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Multivariable Chain Rule

Core Definition

Let z=f(x,y)z = f(x, y) be a differentiable function of xx and yy.

  1. Case 1: Single Independent Parameter (Trajectory Paths)
    If x=x(t)x = x(t) and y=y(t)y = y(t) are differentiable functions of a single parameter tt, then zz is an indirect function of tt, and the total derivative is:

    dzdt=∂z∂xdxdt+∂z∂ydydt\frac{dz}{dt} = \frac{\partial z}{\partial x}\frac{dx}{dt} + \frac{\partial z}{\partial y}\frac{dy}{dt}
    In vector notation, this is the dot product of the gradient and velocity:
    dzdt=∇z⋅v⃗(t)=⟨∂z∂x,∂z∂y⟩⋅⟨dxdt,dydt⟩\frac{dz}{dt} = \nabla z \cdot \vec{v}(t) = \left\langle \frac{\partial z}{\partial x}, \frac{\partial z}{\partial y} \right\rangle \cdot \left\langle \frac{dx}{dt}, \frac{dy}{dt} \right\rangle

  2. Case 2: Multiple Independent Parameters (Surface Parameterizations)
    If x=g(u,v)x = g(u, v) and y=h(u,v)y = h(u, v) are differentiable functions of two independent variables uu and vv, then the partial rates of change are:

    ∂z∂u=∂z∂x∂x∂u+∂z∂y∂y∂u\frac{\partial z}{\partial u} = \frac{\partial z}{\partial x}\frac{\partial x}{\partial u} + \frac{\partial z}{\partial y}\frac{\partial y}{\partial u}
    ∂z∂v=∂z∂x∂x∂v+∂z∂y∂y∂v\frac{\partial z}{\partial v} = \frac{\partial z}{\partial x}\frac{\partial x}{\partial v} + \frac{\partial z}{\partial y}\frac{\partial y}{\partial v}

  3. Implicit Differentiation Formulas

    • For a level curve defined implicitly by F(x,y)=0F(x, y) = 0 where Fy≠0F_y \neq 0:
      dydx=−FxFy=−∂F∂x∂F∂y\frac{dy}{dx} = -\frac{F_x}{F_y} = -\frac{\frac{\partial F}{\partial x}}{\frac{\partial F}{\partial y}}
    • For a level surface defined implicitly by F(x,y,z)=0F(x, y, z) = 0 where Fz≠0F_z \neq 0:
      ∂z∂x=−FxFz,∂z∂y=−FyFz\frac{\partial z}{\partial x} = -\frac{F_x}{F_z}, \qquad \frac{\partial z}{\partial y} = -\frac{F_y}{F_z}

Concept Explanation

The Dependency Tree Mental Model

When a system output depends on intermediate variables that simultaneously depend on one or more independent driving inputs, changes ripple across multiple paths at once. To determine the rate of change with respect to an input, use a tree diagram:

  1. Top Level: The dependent output variable (zz).
  2. Intermediate Level: The variables directly fed into the function (x,yx, y).
  3. Bottom Level: The independent parameters driving the system (tt or u,vu, v).
             z                          z
           /   \                      /   \
          x     y                    x     y
          |     |                   / \   / \
          t     t                  u   v u   v

   Case 1: One Parameter           Case 2: Two Parameters

To compute the derivative of the top variable with respect to a bottom variable:

  • Multiply the derivatives along each connected branch from top to bottom.
  • Sum the resulting products across all parallel pathways leading to the same independent variable.

Total Derivative vs. Partial Derivative

  • An ordinary derivative dzdt\frac{dz}{dt} represents the total rate of change experienced as the parameter tt advances, accounting for all internal pathways changing concurrently.
  • A partial derivative ∂z∂x\frac{\partial z}{\partial x} isolates the rate of change purely along the xx-direction, artificially freezing yy as a constant.
  • When an object moves along a trajectory r⃗(t)=⟨x(t),y(t)⟩\vec{r}(t) = \langle x(t), y(t) \rangle, its sensory experience combines the spatial slopes of the landscape (nablaz\\nabla z) with its travel velocity (r⃗\x27(t)\vec{r}\x27(t)).

Derivation of Implicit Differentiation

Consider an implicit equation F(x,y)=0F(x, y) = 0 defining yy as a differentiable function of xx. Differentiating both sides with respect to xx using the multivariable chain rule (where xx depends on xx with dxdx=1\frac{dx}{dx} = 1, and yy depends on xx):

ddx[F(x,y)]=∂F∂xdxdx+∂F∂ydydx=0\frac{d}{dx}[F(x, y)] = \frac{\partial F}{\partial x}\frac{dx}{dx} + \frac{\partial F}{\partial y}\frac{dy}{dx} = 0
Fx(1)+Fydydx=0  ⟹  Fydydx=−Fx  ⟹  dydx=−FxFyF_x (1) + F_y \frac{dy}{dx} = 0 \implies F_y \frac{dy}{dx} = -F_x \implies \frac{dy}{dx} = -\frac{F_x}{F_y}
The negative sign arises directly from moving the partial FxF_x to the opposite side of the equation when isolating dydx\frac{dy}{dx}.


Engineering Applications


Example Problems

Example 1: Trajectory Rate of Change (Case 1)

A thermal sensor moves across a hot metal plate with temperature profile T(x,y)=2x2y+y3T(x, y) = 2x^2 y + y^3 (in ∘C^\circ\text{C}). The sensor\x27s coordinates (in meters) follow the parametric path x(t)=3tx(t) = 3t, y(t)=t2+1y(t) = t^2 + 1, where tt is in seconds. Find the rate of temperature change dTdt\frac{dT}{dt} recorded by the sensor at t=1 st = 1\text{ s}.

Solution
  1. State Governing Equation:
    dTdt=∂T∂xdxdt+∂T∂ydydt\frac{dT}{dt} = \frac{\partial T}{\partial x}\frac{dx}{dt} + \frac{\partial T}{\partial y}\frac{dy}{dt}
  2. Compute Spatial Partials:
    ∂T∂x=4xy,∂T∂y=2x2+3y2\frac{\partial T}{\partial x} = 4xy, \qquad \frac{\partial T}{\partial y} = 2x^2 + 3y^2
  3. Compute Velocity Components:
    dxdt=3,dydt=2t\frac{dx}{dt} = 3, \qquad \frac{dy}{dt} = 2t
  4. Evaluate at t=1t = 1:
    • Coordinates: x(1)=3(1)=3x(1) = 3(1) = 3, y(1)=12+1=2y(1) = 1^2 + 1 = 2.
    • Partials: ∂T∂x(3,2)=4(3)(2)=24\frac{\partial T}{\partial x}(3, 2) = 4(3)(2) = 24, ∂T∂y(3,2)=2(3)2+3(2)2=18+12=30\frac{\partial T}{\partial y}(3, 2) = 2(3)^2 + 3(2)^2 = 18 + 12 = 30.
    • Velocities: dxdt=3\frac{dx}{dt} = 3, dydt=2(1)=2\frac{dy}{dt} = 2(1) = 2.
  5. Synthesize:
    dTdt=(24)(3)+(30)(2)=72+60=132∘C/s\frac{dT}{dt} = (24)(3) + (30)(2) = 72 + 60 = 132^\circ\text{C/s}

Example 2: Implicit Differentiation of a Closed Surface

Find the rate of vertical elevation change ∂z∂x\frac{\partial z}{\partial x} on the ellipsoid x2+4y2+9z2=36x^2 + 4y^2 + 9z^2 = 36 at the point (2,2,43)(2, 2, \frac{4}{3}).

Solution
  1. Define the Level Surface Function:
    F(x,y,z)=x2+4y2+9z2−36=0F(x, y, z) = x^2 + 4y^2 + 9z^2 - 36 = 0
  2. State Governing Formula:
    ∂z∂x=−FxFz\frac{\partial z}{\partial x} = -\frac{F_x}{F_z}
  3. Compute Partial Derivatives of FF:
    Fx=∂∂x[x2+4y2+9z2−36]=2xF_x = \frac{\partial}{\partial x}[x^2 + 4y^2 + 9z^2 - 36] = 2x
    Fz=∂∂z[x2+4y2+9z2−36]=18zF_z = \frac{\partial}{\partial z}[x^2 + 4y^2 + 9z^2 - 36] = 18z
  4. Assemble and Evaluate at (2,2,43)(2, 2, \frac{4}{3}):
    ∂z∂x=−2x18z=−x9z\frac{\partial z}{\partial x} = -\frac{2x}{18z} = -\frac{x}{9z}
    ∂z∂x∣(2,2,4/3)=−29(43)=−212=−16\frac{\partial z}{\partial x}\Big|_{(2, 2, 4/3)} = -\frac{2}{9\left(\frac{4}{3}\right)} = -\frac{2}{12} = -\frac{1}{6}

Connections & References