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M408M Learning Module Pages

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Chapter 10: Parametric Equations and Polar Coordinates

Chapter 12: Vectors and the Geometry of Space


Chapter 13: Vector Functions


Chapter 14: Partial Derivatives


Learning module LM 14.1: Functions of 2 or 3 variables:

Learning module LM 14.3: Partial derivatives:

Learning module LM 14.4: Tangent planes and linear approximations:

Learning module LM 14.5: Differentiability and the chain rule:

      Differentiability
      Chain rule
      General chain rule
      Worked problems

Learning module LM 14.6: Gradients and directional derivatives:

Learning module LM 14.7: Local maxima and minima:

Learning module LM 14.8: Absolute maxima and Lagrange multipliers:

Chapter 15: Multiple Integrals



Chain rule

Chain Rule

The composition of differentiable functions is differentiable. In particular, if x(t) and y(t) are differentiable functions of a parameter t, and if f(x,y) is a differentiable function of x and y, then f(x(t),y(t)) is a differentiable function of t. We compute its derivative with the chain rule

Chain rule (simple case): Suppose that f(x,y) is a differentiable function of (x,y), and that r(t) is a differentiable parametrized curve in the x-y plane. Then f(r(t)) is a differentiable function of t, and df(r(t))dt=fx(r(t))x(t)+fy(r(t))y(t). This is also written as df(r(t))dt=fxdxdt+fydydt.


The reason behind the chain rule is simple. Since f(x,y) is differentiable, we can approximate changes in f by its linearization, so ΔffxΔx+fyΔy. Dividing by Δt and taking a limit as Δt0 gives the chain rule. For functions of three of more variables, we just add a term for each variable. If f(x,y,z) is a function of three variables, then df(r(t))dt=fxdxdt+fydydt+fzdzdt.

  Example 1: The temperature at a point (x,y) in the plane is T(x,y)C. If a bug crawls on the plane so that its position at time t (in minutes) is given by x(t)=1+t,y(t)=5+13t, determine how fast the temperature is rising on the bug's path after 3 minutes when Tx(2,6) = 20,Ty(2,6) = 3.
Solution: the temperature on the bug's path is S(t)=T(x(t),y(t)). Thus by the Chain Rule for Paths, dSdt = Txdxdt+Tydydt.
But dxdt=121+t,dydt=13. Thus dTdt = 121+tTx+13Ty. Now when t=3, the bug is at the point (2,6), in which case Tx(2,6) = 20,Ty(2,6) = 3. Consequently, dTdt = 204+13×3 = 6C/min.


Implicit Differentiation Revisited. Back in single-variable calculus, we used the single-variable chain rule to compute dy/dx for the level set of a function f(x,y). Let's see what that means in terms of partial derivatives.

Let C be a curve defined by an equation f(x,y)=c, and let r(t) be a parametrization of that curve. Since f(r(t))=c for all t, df/dt=0. But by the chain rule, fxdxdt+fydydt=dfdt=0, so dydx=dy/dtdx/dt=fxfy. Note that the vector fy,fx is tangent to the curve, while the vector fx,fy is perpendicular to fy,fx, and so is perpendicular to the curve. The line through (a,b) and perpendicular to the curve is called the normal line.

  Example 2: Find the slope of the tangent line and the normal line to the curve x3+y2=5 at the point (1,2).

Solution: Let f(x,y)=x3+y2. Then fx=3x2andfy=2y and dydx=3x22y.
Plugging in (x,y)=(1,2) gives dydx=34. This is the slope of the tangent line. The normal line has slope fyfx=2y3x2=43.