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vector calculus.
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Q1: What, in your own words, is the difference between a partial derivative and a directional derivative? How are they simila
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1. Directional derivative is the instantaneous rate of change (which is a scalar) of f(x,y, z) in the direction of the unit vector u. The directional derivative is a number; it is the rate of change when your point in R3 moves in that direction. (You can imagine "reducing" your function to a function of a single variable, say tt, by "slicing" the curve in that direction; the directional derivative is just then the 1-D derivative of that "sliced" function.)

Partial Derivative is the rate of change of f(x,y, z), along x, y and z directions, which can be thought of the slope of the function at a point (x0, y0, z0). The gradient is a vector; it points in the direction of steepest ascent.

In simple words, directional derivative can be visualized as slope of the function at the given point along a particular direction. For example partial derivative w.r.t x of a function can also be written as directional derivative of that function along x direction. So, the gradient is a vector with the slope of the function along each of the coordinate axes whereas the directional derivative is the slope in an arbitrary specified direction.

2. If Duf(x0, y0)=0, then f is constant in the direction u i.e., if we consider the values of f along the line in the direction u, we find that there is no linear-order term:

f(x0+t u, y0+s u) = f(x0, y0) + t Duf(x0, y0 + s u) + s Duf(x0 + t u, y0) +O(t, s) = f(x0, y0) + O(t, s).

(Here O(t, s) is some function such that O (t, s) → 0 as t→0, s→0.)

Instead of considering a line / plane, we can consider the level set . So long as (x0, y0) isn't a critical point of f, this level set will (at least in some neighborhood of (x0, y0) be a curve. Thus, f is constant along a curve in the direction u.

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