#matrices

38 messages · Page 1 of 1 (latest)

slim loom
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why is the answer not 100?

fierce crystalBOT
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buoyant aspen
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Do you know the formula?

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A(Adj(A)) = ?

slim loom
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|A|^n-1

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n is 2 here

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i was trying to think of matrices like vectors
but it isnt making sense

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like if theres a matrix of a column or a row it can be thought of like a vector

buoyant aspen
slim loom
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yeah

buoyant aspen
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I is:

[1 0]
[0 1]

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So |A| is 10.

slim loom
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im just confused
so far ive been thinking of the determinant as a magnitude
like for example if theres a vector <5,5> its magnitude is 5sqrt2 (and the answer stays the same whether i take the scalar 5 out or not) but here when i tried to do that im getting different answers

slim loom
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i meant this

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what am i getting wrong?

buoyant aspen
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Why are you making it so difficult?

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It's a direct formula.

slim loom
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it feels off to me

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ill have to review the defination maybe. i dont get that

buoyant aspen
fervent steeple
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adj A is the complex conjugate of the transpose of A, right?

fervent steeple
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@bronze bone would you mind enlightening me?

bronze bone
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Its the matrix of cofactors transposed per the definition

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Adjugates aren't adjoints

fervent steeple
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Ah that explains it, thanks

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Been a while since I last touched Cramer's rule

slim loom
fervent steeple
# slim loom ???

Your intuition that the determinant as akin to a magnitude is correct to some extent
The determinant is multilinear though, so it gets scaled up every time a column (or each row) is scaled up

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So for a nxn matrix A, |cA| = c^n |A|

slim loom
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its hard to visualize

slim loom
quaint vector
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You can prove this by using properties of determinants