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Linear Algebra

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Section I. Definition 309<br />

read aloud as “the sum, over all permutations φ, of terms having the form<br />

t1,φ(1)t2,φ(2) ···tn,φ(n)|Pφ|”. This phrase is just a restating of the three-step<br />

process (Step 1) for each permutation matrix, compute t1,φ(1)t2,φ(2) ···tn,φ(n) (Step 2) multiply that by |Pφ| and (Step 3) sum all such terms together.<br />

3.10 Example The familiar formula for the determinant of a 2×2 matrix can<br />

be derived in this way.<br />

�<br />

�<br />

�<br />

� t1,1<br />

�<br />

t1,2�<br />

�<br />

t2,1 t2,2�<br />

= t1,1t2,2 ·|Pφ1 | + t1,2t2,1 ·|Pφ2 |<br />

� �<br />

�<br />

= t1,1t2,2 · �1<br />

0�<br />

�<br />

�0 1�<br />

+ t1,2t2,1<br />

� �<br />

�<br />

· �0<br />

1�<br />

�<br />

�1 0�<br />

= t1,1t2,2 − t1,2t2,1<br />

(the second permutation matrix takes one row swap to pass to the identity).<br />

Similarly, the formula for the determinant of a 3×3 matrix is this.<br />

�<br />

�t1,1<br />

�<br />

�t2,1<br />

�<br />

�t3,1<br />

t1,2<br />

t2,2<br />

t3,2<br />

�<br />

t1,3�<br />

�<br />

t2,3�<br />

�<br />

t3,3�<br />

= t1,1t2,2t3,3 |Pφ1 | + t1,1t2,3t3,2 |Pφ2 | + t1,2t2,1t3,3 |Pφ3 |<br />

+ t1,2t2,3t3,1 |Pφ4 | + t1,3t2,1t3,2 |Pφ5 | + t1,3t2,2t3,1 |Pφ6 |<br />

= t1,1t2,2t3,3 − t1,1t2,3t3,2 − t1,2t2,1t3,3<br />

+ t1,2t2,3t3,1 + t1,3t2,1t3,2 − t1,3t2,2t3,1<br />

Computing a determinant by permutation expansion usually takes longer<br />

than Gauss’ method. However, here we are not trying to do the computation<br />

efficiently, we are instead trying to give a determinant formula that we can<br />

prove to be well-defined. While the permutation expansion is impractical for<br />

computations, it is useful in proofs. In particular, we can use it for the result<br />

that we are after.<br />

3.11 Theorem For each n there is a n×n determinant function.<br />

The proof is deferred to the following subsection. Also there is the proof of<br />

the next result (they share some features).<br />

3.12 Theorem The determinant of a matrix equals the determinant of its<br />

transpose.<br />

The consequence of this theorem is that, while we have so far stated results<br />

in terms of rows (e.g., determinants are multilinear in their rows, row swaps<br />

change the signum, etc.), all of the results also hold in terms of columns. The<br />

final result gives examples.<br />

3.13 Corollary A matrix with two equal columns is singular. Column swaps<br />

change the sign of a determinant. Determinants are multilinear in their columns.<br />

Proof. For the first statement, transposing the matrix results in a matrix with<br />

the same determinant, and with two equal rows, and hence a determinant of<br />

zero. The other two are proved in the same way. QED

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