Dismiss Notice
Join Physics Forums Today!
The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

Gradient: Normal vs Direction of Increase

  1. Mar 10, 2010 #1
    Hi,

    I'm having trouble understanding what exactly the gradient of a scalar field represents. According to wikipedia and the textbooks I have it points in the direction of greatest increase and has a magnitude of greatest increase. This by itself seems fine. However, I have also been using it to find the normal of a surface and I don't understand how it can be both.

    Also, do the properties( eg, what it represents) of the gradient change as you change dimensions and how does it work on a simple 2d graph?
     
  2. jcsd
  3. Mar 10, 2010 #2
    The gradient is perpendicular to the level sets of a function. So if your surface is given by f(v)=c, the normal at v is given by the direction of the gradient at v.
     
  4. Mar 10, 2010 #3

    quasar987

    User Avatar
    Science Advisor
    Homework Helper
    Gold Member

    It all comes from the formula <v,w>=|v||w|cosθ where θ is the angle between v and w.

    Let F:R³-->R be a function. By looking at the definition of DF(x)v for |v|=1 (the derivative of F at a point x in the direction of the vector v), we agree that this number represents the rate of change of F at x in the direction v. On the other hand, the gradient of F at x is defined as the (unique) vector ∇F(x) such that DF(x)v=<∇F(x),v> for all vectors v.

    So to ask in which direction is F increasing the most rapidly at x is to ask which vector v of unit lenght (|v|=1) maximizes the value of DF(x)v. But DF(x)v=<∇F(x),v>=|∇F(x)||v|cosθ=|∇F(x)|cosθ, with cosθ taking values between -1 and 1. Clearly, |∇F(x)|cosθ is largest when cosθ=1; i.e. when θ=0. That is, when v points in the direction of ∇F(x)!

    Now, consider S a surface in R³ that is realized as the level set F=c of F. That is, [itex]S=F^{-1}(c)[/itex] for some constant c. Take x a point in S. By definition, a tangent vector to S at x is a vector v of the form [itex]v=\gamma'(0)[/itex] for some curve [itex]\gamma:]-1,1[\rightarrow S[/itex] on S with [itex]\gamma(0)=x[/itex]. Notice that for [itex]v=\gamma'(0)[/itex] a tangent vector to S at x, the derivative of F at x in the direction v vanishes:

    [tex]DF(x)v=DF(x)\gamma'(0)=\frac{d}{dt}_{t=0}(F\circ\gamma)(t)=0[/tex]

    The second equality is the chain rule and the third equality is because the map [itex](F\circ\gamma)(t)[/itex] is the map [itex]t\mapsto c[/itex].
    Ok, so in terms of the gradient, what does this tells us? It tells us that 0=DF(x)v=<∇F(x),v>=|∇F(x)||v|cosθ, so cosθ=0, so θ=±90°. That is, ∇F(x) and v are perpendicular. By definition, this means ∇F(x) is perpendicular (or normal) to the surface S at the point x.
     
Know someone interested in this topic? Share this thread via Reddit, Google+, Twitter, or Facebook




Similar Discussions: Gradient: Normal vs Direction of Increase
  1. Gradient and normal (Replies: 2)

Loading...