Exercise 3.3 · Q8: is symmetric and is skew symmetric
For the matrix
verify that
(i) is a symmetric matrix
(ii) is a skew symmetric matrix
(i)
So is a symmetric matrix.
(ii)
So is a skew symmetric matrix.
Want the reason behind every step, the basics and the checks?
itself is neither symmetric nor skew symmetric: its off-diagonal entries are 5 and 6. Adding puts in both off-diagonal places, so the mirror pairs become equal. Subtracting gives in one place and in the other, so the mirror pairs become opposite, and the diagonal entries cancel to 0. This is Theorem 1 of the chapter, seen in one example.
- Given
- A matrix .
- To show
- (i) ; (ii) .
- Plan
- (1) Write . (2) Compute , transpose it, compare. (3) Compute , transpose it, compare with its negative. (4) Explain why this always happens.
Basics you need
. For a matrix the off-diagonal entries swap. Basics: mirror patterns
Square is symmetric if , and skew symmetric if . Lesson: symmetric and skew symmetric
Matrices of the same order are added or subtracted entry by entry. Basics: adding only like with like
Solution
Write
Rows and become columns:
and are both , so and are defined and are (square, so symmetry can be tested).
Transpose, Definition 3 (Basic 1).(i) Compute
The two off-diagonal entries are and . Addition of numbers is commutative, so they are the same number, 11. That is the whole reason comes out symmetric.Sum entry by entry, Section 3.4.1 (Basic 3).(i) Transpose and compare
Let . Swapping its off-diagonal entries (both 11) changes nothing:
So and is symmetric.
Definition 4: symmetric means . Lesson: symmetric matrices(ii) Compute
Each diagonal entry is a number minus itself, so it is 0. The off-diagonal entries are and : the same subtraction done in opposite orders, which gives opposite numbers.(ii) Transpose and compare with the negative
Let . Then
So and is skew symmetric.
Definition 5: skew symmetric means . Lesson: skew symmetric matricesWhy it works for every square matrix
For any square matrix , using the rules of Section 3.5.1:
The first line says is always symmetric, the second that is always skew symmetric.
The computation in Steps 2 to 5 checks one matrix; these two lines prove the statement for all square matrices. It is Theorem 1 of Section 3.6. The facts used are , , and that matrix addition is commutative.Theorem 1, Section 3.6; properties (i), (iii) of Section 3.5.1. Lesson: symmetric and skew symmetric
The first equals its transpose, so it is symmetric; the transpose of the second is its negative, so it is skew symmetric. Both are verified.
Half the sum plus half the difference must give back : , , , . These are the entries of . ✓ (This split is exactly what Question 10 asks for.)
- Transposing wrongly. Only the off-diagonal entries 5 and 6 swap; the diagonal 1, 7 stays.
- Comparing with instead of . Skew symmetric means .
- Stopping at the sums. "Verify symmetric" needs the transpose to be written and compared.
- For every square : is symmetric and is skew symmetric (Theorem 1).
- Off-diagonal: is the same in both mirror places; and are opposite.
- , the starting point of Theorem 2.
Every fact used, and where it comes from
| Fact | Used in | Source |
|---|---|---|
| Transpose | Steps 1, 3, 5 | Definition 3, Section 3.5 (Lesson: transpose) |
| Sum and difference entry by entry | Steps 2, 4 | Sections 3.4.1, 3.4.2 |
| Symmetric ; skew symmetric | Steps 3, 5 | Definitions 4 and 5, Section 3.6 (Lesson) |
| , | Step 6 | Section 3.5.1, properties (i), (iii) |
| symmetric, skew symmetric | Step 6 | Theorem 1, Section 3.6 |
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