Calculus 4Vector Fields

Divergence and Curl

∇ · F measures spreading out; ∇ × F measures rotation.

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A vector field has many partial derivatives: $P_x$, $P_y$, $Q_x$, and so on. Two combinations of them have a clear meaning and show up in every big theorem of this course. Divergence measures how much a field spreads out from a point, and curl measures how much it swirls. Both are written with the symbol $\nabla = \left\langle \frac{\partial}{\partial x}, \frac{\partial}{\partial y}, \frac{\partial}{\partial z} \right\rangle$, used like a vector whose "components" are derivatives. You need partial derivatives and the cross product.

Key idea

For $\mathbf{F} = \langle P, Q, R \rangle$: $$\nabla \cdot \mathbf{F} = P_x + Q_y + R_z \quad \text{(divergence: a scalar function)}$$ $$\nabla \times \mathbf{F} = \langle R_y - Q_z,\ P_z - R_x,\ Q_x - P_y \rangle \quad \text{(curl: a vector field)}$$ In the plane, $\mathbf{F} = \langle P, Q \rangle$ has divergence $P_x + Q_y$ and scalar curl $Q_x - P_y$, the $\mathbf{k}$-component of the curl of $\langle P, Q, 0 \rangle$.

The curl formula comes from the determinant pattern of a cross product: $$\nabla \times \mathbf{F} = \begin{vmatrix} \mathbf{i} & \mathbf{j} & \mathbf{k} \\ \partial_x & \partial_y & \partial_z \\ P & Q & R \end{vmatrix},$$ where "multiplying" $\partial_y$ by $R$ means taking $R_y$. As with any ${}3 \times 3$ determinant, the middle component carries a minus sign: $-(R_x - P_z) = P_z - R_x$.

Why it works

Two identities, both from Clairaut's theorem (mixed partials are equal when continuous):
$$\nabla \times (\nabla f) = \langle f_{zy} - f_{yz},\ f_{xz} - f_{zx},\ f_{yx} - f_{xy} \rangle = \mathbf{0}\text{:}$$ gradient fields have zero curl.
$$\nabla \cdot (\nabla \times \mathbf{F}) = (R_y - Q_z)_x + (P_z - R_x)_y + (Q_x - P_y)_z = R_{yx} - Q_{zx} + P_{zy} - R_{xy} + Q_{xz} - P_{yz} = 0\text{:}$$ the terms cancel in pairs.
So a field with nonzero curl is not a gradient field, and a field with nonzero divergence is not a curl.
OperationTakesGivesMeasures
gradient $\nabla f$a scalar functiona vector fieldsteepest increase
divergence $\nabla \cdot \mathbf{F}$a vector fielda scalar functionspreading out (sources)
curl $\nabla \times \mathbf{F}$a vector fielda vector fieldswirling (rotation)
$\mathbf{F} = \langle xy, y - x \rangle$, with $\nabla \cdot \mathbf{F} = y + 1$ and scalar curl $Q_x - P_y = -1 - x$. Drag the probe: the box shows the divergence, the paddle wheel the curl. Both change from point to point.

Worked examples

Worked example: A divergence

Find $\nabla \cdot \mathbf{F}$ for $\mathbf{F} = \langle x^2y, yz, xz^2 \rangle$.
  1. $P_x = 2xy$, $Q_y = z$, $R_z = 2xz$.
  2. $\nabla \cdot \mathbf{F} = 2xy + z + 2xz$, a single number at each point.

Answer: ${}2xy + z + 2xz$

Worked example: A curl that vanishes

Find $\nabla \times \mathbf{F}$ for $\mathbf{F} = \langle yz, xz, xy \rangle$.
  1. $R_y - Q_z = x - x = 0$.
  2. $P_z - R_x = y - y = 0$.
  3. $Q_x - P_y = z - z = 0$.
  4. $\nabla \times \mathbf{F} = \mathbf{0}$, as expected: $\mathbf{F} = \nabla(xyz)$.

Answer: $\mathbf{0}$

Worked example: Both at once

Find the curl and divergence of $\mathbf{F} = \langle -y, x, z^2 \rangle$.
  1. Curl: $R_y - Q_z = 0$, $P_z - R_x = 0$, $Q_x - P_y = 1 - (-1) = 2$, so $\nabla \times \mathbf{F} = \langle 0, 0, 2 \rangle$.
  2. Divergence: ${}0 + 0 + 2z = 2z$.
  3. The field spins about the $z$-axis everywhere and spreads out only where $z > 0$.

Answer: curl $\langle 0, 0, 2 \rangle$, divergence ${}2z$

Common mistake

Mixing up the inputs and outputs. Divergence and curl act on vector fields; "$\nabla \cdot f$" for a scalar function $f$ means nothing. And the divergence is one number at each point, not a vector: $\nabla \cdot \langle x^2, y, z \rangle = 2x + 1 + 1$, not $\langle 2x, 1, 1 \rangle$. If your divergence has three components, you forgot to add them.

Practice

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Sources and further reading

  • OpenStax Calculus Volume 3, 6.5 Divergence and Curl
@teddyrookbook GitHub