeneous: the difference of two solutions solves the homogeneous equation, so superposition still organises everything.

What should I know before starting?

Partial derivatives, the divergence theorem and multiple integrals from multivariable calculus; linear second-order ODEs; eigenvalues from linear algebra; and enough analysis to be comfortable with uniform convergence and integrals over infinite intervals.

Why are there so few formulas for solutions?

Explicit solutions exist for linear equations with constant coefficients on simple domains. Almost everything else (curved domains, variable coefficients, nonlinear terms) has none, so the modern subject proves that a solution exists and estimates its size and smoothness without ever writing it down.

How does this course lead to the Navier-Stokes problem?

The Navier-Stokes equations are a heat equation for the velocity with a transport term and a pressure that is found from a Poisson equation. Reading the Millennium problem needs energy estimates, weak solutions, Sobolev spaces, local existence with a blow-up criterion, and the scaling argument that explains why three dimensions is hard. The last six lessons build those.

What do elliptic, parabolic and hyperbolic mean?

Elliptic equations (Laplace) describe equilibrium and smooth everything; parabolic equations (heat) describe diffusion forward in time; hyperbolic equations (waves) carry signals at finite speed and keep their sharp edges. The type decides which data make a sensible problem.

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