Exercise 4.4 · Q13: Show ; hence find
If
show that . Hence find .
Hence .
Now , so exists. Post-multiplying by ,
Want the reason behind every step, the basics and the checks?
A matrix equation such as can be rearranged like ordinary algebra, as long as the order of multiplication is respected. Multiplying it by lowers every power of by one and turns into , so can be read off as without computing any cofactors.
- Given
- The matrix above; is the identity and the zero matrix.
- To show / find
- ; then .
- Plan
- (1) Compute . (2) Compute and and combine, entry by entry. (3) Check so exists. (4) Multiply the equation by and solve for . (5) Check by and against the adjoint.
Basics you need
means , a matrix product (row times column), not the squares of the entries. Basics: matrix facts the chapter uses
multiplies every entry by 5; matrices of the same order are added entry by entry. Basics: scaling and adding matrices
, and . exists exactly when (Theorem 4). Basics: why the inverse divides by |A|
The book shows, for another matrix, how an equation of this kind gives . Example 15
Solution
Compute
is , so is defined and is .
Each entry is a row of the first times a column of the second . For : row 2 is and column 1 is , giving . Squaring the entries instead () would be wrong.Pair up, multiply, add. Basics: matrix facts the chapter usesCombine
All three matrices are , so the combination is defined. Entry by entry:
So , as required.
The identity matrix has only on the diagonal, so it changes only the diagonal entries. The off-diagonal entries of and already agree, which is why they cancel to .Add and subtract matrices of the same order entry by entry. Basics: scaling and adding matricesMake sure exists
, so is non-singular and exists (Theorem 4).
The next step multiplies by . That is only allowed if exists, so we confirm it first, exactly as the book does in Example 15 ("because ").Multiply the equation by
Start from , that is . Multiply every term on the right by :
Solve for :
Matrix multiplication distributes over addition, , so post-multiplying the whole left side means post-multiplying each term. Associativity lets us regroup as . Then , , and . Every term was multiplied on the same side (the right), which matters because matrix products are not commutative in general.Compute
has on the diagonal and elsewhere, so only the diagonal entries of gain a . As a cross-check, the adjoint method gives the same thing: swaps and and negates and , giving the matrix with rows and , and .Check:
Multiply by the integer matrix, then divide by 7:
The product is before dividing, which is , exactly what (Theorem 1) predicts.
holds, and
(Textbook answer: times the matrix with rows and .)
The other order: has entry and entry ✓. Also should be . The entries of are (row 1) and (row 2), so is , that is ✓.
- Squaring entries. is ; its entry is , not .
- Writing instead of . A number cannot be added to a matrix; the equation has , and multiplying it by gives .
- Multiplying different terms on different sides. Multiply every term by on the same side.
- Getting instead of . From , moving terms gives .
- If with , then . Here , .
- Always confirm exists before multiplying by it.
- Check the answer two ways: , and against .
Every fact used, and where it comes from
| Fact | Used in | Source |
|---|---|---|
| Row-times-column product; | Steps 1, 6 | Chapter 3, Section 3.4.5 |
| Scalar multiples, sums, distributive law | Steps 2, 4 | Chapter 3, Sections 3.4.2–3.4.6 |
| invertible ; | Steps 3, 5 | Theorem 4, Section 4.5 (Lesson: inverse) |
| adjoint rule | Step 5 | Remark after Example 12, Section 4.5.1 |
| Step 6 | Theorem 1, Section 4.5 | |
| Post-multiplying by to find the inverse | Step 4 | Example 15 |
| All entries and the check | Steps 1–6, Check | Recomputed in the site's verification script |
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