Math 260, Fall 2018, Assignment 3

We admit, in geometry, not only infinite magnitudes, that is to say, magnitudes greater than any assignable magnitude, but infinite magnitudes infinitely greater, the one than the other. This astonishes our dimension of brains, which is only about six inches long, five broad, and six in depth, in the largest heads.

- Voltaire

Carefully define the following terms, then give one example and one non-example of each:

1. $n\times m$ matrix.
2. $n$-component column vector.
3. $\mathbb{R}^n$.
4. $n$-component row vector.
5. $\left(\mathbb{R}^n\right)^*$.
6. Geometric vector.
7. Addition (of matrices, or of column vectors).
8. Addition (of geometric vectors).
9. Scalar multiplication (of matrices, or of column vectors).
10. Scalar multiplication (of geometric vectors).
11. Dot product (of two column vectors).
12. Length (of a column vector).
13. Angle (between two non-zero column vectors).

Carefully describe the following algorithms:

1. Procedure to write all solutions of a linear system, once it is in reduced row-echelon form.

Carefully state the following theorems (you do not need to prove them):

1. Numerical instability of Gauss-Jordan elimination. (This is not really a theorem, but please be able to give an example of an alarming loss of precision when this algorithm is used to solve a system of linear equations.)

Solve the following problems:

1. Section 1.3, problems 10, 11, 12, 27, and 28.
2. Section 5.1, problems 1, 3, 5, 6, 7, 8, 9, and 10.
3. In ordinary three-dimensional space, is it possible for two planes to intersect in exactly one point? Give a rigorous algebraic proof of your answer. (Hint: each plane is represented by an equation, so their intersection is the solution set of a $2\times 3$ system of linear equations (whose augmented matrix is thus a $2\times 4$ matrix), and this is equivalent to some system in reduced row-echelon form. Now think about all of the possible "types" (as defined in exercise 1.2.22, last week) of $2\times 4$ matrices.)

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