2.6.8 · D4Matrices & Determinants — Introduction

Exercises — Determinant of 3×3 matrix — cofactor expansion

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Before we start, one shared vocabulary reminder so nothing below is a surprise.

The checkerboard of signs — read position and this tells you the before you touch any minor:


Level 1 — Recognition

Goal: can you read the sign pattern and pick the smart row/column?

Exercise L1.1

State the sign for each of these positions: , , , .

Recall Solution L1.1

WHAT we do: add the two indices, then ask "even or odd?" Even , odd .

  • : , even
  • : , odd
  • : , odd
  • : , even

WHAT IT LOOKS LIKE: check them against the checkerboard picture — the four cells light up exactly . The signs never depend on the numbers in the matrix, only on the position.

Exercise L1.2

For the matrix which single row or column should you expand along to do the least work, and why?

Recall Solution L1.2

WHAT we look for: the line (row or column) with the most zeros. Every zero entry kills its whole cofactor term (zero times anything is zero), so a zero means "one fewer determinant to compute."

Scan: column 2 is two zeros. No other row or column beats that.

Answer: expand along column 2. Only one term survives: WHY it matters: the lazy-but-correct choice cuts three minors down to one.


Level 2 — Application

Goal: run the full algorithm end-to-end.

Exercise L2.1

Compute for by expanding along row 2 (this is Practice Problem 1 from the parent).

Recall Solution L2.1

WHY row 2? It contains a at position , so one term vanishes.

Row-2 entries are . Their checkerboard signs (read the middle row of the pattern) are .

Cofactor — sign ; cross out row 2, column 1:

Cofactor — sign ; cross out row 2, column 3:

Sum:

Check with row 1 (WHY: to feel the invariance — different path, same answer). Entries , signs :

Exercise L2.2

Compute for by expanding along column 1.

Recall Solution L2.2

WHY column 1? It has a at , so one of three terms disappears.

Column-1 entries , signs (left column of checkerboard) .

— sign ; delete row 1, column 1:

— sign ; delete row 3, column 1:

Sum:


Level 3 — Analysis

Goal: use structure (triangular form, zero rows) instead of brute force, and interpret the answer.

Exercise L3.1

Show that for the upper-triangular matrix expanding along column 1 gives the same result as expanding along row 1, and state the general pattern (Practice Problem 3 from the parent).

Recall Solution L3.1

Along column 1. Entries with signs . Only the first survives:

Along row 1. Entries with signs :

Same answer, — confirming the parent's "different path, same destination."

General pattern: for any triangular matrix (all zeros on one side of the diagonal) the determinant is the product of the diagonal entries. Here . WHY: expanding down the zero column always leaves exactly one nonzero term — the diagonal entry times the smaller triangular block — and that recursion multiplies the diagonal all the way down. See properties of determinants.

Exercise L3.2

Compute and interpret it geometrically:

Recall Solution L3.2

Structural observation first. Look at rows 1 and 2: . Row 2 is a scalar multiple of row 1 — the two rows point along the same line in space.

Expand along row 3 to confirm. Entries , signs :

Geometric meaning (WHAT IT LOOKS LIKE): three row-vectors normally span a solid box (a parallelepiped) with some volume. Here two of them lie on one line, so the "box" is squashed flat — zero thickness, hence zero volume, zero determinant. See the figure below.

Figure — Determinant of 3×3 matrix — cofactor expansion

Level 4 — Synthesis

Goal: combine cofactor expansion with an unknown, and with an outside idea (Cramer / cross product).

Exercise L4.1

Find all values of for which is singular (i.e. ).

Recall Solution L4.1

WHY set ? A matrix is singular exactly when its determinant vanishes — that is when it has no inverse; see determinant and inverse.

Expand along column 1 (it has a zero at ). Entries .

— sign ; delete row 1, column 1:

— sign ; delete row 2, column 1:

The third entry kills its term. Assemble, entry-times-cofactor:

Set to zero and factor:

Sanity check : And (should be nonzero): , so is invertible.

Exercise L4.2

The cross product can be written as a symbolic determinant (see cross product and determinants): Using cofactor expansion along row 1, compute for and .

Recall Solution L4.2

WHY expand along row 1? Row 1 holds the basis vectors ; expanding there peels off one component of the result per cofactor. Signs .

Compute each :

Assemble, minding the middle minus sign:

Check (perpendicularity): a cross product is perpendicular to both inputs, so its dot with should be :


Level 5 — Mastery

Goal: chain multiple determinants together to solve a real system.

Exercise L5.1

Solve for only, using Cramer's rule, in the system

Recall Solution L5.1

WHAT Cramer's rule says: for , the unknown , where is with its second column replaced by the right-hand side . WHY it works: replacing a column by and taking determinants isolates that one variable through the linearity of the determinant.

Coefficient matrix and its determinant. WHY expand along row 1? No row or column of has a zero, so no choice saves work; we default to row 1 for consistency (any row gives the same number, as L3.1 showed). Signs :

Since , the system has a unique solution — Cramer's rule is valid.

Build (replace column 2 with ). WHY row 1 again? Same reason — no zeros anywhere, so we keep the same row for a clean parallel comparison. Signs :

Therefore:

Full-solution check (not required, but reassuring — WHY: an independent route should reproduce ). Solving all three equations simultaneously gives Verify each equation with these values:

  • Eq 1: … that is , so these values are wrong — a warning that guessing round numbers is dangerous. Let us solve properly.

Solve properly (elimination). From Eq 1, . Substitute into Eq 2 and Eq 3:

  • Eq 2:
  • Eq 3:

Subtract the first reduced equation from the second: Then , and

The true solution is . Check Eq 2: Check Eq 3:

Both routes agree: . Cramer's rule delivered the right value directly, and the full elimination confirms it.


Recall Quick self-test before you leave

The determinant does not depend on which row/column you expand along. ::: True — it is a fixed property of the matrix; expansion choice only changes the arithmetic route. A row that is a multiple of another row forces the determinant to be… ::: (the box is flat, zero volume). To solve for the -th variable by Cramer's rule you replace… ::: the -th column of with the right-hand-side vector . The sign attached to entry is… ::: , depending only on position, never on the entry's value.