M408M Learning Module Pages
Main page Chapter 10: Parametric Equations and Polar CoordinatesChapter 12: Vectors and the Geometry of SpaceChapter 13: Vector FunctionsChapter 14: Partial DerivativesLearning 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:DifferentiabilityChain 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 ruleThe 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
The reason behind the chain rule is simple. Since f(x,y) is differentiable, we can approximate changes in f by its linearization, so Δf≈fxΔx+fyΔy. Dividing by Δt and taking a limit as Δt→0 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=∂f∂xdxdt+∂f∂ydydt+∂f∂zdzdt.
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.
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