#linear-algebra

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serene axle
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but this is false

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no mathematician sits down and just stares at a proof and suddenly figure out the steps in an instant

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they do it by trial and error

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there's a reason why all these stuff took thousands of years to build upon cause these patterns weren't easy to recognize in the first place.

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i know professors and some of your fellow classmates makes you feel this way

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but in reality they 100% did not sit down and just understood everything over night.

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if they do then they're most likely exaggerating. the human mind is not made for these type of things.

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that's why books exists to contain information.

wintry steppe
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I just don't understand why force everyone to learn this if it doesn't pertain to their field of study; This causes more stress and anxiety I ever felt before and trying to figure this out with a textbook that isn't very useful makes it even more difficult. I'm reading the chapter but it doesn't make it easier to understand how to find the answer to the math problem

serene axle
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universities just wants your money

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there's a reason why people call it garbage

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but to make garbage into gold you have to own up to it

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make the most out of it by enjoying it.

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i know it doesn't sit right but if you can enjoy the process it'll make things easier.

jagged saffron
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Would someone be able to help with showing well definedness for 2?

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I think i have to show that if

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$v_1 + W = v_1'+W$ then $<v_1+W,v_2+W> = <v_1'+W,v_2+W>$

stoic pythonBOT
jagged saffron
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To show this is well defined, consider $\langle v_1+W,v_2+W \rangle'$ and $\langle v_1'+W,v_2+W \rangle'$ such that $v_1 + W = v_1'+W$ . Then, we have to show that $\langle v_1+W,v_2+W \rangle' = \langle v_1'+W,v_2+W \rangle'$ But since by definition of equal cosets, we have that $v_1 - v_1' \in W$, so we have that $\langle v_1-v_1',v_2 \rangle = 0 = \langle v_1,v_2 \rangle - \langle v_1',v_2\rangle = \langle v_1+W,v_2+W \rangle' - \langle v_1'+W,v_2+W \rangle'$

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does this work?

stoic pythonBOT
jagged saffron
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also I'm kinda stuck on proving that the new inner product has the property of positive definiteness where <w,w> = 0 iff w = 0

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Positive definiteness: We just have to show that $\langle v_1+W,v_2+W \rangle' = 0$ iff $v_1+W = v_2+W$ as nonnegative is already given to us by our original function.
$\xrightarrow{}$ direction:
$\langle v_1+W,v_1+W\rangle' = 0 \xrightarrow{} \langle v_1,v_1 \rangle = 0$ Let $w_1 \in W$ then $\langle v_1+w_1,v_1 \rangle =\langle v_1+w_1+W,v_1+W\rangle'$ However, we showed in well definedness that this holds iff $v_1 +W = w_1 + W \xrightarrow{} v_1 + W = W \xrightarrow{} v_1 = 0$.

stoic pythonBOT
jagged saffron
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i think this is right? Im honestly not too sure

zealous kettle
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can I get help understanding this bit regarding elementary row operations? thanks

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I think one of the symbols is called kronecker delta? it was mentioned earlier but I dont know what it means

dusky epoch
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$\delta_{ij} = \begin{cases} 1 & i=j \ 0 & i\neq j \end{cases}$

stoic pythonBOT
zealous kettle
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huh, alright, thanks

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so delta_(ik_i) is 1 if i = k_i and 0 if i =/= k_i?

dusky epoch
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yes

zealous kettle
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thanks

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what does k mean?

dusty hare
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How does that factor to (x+1)(x+1)

winter reef
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(a+b)^2 = a^2 + 2ab + b^2

clever cedar
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is the inverse of a matrix A the same thing as the product of the elementary operations needed to get a matrix A to RREF

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in other words does U = A(inverse)

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also is the identity of a matrix the same thing as the RREF of a matrix

cobalt tartan
gray dust
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@clever cedar not always, if square matrix A is full rank, then yes rref(A) = I

cobalt tartan
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Like I think that it has something to do with the definition of a matrix fo a linear mapping?

clever cedar
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my textbook explained the form of B = UA and said that B is the reduced for echelon form of A, and U is the product of all elementary matricies needed to get A to RREF. Therefore A * U = B can only be possible if U is the inverse, correct?

quaint heart
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Full rank isn't enough

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You need invertible

clever cedar
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i should've stated that i assume the matrix is invertible

north sierra
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A = (1,2,3),(5,8,11)

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this would not span R^3 but is there a possibility of it spanning a plane in R^3 ?

clever cedar
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is the product of elementary row operations of A to A(inverse) the same thing as the inverse of A

clear otter
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@clever cedar if you take the product and multiply it by A, do you get hte identity matrix?

clever cedar
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funny u mention that, i actually just found the product of elementary row operations of to A(inverse) and it was A

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wait no

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that cant be true

clear otter
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@clever cedar if you think something is the inverse of another thing, say u and v, then it should satisfy u*v = identity

clever cedar
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ffs

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thats exactly why this is confusing

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for me

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i cant understand why we care about elementary row operations

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when we have that formula

clear otter
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So multiply out all of your elementary matrices to get a single matrix

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If it satisfies the above, then you've found an inverse.

clever cedar
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ty, i need some time to think over and reread

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thanks for ur time

half ice
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@north sierra
Those two vectors span a plane in R3, yes

north sierra
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okay

half ice
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Two linearly independent vectors span a 2D space

north sierra
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but it wouldnt span all of R^3 right

half ice
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Nop

north sierra
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okay

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i have a test tomorrow Kaynex

half ice
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There's many points in R3 that cannot be made with those vectors

north sierra
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thank you for the help these past few days

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also to everyone else that helped

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okay i see

half ice
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Np, anything else you want to ask? You seem pretty confident

north sierra
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yeah

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im good for now

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yes im confident now

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just hope i do good

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tomorrow

cobalt tartan
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So far my ideas are that uh

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R^n -> R^n are isomorphic

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And change of basis is linear

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But that's all I got

thorn robin
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try and draw a diagram

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you have B[L]C going from (R^n,B) to (R^n,C)

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and on a separate line draw C[L]B going from (R^n,C) to (R^n,B)

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connect the two rows of the diagram with vertical arrows P : (R^n,C) -> (R^n,B) which is the change of basis and P^{-1} on the other side

cobalt tartan
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Wait there's no P^{-1} though ?

thorn robin
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instead of P^{-1} you can just draw P going in the other direction

cobalt tartan
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Wait

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I'm confused

thorn robin
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one sec

cobalt tartan
thorn robin
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one of the top/bottom arrows points the wrong way

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depending on what B[L]C means

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otherwise yes

cobalt tartan
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Um

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In my book B[L]C means from a basis C to a basis B

thorn robin
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ok then the top arrow should point left

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wait I think that's wrong

cobalt tartan
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Wait it's cLb = PbLcP

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The arrows I think are in the right direction?

thorn robin
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I'm not sure I understand what you drew

cobalt tartan
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Um

thorn robin
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you have P going C to C

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and the other P going D(?) to B

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P should go C to B

cobalt tartan
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cLb goes from basis B to basis C

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Oh

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So P should be diagonal?

thorn robin
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here's what I have

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top row: C[L]B going B to C

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bottom row: B[L]C going C to B

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left column: P going up from C to B

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right column: P going down from C to B

cobalt tartan
thorn robin
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right

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the point of drawing this is just to organize our thoughts and see what is happening
it also suggests that the P you want to use to solve the problem is the change of basis matrix from C to B, just because that's what makes the diagram make sense

cobalt tartan
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Ah

thorn robin
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now to prove it you just have to take a vector in R^n and write it in C basis

cobalt tartan
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Wait I think that this diagram is slightly wrong

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Should be other way lol

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I want to show that (P)(bLc)(P) = (cLb)

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This diagram shows that (P)(cLb)(P) = (bLc)

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It's the same thing though

thorn robin
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ah yeah you're right
I thought the convention for the B and C subscripts was the opposite when I first looked at the question

cobalt tartan
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Yea

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Idk why they write it like that

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Is confusing

thorn robin
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so then you should take P to be the change of basis matrix from B to C

cobalt tartan
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Yea

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So if we have some change of basis matrix from B to C, multiplied by a change of basis matrix from C to B, multiplied by a change of abasis matrix B to C, we should end up with a change of basis matrix from B to C lol

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Now how do I state that mathematicalyy...

thorn robin
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what you said isn't quite what you want

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because you referred to all 4 matrices as change of bases

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but L is anything

cobalt tartan
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Ah right

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L is just some linear mapping

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Right

thorn robin
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stating it mathematically is just the equation given in the problem

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you just need to calculate what happens to a vector written in B basis when you apply the composition of the 3 matrices

cobalt tartan
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Hrm

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Wait

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Hrm

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It says to prove that there exists a matrix P

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Hrm

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Like that wouldn't prove that a matrix P exists, would it?

thorn robin
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we know there exists a matrix P that changes basis B into basis C

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I assume we can take that for granted, yes?

cobalt tartan
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Hrmm

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I mean

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THe question is basically saying to prove that such a matrix exists isn't it?

clear otter
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I think that's what they're trying to prove.

cobalt tartan
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"Prove that there exists a matrix P such that"

thorn robin
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oh hmm ok

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well then let's figure out how to write down P explictly

cobalt tartan
thorn robin
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how about using that definition on the identity map

cobalt tartan
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By the identity map you mean L:R^n->R^n, L((x1 ... x_n)) = (x_1 ... x_n) right?

thorn robin
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yup

cobalt tartan
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If we use the standard basis with the identity map then we'd just get the identity matrix

thorn robin
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then the property from the picture you posted is [v]C = C[I]B [v]B

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so take P = C[I]B

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yes that's true but we have two arbitrary bases, not the standard basis

cobalt tartan
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WHat is C[I]B?

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Is that identity?

thorn robin
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it's the matrix of the identity map in the bases B, C

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same notation as your picture

cobalt tartan
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Ah ok

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So if we have P = c[I]b, then (P)(bLc)(P) = (c[I]b)(bLc)(c[I]b)

thorn robin
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yes

cobalt tartan
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And if it's R^n->R^n, c[I]b must exist yea?

thorn robin
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any linear map has a matrix in any basis

cobalt tartan
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Yes

thorn robin
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regardless of whether it's R^n or the identity map

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so yes

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here are the two things you know: $P[v]_B = [v]_C$ and ${}_C[L]_B[v]_B = [Lv]_C$

stoic pythonBOT
thorn robin
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now you just need to use them to show that $P{}_B[L]_CP[v]_B = {}_C[L]_B[v]_B$

stoic pythonBOT
thorn robin
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which will give the statement the problem asks for since you will verify that this is true for every v

cobalt tartan
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Ah

thorn robin
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everything make sense?

cobalt tartan
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Um

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Kinda

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STill a bit muddlede

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But uh gonna take a few minutes to try to think through it

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And see if it makes more sense once I put it down on paper

thorn robin
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if you understand everything I wrote
then to prove it you just need to do the calculation I mentioned

cobalt tartan
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By the calculation you mentioned you mean $P{}_B[L]_CP[v]_B = {}_C[L]_B[v]_B$

stoic pythonBOT
cobalt tartan
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right?

thorn robin
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yes

cobalt tartan
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Ah, and (cLb)(v_b) = (Lv)_c because of linearity...?

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Ah, no, it's a definition

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Ok

thorn robin
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yeah I mean
it couldn't really be any other way

cobalt tartan
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Ah

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Ok I think I see now

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Like the actual math is kinda sketchy but like

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It makes sense logically now?

thorn robin
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what is sketchy?

cobalt tartan
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Mmmm

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I wrote it out like this

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Like

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Oh wait brackets are missing

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But uh

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I can't concievably see myself coming up with that in a short period of time haha

thorn robin
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yup looks good

cobalt tartan
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Thank you!

north sierra
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i dont understand of how this is a subset of the xz plane

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i know you explained it before @half ice but i still dont really get it

gray dust
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what's the y component of those vectors?

north sierra
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0

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so any scalar times v1 and v2 would = 0 in y

gray dust
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mhmm

north sierra
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so i get that part

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sooo

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like

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the plane would still be in R^3 tho right

steady fiber
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does the plane cover all of R^3

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if I give you any point in R^3 with a non-zero y component

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would it be in the plane

gray dust
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these are 3d vectors... they exist in 3d aka R^3

north sierra
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no it would not cover all of R^3

steady fiber
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so it's a subset of R^3

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if it was not a strict subset of R^3, then it would cover all of R^3

north sierra
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what does xz-plane refer to?

steady fiber
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the plane that goes through the x and z axes

gray dust
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all points (x,y,z) where y=0

north sierra
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oh

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so would you call (1,2) (5,7) an xz plane

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i mean xy

gray dust
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those aren't points in R^3

north sierra
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yeah ik

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i meant to put only 2

steady fiber
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I mean it's still the xy plane, but it's just the xy plane in R^2

gray dust
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rather they're in R^2 where you have (x,y) coords

steady fiber
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the xy plane in R^2, is all of R^2

north sierra
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always?

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oh nvm

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so xz plane in R^3 would be not be all of R^3 then right

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itd be a subset of R^3

gray dust
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yes

north sierra
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ok

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got it

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thx !

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to be more specific

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wouldn't you say xz plane is a proper subet of R^3?

gray dust
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you could

north sierra
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ok

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thx again

scarlet hamlet
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hey i'm not really getting the intuition behind this

north sierra
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behind what exactly?

scarlet hamlet
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"If L:V->W is a linear mapping, L is one to one iff Ker(L) = {0}"

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like yea the proof makes sense

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but its not really intuitive to me?

sonic osprey
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Well if Ker(L) isn't just {0} then it clearly wouldn't be one-to-one

scarlet hamlet
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its not 'clearly' to me yet so thats why im asking

sonic osprey
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Well the definition of one-to-one is that no two elements get sent to the same element

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0 is always sent to 0 in a linear map

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So if anything else is also sent to 0, then your map isn't one-to-one

scarlet hamlet
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ohh ok i see

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yep ok thanks

half ice
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The other direction is harder. It turns out that if any output has multiple inputs, then the zero output also has multiple inputs

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"iff" means this statement is really two statements

scarlet hamlet
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yeah

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i'm just asking cuz i've been using the lemma

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like so often

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but i dont think i actually get it

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like i get rank nullity for example

half ice
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It's very useful yeah. You can check one-to-one-ness just by checking the zero output

scarlet hamlet
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for me, rank nullity makes sense but this doesnt really yet if that makes sense

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its like

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i know how to use it but it still feels weird?

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idk if its relatable at all

half ice
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It definitely is relatable. In this case, I would suggest trying to prove it yourself! It's not a very hard proof. You need the fact that the function is linear, and it's over pretty quick

scarlet hamlet
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ok thanks ๐Ÿ™‚

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i tend to try and just hammer out examples but i think thats why i dont do well on the proof sections of tests lol

zealous kettle
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$E_{ik}A_{kj} = A_{rj} + cA_{sj} , i = r$

stoic pythonBOT
zealous kettle
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I get that E_{ik} = delta_{rk} + cdelta_{sk}

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which makes it

stoic pythonBOT
cloud cedar
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when you sum over something with the kronecker delta it acts to "replace" the index that gets summed over with the other: $\sum_j\delta_{ij}A_{jk} = A_{ik}$; it's like we took the $j$ index on $A$ and replaced it with an $i$ using the delta

stoic pythonBOT
cloud cedar
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in that step, youre summing over k, so the first Akj becomes Aij and the second turns into Asj (then since i=r you can replace the subscript i with an r)

toxic pendant
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I'd like to understand why when a determinant for a homogenous matrix is 0, there are an infinite amount of solutions

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Could someone explain it to me like I'm 5

steady fiber
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a 5 year old wouldn't understand matrices

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or determinants

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or homogenity

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or infinite solutions

toxic pendant
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Says the one with a pfp of someone who definitely would at 5

steady fiber
toxic pendant
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Wait what these emotes

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Mathematicians are weebs

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Qed

grave plank
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When I show the existence of the zero vector in a subspace, do I need to show that it is the result of the additive inverse property?

steady fiber
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when the determinant is 0, at least one row is not linearly independent from the other rows. If you row reduce such a matrix, you will have an all zero row at the bottom. If you find the solutions, since at least one variable is dependent on the other variables, there ceases to be a unique solution

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and you can vary the dependent variable(s) around to get infinite solutions

toxic pendant
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Oh

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That makes sense

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This makes too much sense

steady fiber
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I mean if it's a zero vector in the main vector space

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then it's still going to be the zero vector in the sub space

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you just have to show it exists in the subspace

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you already know it is the result of the additive inverse property in the main vector space, no need to re-prove it

grave plank
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so would i just need to prove the additive identity?

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well

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i shouldnt have to

steady fiber
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you just need to prove the zero vector exists in the subspace (and you have to prove the subspace is closed under addition and scalar multiplication)

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that's all

grave plank
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ah

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ok

toxic pendant
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btw ishigami best girl

steady fiber
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technically proving addition and scalar multiplication is closed already proves the existence of the zero vector in the subspace

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but I like to independently check for the zero vector first

grave plank
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ok thank you

zealous kettle
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@cloud cedar why does summing over the kronecker delta "replace" the index that gets summed over?

cloud cedar
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write out the terms of $\sum_j\delta_{ij}A_{jk}$

stoic pythonBOT
cloud cedar
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and youll see that youre only left with Aik

steady fiber
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since only the term where i and j are equal are kept, the kronecker delta function multiplies every other term with 0

cloud cedar
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yup

steady fiber
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it's the same concept as integrating a function multiplied by a shifted dirac delta function

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just discretized

paper egret
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what does inconsistennt mean

zealous kettle
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I see, thanks

steady fiber
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there is no solution

paper egret
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ah ty

steady fiber
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the constraints on the solutions

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don't match up

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so the constraints are "inconsistent" (with each other)

zealous kettle
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another question: in future scenarios when I have trouble understanding a particular theorem, how should I visualize it to help me understand it?

steady fiber
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depends from theorem to theorem

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might not even be possible to visualize it fully

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if it gets abstract enough

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that's when you have to just trust the math checks out

zealous kettle
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hmm

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what about for this theorem specifically? what could I do?

steady fiber
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which theorem

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oh I see it

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for this one you can just try writing out some simple 2x2 or 3x3 elementary row operation matrices

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and see what happens when they multiply random matrices

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get a feel for it and convince yourself it's true

zealous kettle
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hmm ok

steady fiber
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for most matrix proofs, just try doing some examples with 2x2 and 3x3 matrices (or like 2x3/3x2/2x1/1x2/3x1/1x3)

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to get a feel for it

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bigger sizes get a bit unreasonable to do by hand

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1x1 is just scalars

zealous kettle
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somewhat related question: in matrix multiplication AB, is the product a linear combination of B?

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for example

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take an elementary matrix E
1 1
0 1

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and another matrix A
2 3
4 5

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I guess what I'm really asking is

steady fiber
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let C be a matrix such that AB = C, for two matrices A and B
The rows of C are in the row space of B
The columns of C are in the column space of A

zealous kettle
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is there a way to think of E as the identity matrix with a 1 in the 1,2 position, and how it affects the product?

steady fiber
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does that answer your question

zealous kettle
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what is row space and column space?

steady fiber
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a linear algebra textbook can probably explain it better than me

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or someone else here

zealous kettle
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is it like all possible combinations of the rows of B?

steady fiber
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yes

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the rows of the product EA would be a combination of the rows of A, so that's why it's a row operation

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you can indeed look at E and predict what row operation it would be

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the elementary matrices are quite simple

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all 3 elementary matrices are simple changes to the identity:
if E looks like the identity with 2 rows swapped -> row swap operation for those two rows
if E looks like the identity with one non-1 element along diagonal -> multiplies that row by that non-1 number
if E looks like the identity with one non-0 element outside a diagonal, then you're adding a multiple of a row to another

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there's also column operations if you want to look into it

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where it would instead be AE, and the product would do column operations instead

zealous kettle
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so to clarify

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row space is like all linear combinations of rows as vectors

steady fiber
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yes

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it's the span of the rows

zealous kettle
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The rows of C are in the row space of B
The columns of C are in the column space of A

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this is still a little fuzzy to me

steady fiber
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you'll get to it sometime

zealous kettle
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alright

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also wont the span of the rows cover the entire ... um... space?

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like it could reach everywhere, right?

steady fiber
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if the rows are in R^n

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they can span up to R^n

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but not necessarily

zealous kettle
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oh because they could be all missing a x_k unknown where 1 <= k <= n

steady fiber
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there is a possibility there aren't enough linearly independent rows

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to span R^n

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or that there aren't even enough rows

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like in the matrix:
1 1 1
1 2 3

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the rows are in R^3

north sierra
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@paper egret p sure Hx = 0 will always be consistent becuase the augmented column will always be 0 in RREF

steady fiber
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but there's only 2 rows

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2 rows cannot possibly span all of R^3

zealous kettle
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why not?

steady fiber
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you haven't learned why?

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but you're learning matrices?

zealous kettle
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I probably have hang on

steady fiber
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that's a pretty big theorem to skip

zealous kettle
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I know for sure I didn't skip anything

steady fiber
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you need n linearly independent vectors to span a vector space with dimension n

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that's a theorem

zealous kettle
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the first mention of "linearly independent" is ~15 pages down

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but that makes sense though, to some degree

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since if you have
1 2
2 4
or any two rows that are colinear

north sierra
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yeah

zealous kettle
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ah the "missing a row part" also makes sense now

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its like you can't cover all of 2d space with only <1, 2>

steady fiber
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yes

north sierra
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yeah

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is origin the same as 0 vector?

zealous kettle
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finally

#

are you asking me?

north sierra
#

anyone who knows

steady fiber
#

I mean depends on how you want to define origin

#

if you define origin as the point that's (0,0,0,...0) (all coordinates 0)

#

then no

north sierra
#

like what if you say span(v1,v2) is a line through the origin and v1

#

would that mean 0 vector and v1

steady fiber
#

also by zero vector do you mean "vector with 0 magnitude" or the vector with the zero vector property

north sierra
#

um im not sure lol

steady fiber
#

I'll go with the latter

north sierra
#

lol

#

yeah probably

steady fiber
#

the span automatically contain the 0 vector

#

it has to

north sierra
#

oh ok

steady fiber
#

since it says it's through the origin, it contains the origin too

#

doesn't mean the origin and zero vector would be the same

north sierra
#

oh

#

so for my answer

#

i should just wrtie oigin

#

origin

#

origin + v1 or whatever

#

if it asked me to provide a geometric description of span(v1,v2) where they where v1 and v2 were independent

steady fiber
#

Define Vector space: $V=\left{\left(x_{1},x_{2}\right)| x_{1},x_{2}\in \mathbb{R} \right}$

Define vector addition: $\left( x_1,x_2 \right)+\left( y_1,y_2 \right) = (x_1+y_1+1, x_2+y_2+1)$

Define scalar multiplication: $c\left( x_1,x_2 \right) = \left( cx_1+c-1,cx_2+c-1 \right)$

#

the zero vector in this vector space is (-1,-1) if you want to verify it, so this is an example where the zero vector isn't the origin

stoic pythonBOT
steady fiber
#

A geometric description would the plane that contains both vectors v1 and v2

#

that's what span(v1, v2) is

zealous kettle
#

I got through half a page in hk today ๐Ÿ˜ซ

#

I'll never finish linalg at this rate

steady fiber
#

no one "finishes" lin alg

zealous kettle
#

bad word choice

#

I'll never finish this book

#

Which is like a intro to linalg

#

ashe if you don't mind me asking how did you learn lin alg?

serene axle
#

he breathed it probably

#

like most people in this server does.

#

then there's me and you doing it with sweat and blood

#

no pain; no gain

jagged forum
#

Does anyone know how to compute the basis of $W \cap V$ for subspaces W, V in R^5?

stoic pythonBOT
jagged forum
#

I forgot how to do any linear algebra computation, and my professor in my LAII course decided to give us a computation quesiton

dusky epoch
#

how are your subspaces given

jagged forum
steady fiber
#

I learned introductory Lin alg in a university from a professor

scarlet hamlet
#

all i did was write out c[L]b and b[L]c

#

and uh i have no idea where to go from there

#

theres this one too

#

i literally dont have a clue yikes

#

any insights would help โค

jagged saffron
#

wait i misread nvm

scarlet hamlet
#

haha itsok

#

ive literally just stared at the thing for 15 mins

half ice
#

In any general algebraic thingy, if Ax = A, then x is a "do nothing" element

#

Here, you have TST = T

#

ST is a "do nothing" which means S undoes T.

#

@scarlet hamlet

#

Mind you, this is probably not the only answer, but it's the easiest one to get

#

Oh wait, the kernel is non trivial so T isn't invertible. Huh.

distant gate
#

I forgot some linear algebra, does the null space and range of a linear transformation change with respect to different basis?

scarlet hamlet
#

@half ice i feel like im going in circles LOL

#

ive been writing stuff down

#

but its not leading anywhere

thorn robin
#

@scarlet hamlet do you know @cobalt tartan?
you two had the exact same question, in the exact same notation, one day apart lol

#

you can scroll up to see our discussion about the problem

cobalt tartan
#

Oh

thorn robin
#

(referring to your Q4)

cobalt tartan
#

Maybe same class

#

LOL

#

Yea that is uh same class as me

thorn robin
#

๐Ÿ˜‚

cobalt tartan
#

@scarlet hamlet q5 is uh you're almost definitely overthinking it

#

When u see it you'll go wtf did I spend 3 hours on this for

#

Q4 I'm still not 100% sure I understand lol

scarlet hamlet
#

LOL wait

#

do u go to UW

#

@cobalt tartan

cobalt tartan
#

Yea

#

LOL

#

MATH235?

scarlet hamlet
#

YEAH LOOOOOOOOOOOOL

cobalt tartan
#

What section

scarlet hamlet
#

i knew id find another loo person here

#

uh

#

i have no idea

#

i have satriano at 1030

cobalt tartan
#

Oh

#

Ok

#

Different section

#

Uhm

#

Anyways q5 uh

sonic osprey
#

I thought UW meant University of Washington rip

half ice
#

Waterloo?

cobalt tartan
#

Is easier than it seems

#

Yea

scarlet hamlet
#

yeah waterloo

#

waterpoo

#

same thing

half ice
#

Cool cool. I was Western over here

#

Nice to see Canadian rep

#

You guys are the better school

cobalt tartan
#

Haha

scarlet hamlet
#

my gpa is trash x.x

cobalt tartan
#

@scarlet hamlet Q5 uh what mapping takes T(x) and produces T(x)

scarlet hamlet
#

T(x) = x

#

??

#

wait what

#

idk i have 0 confidence in anything math

cobalt tartan
#

Uh let's go with an easier example

#

Say R2 -> R2

scarlet hamlet
#

uh

#

im literally so confused lol

cobalt tartan
#

Say that you have T:R^2-> R^2

#

Such that T((x, y)) = (y, x)

#

What is a linear mapping S:R2-> R^2

#

Such that S(T((x, y))) = (y, x)

#

@scarlet hamlet?

scarlet hamlet
#

S(y,x) = (y,x)?

cobalt tartan
#

Yes

#

So the mapping S((x, y)) is...?

scarlet hamlet
#

one to one? onto? isomorphic?

#

id say so lol

cobalt tartan
#

Yep

#

Does that give you a hint lol

scarlet hamlet
#

ya a bit

#

i think?

cobalt tartan
#

Q5 is big brain

#

Lol

scarlet hamlet
#

waterloo is too big brain for me

cobalt tartan
#

Same

scarlet hamlet
#

naw u seem like an intelligent being

#

i have the iq of a donkey

cobalt tartan
#

Uh I'm low IQ wannabe mathie ๐Ÿ˜‚

scarlet hamlet
#

i lowkey celebrated when i did q1 and q2 on my own

cobalt tartan
#

Oh

#

Same

#

A4 is easier

scarlet hamlet
#

did u already do it

#

whoa

#

i spent the whole weekend applying to jobs so im SoOo behind

cobalt tartan
#

Uh I looked at it, gonna start tonight

#

Have uh stat midterm to catch up + study for first

scarlet hamlet
#

oh same

#

stat230?

#

LOL

#

ok i feel like we should take this convo to dm

cobalt tartan
#

Ya

thorn robin
#

and they lived happily ever after

north sierra
#

a plane in R^2 would have to span all of R^2 right

#

wait i said that wrong

north sierra
#

[105]
[014]
[003]

#

this is an augmented matrix btw

dusky epoch
#

do you mean

#

[ 1, 0, 5 ]
[ 0, 1, 4 ]
[ 0, 0, 3 ]

north sierra
#

yeah

dusky epoch
#

don't write matrices like what you just did. matrix entries don't need to be single-digit integers

north sierra
#

ok sorry

#

so x1=5 x2=4 and is there an x3?

half ice
#

There's no solution to your system, as the bottom line implies 0 = 3
@north sierra

junior shard
#

I got the derivatives but im not sure how to show that theyre linearly independent

subtle walrus
#

by using the definition of linear independence

junior shard
#

How do i put them into matix

#

So i set cf+cf'+cf''= 0

subtle walrus
#

you use different coefficients for each, but yeah

junior shard
subtle walrus
#

yeah

#

now you have to show that c_0=c_1=c_2=0

junior shard
#

How do i set up the matrix for this?

junior shard
#

Is it correct to say c_2 must be 0 since its the only one that contains x^2

stoic pythonBOT
grave plank
#

Is my proof also enough to show that span(u,v,w) = span(u,v)?

steady fiber
#

pog I saw university of waterloo in chat

scarlet hamlet
#

@steady fiber r u a fellow looser too

steady fiber
#

no

#

I'm at the much better university a few hundred kilometers away

#

but every single one of my high school friend is at waterloo

scarlet hamlet
#

lol uoft?

steady fiber
#

u of tears

scarlet hamlet
#

sorry but we won the meme war

steady fiber
#

you did

#

we were completely destroyed in the meme war

#

no one denies it

scarlet hamlet
#

๐Ÿ’ช

grave plank
#

<@&286206848099549185>

grave plank
#

yah

#

7:52

#

idk what youre on

tranquil junco
#

repost ur question

#

or send screencap or smth

tranquil junco
#

like 95% of the time its people ponging helpers randomly and the other 5% its reposti

grave plank
#

can my proof generalize for span(u,v,w) = span(u,v)

sonic osprey
#

Do you think you can

grave plank
#

oh wait

#

i proved span(u,v) is a subset of span(u,v,w)

#

so by the definition of the subset

half ice
#

No, you proved what you said you did

grave plank
#

i mean earlier

#

in another part of the problem

#

my bad

#

but why cant i say span(u,v,w) = span(u,v) for my proof?

half ice
#

You showed that any element in span(u,v,w) is also an element in span(u,v). This proves that span(u,v,w) is a subset of span(u,v)

#

With that recent picture

grave plank
#

oh yeah, because if i think of it in terms of the logical form of the subset

#

an element of span(u,v,w) -> span(u,v)

#

i mean also just intuitively

half ice
#

It's a very easy proof to show that span(u,v) is a subset of span(u,v,w)

grave plank
#

yeah

half ice
#

So you should be able to show they're equal sets

grave plank
#

yeah

#

ty

cedar solar
#

What is a good interpretation of pseudoinverse?

#

Like if i have

#

$$X X^\dagger y$$

stoic pythonBOT
cedar solar
#

Assuming X is not invertible because the case when it evaluates to I is obvious

#

So $X X^\dagger$ is a projection but projection onto what

stoic pythonBOT
native lodge
#

thinking it's row space

#

but looks like I'm wrong lol

cedar solar
#

Oh

#

Thanks

#

I just realized it is explained in wiki but i mustve scrolled past it earlier

junior shard
#

is this correct?

#

im not sure if i can multiply c_1,c_2,c_3 by the different derivatives

pallid swallow
#

you can because it's true for all x

hardy blaze
#

yall this is a dumb question

#

if im asked to find 3(AB)

#

i find AB then scale it by 3 right ...

dusky epoch
#

you could do that, sure

short lava
#

Iโ€™m not asking for homework help but I came across this problem that I need help with

#

โ€œProve L(x)=(uโ€ขv)v is a linear transformationโ€

#

Any insight?

dusky epoch
#

are you sure you didn't mistype anything

#

as written it either doesn't make any sense or is underspecified

#

post the whole question exactly as it is stated

short lava
#

@dusky epoch hey sorry I donโ€™t have access to the question anymore

#

R^3โ€“>R^3 mapping

scenic acorn
#

Are you sure it's not something like "Show that L(x)=(x \cdot v)v is a linear transformation for any fixed v in R^3."?

lunar sable
#

Can someone guide me through to find the special solution to

#

1

#

Sorry about the pic

pallid swallow
#

you mean, a particular solution?

#

Just gaussian elimination it

#

WAIT

#

erm

#

It has no solution lol

#

because you can't multiply a 3x4 matrix with a 3x1 matrix

charred stirrup
#

Why cant vector n be [1, 1] and vector x be [2x, y]?

steady fiber
#

does it say anywhere that it can't be [1, 1] and [2x, y]

#

but it's better to split the coefficients and variables

#

and I believe it's necessary for normal form

#

it gives some useful properties (as outlined in the description you linked)

charred stirrup
#

oh so it convention and good practice

#

@steady fiber thank you

urban bough
#

What specifically is meant by this?

#

Are ui and vit supposed to be full matrixes in of themselves?

dusky epoch
#

they're vectors

urban bough
#

Never mind, I got it

#

I thought multiplying them was supposed to produce a scalar

undone garnet
#

$(I+AB)$ is invertible, prove that $(I+BA)$ is invertible too

stoic pythonBOT
undone garnet
#

hm...any idea

#

my proof is

#

if lambda is an eigenvalue of AB then it is also an eigenvalue of BA

#

so det(I+AB) = (1+lambda_1)(1+lambda_2)...(1+lambda_n) = det(I+BA)

#

I hope to see another idea for this problem :p

quartz compass
#

my gut instinct when I see something of this form is to use a geometric series if possible

#

$(I-X)^{-1} = I+X+X^2+X^3+\cdots$

stoic pythonBOT
quartz compass
#

just make sure things converge

#

well, idk if that's the best approach here, I think making use of this is a good idea:

#

$B(I+AB) = B+BAB = (I+BA)B$

stoic pythonBOT
quartz compass
#

there should be the same kind of relation for A as well, just some general ideas to think about that might help

pallid swallow
#

A and B are square matrices?

#

or not necessarily?

undone garnet
#

hm..don't remember exactly

#

maybe square

steady fiber
#

BA and AB have the same eigenvalues except for a bunch of zeros (in this case, they're square matrices of equal dimensions, so they have the exact same eigenvalues with the same algebraic multiplicities). Since (I+AB) is invertible, -1 isn't an eigenvalue of AB, so it's not an eigenvalue of BA either. If -1 isn't an eigenvalue of BA, (I+BA) must be maximal rank, and therefore must be invertible

undone garnet
#

well

#

I mean

#

is there another proof for this problem

#

without using eigenvalue

steady fiber
#

Probably

#

Is there a restriction on using eigenvalues

#

This is probably the simplest way to prove it

undone garnet
#

yeah

#

but this problem was on a midterm exam

#

eigenvalue hadn't have introduced

#

so I'm looking for another method

steady fiber
#

Oh there is another way

#

Find an explicit expression for the inverse of I+AB in terms of I, A, B and BA

#

It will automatically prove the existence of the inverse of I+BA

lone cove
#

assume the inverse of (I + BA) is (I + C)
for some C

#

then find what C can be

undone garnet
#

hm...

#

$(I+AB)(I+C) = I \Leftrightarrow AB+C+ABC=0$

stoic pythonBOT
lone cove
#

you mixed up the order of A and B

undone garnet
#

huh?

lone cove
#

we want to find the inverse of I + BA not I + AB

#

we already have the inverse of I + AB

undone garnet
#

already have?

#

where?

lone cove
#

from the question

#

we know it exists

undone garnet
#

ah ah we just know it exists

#

so

#

$(I+BA)(I+C) = I \Leftrightarrow BA+C+BAC=0$

stoic pythonBOT
lone cove
#

$(I + BA) C = -BA$

stoic pythonBOT
undone garnet
#

hm...

#

$C=-(I+BA)^{-1}BA$

stoic pythonBOT
undone garnet
#

$C = -(I+C)BA = -BA - CBA$

stoic pythonBOT
lone cove
undone garnet
#

@@

#

let $C = (I+AB)^{-1}$\
$(I+BA)BCA = BCA + BABCA = B(C+ABC)A = B((I+AB)C)A=BIA=BA$\
$(I+BA)(BCA-I)=(I+BA)BCA - (I+BA) = BA - I - BA = -I$\

stoic pythonBOT
undone garnet
#

done

scarlet hamlet
#

hey quick nub question here

#

to compute the norm of a vector v in an inner product space

#

does that work for all of 2x2 matrices in R?

#

ok ignore i asked that

#

i wrote out a general one and figured it out myself :p

scarlet ermine
#

what does it mean when it says 'set of prices when the price for output is 100 units'?

#

i've gotten to this stage but when i row reduced i got the 1 1 1 matrix which isn't useful

#

so i think i made a mistake somewhere

prisma prawn
#

guys why a linear transformation is injective if and only if the kernel is 0 ??

#

I need some help to understand it conceptually, geometrically

#

this is how i think

dusky epoch
#

do you understand injective => zero kernel?

rancid sonnet
#

derivatives can be represented as matrix operators right?

half ice
#

Kind of. They'd have to be infinite if your vector space is all polynomials

#

And we don't like to call them matrices anymore if they're infinite in size

#

But if you're limiting the degree, which is still a vector space, then yes definitely

dusky tartan
#

the main thing is understanding what linearity means and then it's clear

steady fiber
#

Calculus on Manifolds, by Michael Spivak (Chapter 2) might give you more information on what you want

#

about derivatives being linear operators (and being represented by matrices)

#

there's a lot more to it, so check out the book if you'd like (and don't skip Chapter 1)

rancid sonnet
#

ok I will

#

But if I represent polynomials with column matrices, then can I represent complex polynomials with a matrix too, by adding a second column for the imaginary components?

dusky tartan
#

you don't need to add an extra column

rancid sonnet
#

you mean just make the elements complex?

dusky tartan
#

yeah, complex numbers are still a field so they're not really any different in terms of polynomials

rancid sonnet
#

I want to solve some eigenvalue problems by trying to represent the hamiltonian operator of quantum mechanics as a matrix by writing some python code, so since I can write derivatives and polynomials as matrices, I'm gonna give it a try

steady fiber
#

I mean complex numbers are different, and you can't assume complex valued polynomials are differential everywhere (or even, anywhere)

dusky tartan
#

yeah but in terms of just defining a polynomial by coefficients it makes more sense to just keep it as one column vector

rancid sonnet
#

wait how do I represent polynomial multipllication in matrices?

#

I got my second derivative operator in the hamiltonian

#

but if I want to express the potential as an operator

#

I should express it as an nxn matrix instead of a nx1 polynomial matrix right?

#

Should I just

#

enter coefficients of x^0 to x^(n-1) in the first row and

#

cycle them

#

in the next rows?

quaint heart
#

"yeah, complex numbers are still a field so they're not really any different in terms of polynomials"

#

laughs in Algebraically closed

steady fiber
#

laughs in ordered field

hardy blaze
#

is the only way to get an identity matrix

#

by multiply a matrix & the inverse of that matrix

gray dust
#

you can also have this because I is its own inverse

#

$II = I$

stoic pythonBOT
hardy blaze
#

what if AB = Identity

#

wuld that mean B is the inverse of A

#

or A is the inv of B

#

like would it mean both of those statements*

stoic pythonBOT
hardy blaze
#

so if AB = I, then A=IB^-1 correct?

#

couldnt you make it A=B^-1 since I is like 1

#

wait

#

AB = I, so B is the inverse of A

wintry steppe
#

that's assuming both B is a square matrix

hardy blaze
#

yes

#

A,B,C are all nxn

#

so is it possible for AC to = 0 without C = 0? ๐Ÿค”

#

i dnt think so bc if A is invertible, then AC=0 -> AA^-1C=0 -> C = 0

#

but maybe bc u dont have to put A^-1

#

but then if u solve for C u would just get 0

wintry steppe
#

try A = [[1, 0], [0, 0]] and C = [[0, 0], [0, 1]]

hardy blaze
#

see

#

how yall come up w matrices like that that fast ๐Ÿ˜ญ ๐Ÿ˜ญ

#

so it is possible for AC to = 0 if C = that matrix u put

wintry steppe
#

for AC = 0, the image of C has to be in the null space of A

hardy blaze
#

well

#

i havent learned that ๐Ÿ˜ณ

wintry steppe
#

obviously, if C = 0, then the image of C is just the 0 vector and that condition is trivially satisfied

wintry steppe
#

I find that most of the time when people say that they haven't learned it, they really have, but just didn't understand it.

formal moss
#

question

#

if y = mx+b and m (slope) is undefined does that mean it's equal to 0?

#

or is a 0 slope undefined??

#

I'm given two points with an undefined slope so how do i figure the slope intercept form

#

when y-y1 = m(x-x1)

gray dust
#

0 slope is not undefined slope

formal moss
#

so how can i solve the point slope formula if i have a undefined slope

#

slope intercept*

dense sonnet
#

@hardy blaze if AB=I then that means B is the inverse of A if and only if A is the inverse of B. Also yes you can have two matricies not equal to the zero matrix that multiply to be zero. You can show this for a 2X2 case easily as someone else has shown you. Just multpily any arbitrary matrices 2X2 and then find what conditions will satisfy it to be the zero matrix. Linear is abstract but you'll get it eventually

#

@formal moss 0 slope is not the same as undefined slope. Think of it as rise over run. 0 slope can be written as (0/n) for any number n so we rise 0 and move right any amount. undefined slope is kinda like (n/0) so we rise any amount and move right zero. however this is kinda over simplifying it since you cannot divide by zero that is why it is undefined

formal moss
#

so the points are (2/3 , 1/5) and m is undefined and to find the answer in slope int form the answer is 2/3 and idk why

dense sonnet
#

if you have an undefined slope which coordinate will stay the same on your line?

#

@formal moss

formal moss
#

b?

#

oh

#

the x coordinate will

#

hmm i dont think thats right either

#

its the y

#

coordinate

#

that stays the same

dense sonnet
#

yes! so usually we have the equation y=mx+b but what you just said was our x will always be 2/3. so instead of y= youll have an equation x=

#

do you know what the equation x= will be?

formal moss
#

umm

dense sonnet
#

and you were right first with the x stays the same for an undefined slope

formal moss
#

x = 2/3

#

?

dense sonnet
#

perfect!

formal moss
#

OOH

#

i see

#

2/3rds is our constant and with an undefined slope(rise over run) it's just x = 2/3?

dense sonnet
#

you got it

formal moss
#

oddly enough that sounds like the same as if it was 0 slope though

dense sonnet
#

draw the line x=1 and y=1. what do you notice? they are similar but have a big difference

scarlet hamlet
#

o

formal moss
#

one is horizontal and the other vertical?

#

waiit

dense sonnet
#

yes. x=1 is vertical and y=1 is horizontal

formal moss
#

oh

#

ok

#

so it's an undefined function where the constant is 2/3rds

#

if a slope is undefined?

#

its not even a function actually

#

since x=2/3 fails the VLT

dense sonnet
#

yes. x=2/3 is not a function

formal moss
#

i see

#

thank you!

dense sonnet
#

no problem

sand oak
#

Can anyone help me with a problem

#

Let V = the x1x3 plane (also called xz plane) in R3, and v1 = (1,0,2), v2 = (0,0,1). Is V contained in Space {v1,v2}?

half ice
#

@sand oak
You mean Span{v1, v2}? Yes, it is. In fact, they're the same space

toxic pendant
#

What are complex numbers used for? Searching online gets me stuff like "used for electricity" but no examples.

gray dust
#

lots of things. circuit analysis is certainly one application

toxic pendant
#

Can you give an example of how complex numbers are used to solve problems

gray dust
#

quantum mechanics too but that's for the physics discord server

toxic pendant
#

wait I'm dumb, complex variables is literally right under this channel

#

also physics discord? gib

gray dust
half ice
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Circuit analysis isn't a small one lol.

You can't get into any real integral transformations without including complex numbers

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Differential equations will include complex at some point, and differential equations are a lot of engineering

gray dust
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did i say it was a small one?

half ice
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No, you didn't

toxic pendant
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I'm still ignorant of how to apply them so I can't really "imagine" a scenario using them. Can you give a problem which would require them

half ice
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Know what a derivative is?

toxic pendant
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I think so

gray dust
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you have a circuit which consists of a resistor, inductor, and capacitor strung together in series with an alternating voltage source (it drives AC current). you can use complex numbers to model the current through the circuit over time (look up phasors too)

half ice
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A differential equation is an equation that relates an equation to it's derivatives. Lots of natural phenomena follow differential equations. Getting information out of them isn't always easy, but integral transforms are a common way to do it.

The Fourier transform needs complex numbers, even if the system you're looking at is real

toxic pendant
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Huh, interesting

steady fiber
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I mean you can do the "easy" fourier transform with R->R^2

gray dust
steady fiber
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which is how it's often first taught

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sadly

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where you do cosine and sine seperately

half ice
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What Roketto and I are describing are related, a transform allows one to find phasors

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I think anyway? I know you can use the Laplace to get circuit stuff

toxic pendant
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Well, this was helpful, I have a lot of wikipedia to read though now

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thanks

half ice
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Np, feel free to ask if you have any questions about it

dense sonnet
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@toxic pendant so one quick thing you can notice for complex numbers is the formula for the roots of a cubic. now for specific cubics youll naturally run into imaginary numbers using the formula. but after computing it youll get a real solutions (all the imaginary parts cancel each other) and you end up with a real solution. however you go through a "world" of a number system that real numbers cant explain in order to get your solution. so imaginary numbers can arise to get real solutions. in the lift of a plane to model some stuff imaginary numbers will naturally arise having a real meaning in how the system behaves

toxic pendant
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Thank you for the explanation

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you may or may not have saved me from the wikipedia rabbit hole

quartz compass
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I can show you some stuff if you have some time

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I find it nice to take a geometric perspective and see the complex numbers as extending the number line into a 2D number plane

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gives a very clear interpretation of exponents and multiplication, just ping me if you're around

toxic pendant
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will do

upbeat niche
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Hey yall I got a quick question

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I'm sure this is actually super simple but idk where to start

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Or what to get from this

dusky epoch
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,rotate -90

stoic pythonBOT
dusky epoch
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do you have access to determinants

upbeat niche
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Nope that's all I was given, or were you asking if I can find them from this system of eq?

quartz compass
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I guess you have to get your hands dirty and do gaussian elimination then

dusky epoch
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@upbeat niche i'm not asking whether or not you were given anything else, i'm asking whether your class has ever talked about determinants in any capacity

upbeat niche
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Right now I'm just trying to solve the augmented matix

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Into rref

cobalt tartan
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When they say that "If and only if v = 0", say for example that we have some p in P^2

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p(x) = ax^2 + bx + c

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Right?

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When they say that the vector has to be the 0 vector do they mean that we have to have p(x) = 0x^2 + 0x + 0?

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Or does p(x) = 0, i.e, the values of its roots...?

quartz compass
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the first statement

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the actual "value" of x doesn't matter when talking about the vector space P^2

cobalt tartan
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hrm

quartz compass
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think of them as just letter placeholders, they're basis vectors taking on no value

cobalt tartan
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Oke

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As I can like... find p, q, and values of a, b, c such taht it's not positive definite...?

quartz compass
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here a,b,c are like separate x values, they're not the coefficients on the polynomials

cobalt tartan
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Hrm

quartz compass
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it's like they've taken the original version but they've repeated it three times in a row

cobalt tartan
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Ok so like is the question basically saying

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Let p(x) = p_1x^2 + p_2x + p_3, q(x) = q_1x^2 + q_2x + q_3, and then go and show that for any a, b, c, the inner product defined in the question will equal 0 if and only if p_1 = p_2 = p_3 = 0 or q_1 = q_2 = q_3 = 0?

quartz compass
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very close, it's not wrong exactly, but

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the last part I think should be said as when p=q and then p_1 = p_2 = p_3 = 0

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since they're not separate

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I think I might be nitpicking in a confusing way

cobalt tartan
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Oh right

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Because positive definite requires them to be the same right?

quartz compass
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yeah

cobalt tartan
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Err because positive definite is'nt on different p and q, it's on the same p and q

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Like

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Do I just expand it out...?

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Like I can do that but it's a lot of work lol

quartz compass
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well, I'd just rewrite it with p=q and then

cobalt tartan
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err

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I'd jsut write it with <p, p>

quartz compass
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all the terms are really just (p(a))^2 + (p(b))^2+ (p(c))^2

cobalt tartan
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Ya

quartz compass
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yes exactly

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is it clear how this is gonna work out, you don't have to expand anything

cobalt tartan
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Oh

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Hrm

quartz compass
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p(a) is just a number

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it could be positive or negative

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p(a)^2 however is always positive

cobalt tartan
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Yea, <p, p> = 0 iff p(a)^2 = p(b)^2 = p(c)^2

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But because it's in p2

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You can only have 2 roots

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So it's impossible for all 3 to be 0

quartz compass
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not necessarily you also have to have p(a)^2 = p(b)^2 = p(c)^2=0

cobalt tartan
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Err yea

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Only in the case where it's all 0

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Oh wait

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Hrm

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Well, showing positive/negative is easy enough, p(a), p(b), p(c) are all real numbers, when you square them , they will always be positive, so their sum will also be positive

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Right?

quartz compass
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yeah good

cobalt tartan
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Hrmmm yea my roots idea would have like 3 cases which is too much work

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Would need to show the case where 3 distinct, 2 distinct, and no distinct

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And my idea only holds for 3 distinct/no distinct

quartz compass
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it's good cause you have been given all 3 are distinct

cobalt tartan
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Oh wait

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Hrm

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Then does my idea work then if I just show the 2 cases?

quartz compass
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I don't think I follow your reasoning, I'm imagining 3 quadratics each having at most 2 roots

cobalt tartan
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Well because it's <p, p> we only have one quadratic

quartz compass
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err, 1 quadratic

cobalt tartan
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One quadratic would have at most 2 roots

quartz compass
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3 results of plugging in 3 roots to 1 quadratic which can have at most 2 roots

cobalt tartan
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Ah wait no

quartz compass
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so one of them can't be 0