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Published byKorbin Bracy Modified over 4 years ago

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Determinants and Areas

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The intention here is to prove that application of a 2 x 2 matrix to regions of the plane multiplies the area by the absolute value of the determinant of the matrix.

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Begin with a unit square: (1,0) (0,1)

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Transform this by a matrix (1,0) (0,1)

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Transform this by a matrix (1,0) (0,1) (a,c)

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Transform this by a matrix (1,0) (0,1) (b,d)

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(1,0) (0,1) (b,d) (a,c) So the unit square is transformed into a parallelogram (a+b,c+d)

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) We need to show that the area of the parallelogram is |ad-bc|

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) The base of the parallelogram has length (a 2 +c 2 ) 1/2 (a 2 +c 2 ) 1/2

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) We need the altitude (a 2 +c 2 ) 1/2 ?

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) The residual projection of (b,d) onto (a,c) is an altitude

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) This projection is (a 2 +c 2 ) 1/2 ?

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) By the Pythagorean Theorem its length squared is the difference in the squared lengths of (b,d) and …

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) By the Pythagorean Theorem its length squared is the difference in the squared lengths of (b,d) and the projection of (b.d) onto (a,c)

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So the altitude is

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) So the area is (a 2 +c 2 ) 1/2 |ad-bc| ---------- (a 2 +c 2 ) 1/2

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(1,0) (0,1) (b,d) (a,c) (a+b,c+d) (a 2 +c 2 ) 1/2 |ad-bc| ---------- (a 2 +c 2 ) 1/2 But the determinant of is ad-bc, so the area has been multiplied by |determinant|.

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We proved that application of a 2 x 2 matrix to a unit square of the plane multiplies the area by the absolute value of the determinant of the matrix.

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What about the areas of any figures in the plane? Under transformation are they simply multiplied by the absolute value of the determinant?

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If we transform small boxes, the area of each box is multiplied by the absolute value of the determinant of the matrix.

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But the area of any figure is approximated by the sum of the areas of small boxes contained in the figure

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So the area of the transformed figure is the area of the original figure multiplied by the absolute value of the determinant of the matrix.

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Let’s use this for a nifty application. Suppose we first transform the square using the matrix A. We now know how the area will change A

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Let’s use this for a nifty application. Suppose we first transform the square using the matrix A. We now know how the area will change – by a factor of |det(A)|. A But then we do a second transformation using matrix B: the area will then change by a factor of |det(B)|. B

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Let’s use this for a nifty application. Suppose we first transform the square using the matrix A. We now know how the area will change – by a factor of |det(A)|. A But then we do a second transformation using matrix B: the area will then change by a factor of |det(B)|. Thus, relative to the original square the area has changed by |det(A)|x|det(B)|. B

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We could have skipped the intermediate step, however, and transformed the square by the product BA. BA

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We could have skipped the intermediate step, however, and transformed the square by the product BA. The area must change by the factor |det(BA)|. BA

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We could have skipped the intermediate step, however, and transformed the square by the product BA. The area must change by the factor |det(BA)|. We have just proved that |det(A)| x|det(B)| = |det(BA)|, and by reversing the roles of A and B we have |det(B)| x|det(A)| = |det(AB)|, BA

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We could have skipped the intermediate step, however, and transformed the square by the product BA. The area must change by the factor |det(BA)|. We have just proved that |det(A)| x|det(B)| = |det(BA)|, and by reversing the roles of A and B we have |det(B)| x|det(A)| = |det(AB)|, so |det(AB)| = |det(B)| x|det(A)| = |det(A)| x|det(B)| = |det(BA)|. BA

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We actually could prove that the absolute values could be dropped so that det(A) x det(B) = det (AB) = det (BA)

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We actually could prove that the absolute values could be dropped so that det(A) x det(B) = det (AB) = det (BA) and this holds for any n by n matrices.

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