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sayitwithscience:

The del operator, denoted with what is called the nabla symbol (an inverted delta), is a differential operator connecting differential calculus of functions to the study of vectors, and vector-valued functions. The del operator has several forms, and is defined by

where ∂/∂x indicates the partial derivative with respect to x (similarly for y and z), and i, j, and k indicate the three standard unit vectors (all in the Cartesian coordinate system).

To a scalar function, F(x,y,z), in the Cartesian coordinate system, the del operator may be applied to create what is known as the gradient of F — defined as

The inclusion of the unit vectors in ∇ lead to the gradient’s being a vector-valued function in three dimensions, and the vector consequently is directed toward the greatest increase in F, at any point (x,y,z). Its magnitude is equal to the maximum rate of increase, and hence may be used as an analog to the 1-dimensional derivative, in 3 dimensions.

When ∇ is applied to a scalar field (function) of the form F(x,y,z), and a vector field a (= <a_1, a_2, a_3>) is chosen, the directional derivative takes the form

in which the dot-product of the gradient of F and and the vector a is taken. The most common analogy is this: if ∂F/∂x gives the rate of change of F in the x direction, then ∇F • a gives the rate of change of F, in vector form, toward the vector a. a is taken to be the unit vector for this calculation. This operation allows the rate of change of a scalar field with respect to an arbitrary — and sometimes changing — direction of a vector (a need not be a vector composed only of constant components), to be calculated. Its most common application for this operation lies in the field of fluid dynamics.

Coming soon: ∇applied to vector functions!

sayitwithscience:

After being introduced to the concept of a limit and the derivative, the typical calculus student is asked to evaluate simple antiderivatives and apply a strange symbol, ∫, much like an elongated “S”, to their notation. He then completely shifts gears, and applies his knowledge of limits to summations of rectangular areas, of which there are an infinite amount, and all with vanishingly small width. After establishing the techniques used in finding exact areas bounded by curves, he is asked again to apply ∫ to the function whose area it is he must calculate…and is left to his own devices to interpret the Fundamental Theorem of Calculus (FTOC) — the theorem which relates the derivative to bounds of a definite integral, and the area bounded by a function to its antiderivative. Few introductory calculus courses take the time to prove the theorem, and simultaneously probe the intricate connections that definite integration has with differential calculus.

The first part of the FTOC is as follows: a function

is a general antiderivative of f such that A’(x) = f(x). The proof of this part is lengthy, but less conceptually rigorous than the second.

Second part of FTOC — Prove:

Proof: Consider F, a function which is a general antiderivative of f. Also consider an antiderivative of f, A — for simplicity, the same as that which was used in the first part of the FTOC. Because F and A are both antiderivatives of f which differ by a constant of integration, C, you may then make a relation such that

where C is a constant. Substituting x = a into this equation brings you to the following relation:

(by early properties of definite integrals, the region has a width of 0). Substituting x = b,

which, when rearranged, yields

(Note: there are many proofs of the FTOC and its corollaries, so it’d be wise to browse through as many as you can find!)

It helps to introduce a bit of generalization for the purpose of understanding the geometric significance of the FTOC (coupled with the picture above): the gradient of a small target region of a function is approximated by ∆y/∆x, whereas the area of that small region may be approximated by ∆y•∆x — inverse operations, correlating directly to the inverse relationship between differentiation and integration.