🧭 Gradient, Divergence & Curl

πŸ“– The Physics

The operator βˆ‡ ("del") = (βˆ‚/βˆ‚x, βˆ‚/βˆ‚y, βˆ‚/βˆ‚z) combines with a field in three ways. Which one you use depends on whether the field is a scalar (like temperature) or a vector (like flow velocity).

Gradient (scalar β†’ vector):

βˆ‡f=(βˆ‚fβˆ‚x,β€…β€Šβˆ‚fβˆ‚y,β€…β€Šβˆ‚fβˆ‚z)\nabla f = \left(\dfrac{\partial f}{\partial x},\; \dfrac{\partial f}{\partial y},\; \dfrac{\partial f}{\partial z}\right)

Divergence (vector β†’ scalar):

βˆ‡β‹…Fβƒ—=βˆ‚Fxβˆ‚x+βˆ‚Fyβˆ‚y+βˆ‚Fzβˆ‚z\nabla \cdot \vec{F} = \dfrac{\partial F_x}{\partial x} + \dfrac{\partial F_y}{\partial y} + \dfrac{\partial F_z}{\partial z}

Curl (vector β†’ vector):

βˆ‡Γ—Fβƒ—=(βˆ‚Fzβˆ‚yβˆ’βˆ‚Fyβˆ‚z,β€…β€Šβˆ‚Fxβˆ‚zβˆ’βˆ‚Fzβˆ‚x,β€…β€Šβˆ‚Fyβˆ‚xβˆ’βˆ‚Fxβˆ‚y)\nabla \times \vec{F} = \left(\dfrac{\partial F_z}{\partial y} - \dfrac{\partial F_y}{\partial z},\; \dfrac{\partial F_x}{\partial z} - \dfrac{\partial F_z}{\partial x},\; \dfrac{\partial F_y}{\partial x} - \dfrac{\partial F_x}{\partial y}\right)

Gradient of a scalar field points in the direction of steepest increase, and its length is how steep that slope is β€” here every arrow points toward the top of the hill. Divergence measures how much a vector field spreads out of a point: positive is a source, negative a sink. Curl measures how much it rotates about a point.

For the radial field F = a(x, y), βˆ‡Β·F = 2a everywhere and its curl is zero. For the swirl F = a(βˆ’y, x), βˆ‡Γ—F = 2a αΊ‘ and its divergence is zero β€” a neat pair of opposites.

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