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00:16
What is the statement of Schur's lemma for Lie algebras? Every source I come across just gives a statement of Schur's lemma for representations of Lie groups and says an analogous statement holds for Lie algebras; but I'm not sure how to translate things from Lie groups to Lie algebras.
00:36
Hello
I was mixing up sets with subsets of sets. In particular, I had mistakenly thought that the real numbers contained the empty set.

I don't understand why probability spaces use the empty set though. For example, what happens when I have a random variable? If probability spaces have an empty set, what does it map to?
Yikes @Stan
Probability spaces are measure spaces, and the empty set is a measurable set with measure 0.
@user193319 if $A$ is an abelian category and $V_1,V_2 \in A$ are simple objects in $A$, then every morphisms $f:V_1 \to V_2$ is either $0$ or an isomorphism. Consequently $\mathrm{End}(V_1)$ is a division ring
hi @Mathein
@TedShifrin yikes sums up my relationship with math as of late but that's ok
LOL ... you don't appreciate my critiques.
00:41
oh no i do
I was trying to get you thinking more conceptually about linear algebra, as opposed to relying on brute-force computation.
it was more that i was frustrated with how slowly i've proceeded at linear algebra
@MatheinBoulomenos Any way to state it without category theory? I'm just a mere mortal thinking about Lie algebras.
that's why i've been putting in more time
00:42
Linear algebra, done right, is interesting and challenging.
cuz it's showing up in one class and i can tell i'd get a lot more out of it if i went through ur book like im doing now
@user193319 no offense, but how hard did you search? it's even on the wikipedia page for Schur's lemma
But mostly it's done wrong (in the US, anyway).
In mathematics, Schur's lemma is an elementary but extremely useful statement in representation theory of groups and algebras. In the group case it says that if M and N are two finite-dimensional irreducible representations of a group G and φ is a linear transformation from M to N that commutes with the action of the group, then either φ is invertible, or φ = 0. An important special case occurs when M = N and φ is a self-map. The lemma is named after Issai Schur who used it to prove Schur orthogonality relations and develop the basics of the representation theory of finite groups. Schur's lemma...
@TedShifrin that's why i'm doing this in addition to my studies because i want to get the most out of my classes next quarter
and just doing linear algebra during break won't be enough
i need a solid few months doing it everyday
00:43
I think that's not a bad idea.
Did you get the point of my last email?
Hiii
Oh, look, it's Meow.
@MatheinBoulomenos Sorry...I was looking through the books I own.
I miss this place
@TedShifrin No, but I think I just have to struggle with it. I'm gonna reply sometime in the next 24 hours. I'm prepping for a midterm and wanted to clarify my probability notes, but i think i'll wait til break to go over the measure theory sections. Ok I'm gonna run and get back to work. I'll message you later. au revoir mon ami
00:48
A bientôt, @Stan.
aww, @Meow. No one banned you.
Lol but I have no time for recreational math anymore
Recreational? Hrumph.
What are you so busy doing now?
School work
Junior year is stressful
Learning anything interesting/challenging?
Yeah AP chem is offering me a nice challenge
I think chem is really hard
00:50
Well, that's good. Why?
Everything is just so complicated. Like there's so much more to something so simple like bonding than just "two atoms connect"
And no matter how in depth you go, for a high school course there will always be a point where you just have to accept that that is just how things are instead of looking further into why that's the ase
it's*
So I think it frustrates me in that aspect but it offers a unique challenge
@MatheinBoulomenos How do I use Schur's lemma to conclude that for simple Lie algebras over $\Bbb{C}$ the space of invariant bilinear forms is at most $1$-dimensional? Is this space a subspace of $hom_{\frak{g}}(\frak{g} \times \frak{g}, \Bbb{C})$ or $hom_{\frak{g}}(\frak{g} \otimes \frak{g},\Bbb{C})$?
Well, I was only truly satisfied about a lot of those things when I took physical chemistry in college.
In high school, a lot of the things are just axiomatic ...
@user193319 it's isomorphic to the latter
I can't wait for that. I hate feeling like I'm so incompetent because I don't understand why something is the case
00:54
$hom_{\frak{g}}(\frak{g} \otimes \frak{g},\Bbb{C})=hom_{\frak{g}}(\frak{g},\frak{g}^*) \cong hom_{\frak{g}}(\frak{g},\frak{g})$
Meow, stop taking everything personally.
A good example of “where does that come from” in chem is drawings of molecular orbitals (s,p,d etc)
It’s easy enough to splash those images in an intro chem book
Well, no one says that the Bohr model is "right." :P
Aren't those just solutions of Schrodinger's equation things?
But to actual derive them in QM you need to solve the Schroedinger equation in spherical coordinates
00:56
@user193319 the first equality is the Hom-tensor adjunction, the second uses the fact that $\mathfrak{g} \cong \mathfrak{g}^*$ since $\mathfrak{g}$ admits a non-degenerate invariant bilinear form (e.g. the Killing form)
@MeowMix right
Spherical harmonics and all that
@Semiclassic: But by symmetry doesn't it reduce to just 1-D?
Everything in physics and chem seems like just a huge mess of a bunch of super tiny things interacting with each other at every point in time and properties just arise from that
@TedShifrin no
And I think it's cool it just makes things super complicated
00:57
Hmm.
But yeah they put me in Calc III this year so math is a bit of a challenge I guess too
In a college?
No they teach Calc III at my high school
I guess I meant $\rho$ as a function of $\phi$, @Semiclassic.
Oh, those courses are almost always disasters. Is the teacher actually competent?
00:58
It's not very rigorous and it kind of frustrates me
She is somewhat competent
if $\mathfrak{g}$ is simple, then $\mathfrak{g}$ is an irreducible representation (well actually $\mathfrak{g}$ is abuse of notation for the adjoint representation here
Even most college Calc III courses are bad.
Yeah :(
@MatheinBoulomenos So, if $\frak{g}$ is simple, then we conclude that $hom_{\frak{g}}(\frak{g},\frak{g})$ is $1$-dimensional?
No, it can still be a good course without being totally rigorous.
00:59
@user193319 yes
But there are difficult concepts that need to be explained, even if we don't talk carefully about what continuity and differentiability mean. (You can always watch my lectures for those, Meow, in your spare time. Ha.)
I know but when things aren't rigorous I get the sense what I'm doing is shaky
So I need to how that $hom_{\frak{g}}(\frak{g},\frak{g})$ is an irreducible representation
@Meow: I can send you my lecture notes from the multivariable calc class at MIT I taught back in 1981. If you are interested.
01:00
I still remember everything I learned from Spivak's so I feel like I have a solid understanding of Calc I
How do I apply Schur's lemma then? Schur's lemma is about irreducible representations
$\mathrm{hom}_{\mathfrak{g}}(\mathfrak{g},\mathfrak{g})$ is not a representation
How in depth are the lecture notes
You never got very far in Spivak, @Meow.
there’s a line I like: “Teaching is the art of telling smaller and smaller lies.”
01:01
I got somewhat far, like chapter 16
Oh, you never talked to me about anything after Chapter 4.
@user193319 you apply it to $\mathfrak{g}$ itself (as I said that's abuse of notation for the adjoint representation, but everyone seems to do that)
@Semiclassical Haha that's a good one
@TedShifrin Yeah I read up to the trig functions chapter
The balance, of course, is that if you tell too big a lie then you lose credibility
Reading without doing exercises ?
01:02
No I was doing exercises
@MatheinBoulomenos hmm...how do you even define $hom_{\frak{g}}(\frak{g},\frak{g})$...I just realized that I'm entirely certain how to define it.
@Meow: I explained concepts carefully and did examples, but I only did proofs when they gave insight and understanding. It was not a proof-based course. For that, you need my videos.
So even if it’s not “truly” rigorous it still needs to stand up to scrutiny
And I think it's important to make it clear when you're telling lies @Semiclassical
01:04
Not always.
@user193319 if $V$ and $W$ are representations of $\mathfrak{g}$, then a $K$-linear map $f:V \to W$ is said to be $\mathfrak{g}$-equivariant if $f(Av)=Af(v)$ for all $A \in \mathfrak{g}$, $v \in V$
If you tell them you’re lying, you’re not lying :P
Not every course in calculus should be aimed at Spivak-capable students. That would be an unmitigated disaster.
And $hom_{\frak{g}}(V,W)$ is the collection of all such $f$?
01:05
Yes
That said, you should always be prepared to admit the lie
I suppose
so teaching is basically lie theory?
@MatheinBoulomenos So when we write $hom_{\frak{g}}(\frak{g},\frak{g})$, we must have some natural representation of $\frak{g}$ in mind, no?
I knew you were going to say that (or semi would), @Mathein.
01:06
@user193319 as I already said $\mathfrak{g}$ is used for the adjoint representation of $\mathfrak{g}$
Anyways I come here because I have the opportunity to take linear algebra and diff eq next year at a local college and I don't know if that's a good idea. I know if I don't do that I'm not gonna have any math classes and I won't have any motivation to learn on my own
As in, if someone questions it, it isn’t a good idea to dig in your heels and insist that they’re being silly
@MatheinBoulomenos That is, $ad : \frak{g} \to \frak{gl}(\frak{g})$ given by $(\text{ad } x)(y) = [x,y]$?
@Meow: It's OK to wait until you actually go to college.
01:08
Diff eq is probably OK, but I am sure I'd hate the linear algebra class.
But you can’t spend all of the lecture repeatedly saying “it’s actually more complicated than what I’m saying”
if you do linear algebra at a local college, it's probably over a local field
spanks Mathein
Depends on what level of linear algebra one is doing. There’s some parts of it which go very nicely with diff eqs
Yes, but no one teaches them combined ... well, it's a set of measure 0.
01:11
Aye. But if one is doing self-study then there’s at least some parts of linear algebra that goes well with DEs
I liked that we did the STFGMPID in in linear algebra
Hi @Akiva
It does depend a lot on what level of linear algebra one is talking about of course
> Complex analysis: suppose f(z) is a function which is interesting in some way. Then f is a constant function.
01:12
LOL
I guess I don't agree on the definition of "interesting."
I very much do -not- have in mind what Mathein would mean by a linear algebra course :P
No, @Semiclassic. He's very pure-math European.
> Graduate algebra classes in a nutshell
Definitions: take the largest class of objects where everything works the way you want them to.
Theorems: everything works the way you want them to.
First comment
>Definition: Take the largest class of objects that seem to act the way we want.
Example: They sometimes still don't act the way we want.
Definition: An object is called "normal" if it _really_ does act the way we want.
@MeowMix Hey, long time no see
01:13
@AkivaWeinberger true
@AkivaWeinberger easiest counterexample to that are functions with branch points
@LeakyNun Hey, short time yes see
I wanna know why that way of computing inverse matrices works
Apart from "when you calculate it it gives the identity matrix"
01:14
@MeowMix which?
Look at my book or videos, @Meow.
The one where you do like 4 steps
Here's a challenge. Which part of math is this theorem from "Regular implies normal"?
Like take the cofactors and transpose and whatever
01:14
That’s...not very descriptive
Oh
Oh, that's a terrible way to find inverses, @Meow, but it's not hard to prove.
Adjugate matrix
@MatheinBoulomenos Call a branch of math "perfectly normal" if regular implies normal
Wait what are the matrices that preserve normals
Adjoint?
Better way is with row operations, @Meow. But proofs of both are in both my books and my lectures.
normals?
01:15
Math is fun
I had to use that in one of my 3d graphics programs
Adjugate matrix is nice for theoretical purposes but not for computational
You mean preserve lengths?
Basically try multiplying them together and see what happens
No
So like
01:16
I had to use a sinusoidal model to weave around bad data recently. I’m hooked on learning math now
If you have 3 vectors that form a triangle with normal $n$, the image of those 3 vectors under the linear map form a triangle whose normal is the image of $n$
I am a sponge
Does that make sense
So the matrix will end up having to be a scalar multiple of an orthogonal matrix.
I don't know what the context is but I'm imagining a sine wave literally "weaving" around points in the x-axis
01:17
It needs to preserve angles.
Are you putting $ signs there or is that a symbol my phones isn’t picking up
we just like money
tinyurl.com/cfqcvpc @JacobMcMichael
See on the top right ^^^>>>
On the note of data analysis, there was an op-ed in the Minneapolis paper today
Let me find it
Oh it's just called a normal matrix
01:18
Minneapolis - don't they just call it an oped over there
Hmm, normal means $AA^* = A^*A$.
or an ope for short
Well here I'm specifically talking about 4D transforms where one coordinate is homogeneous
So that you can do translations and stuff
It’s not working on mobile akiva
If it's real, star means transpose, and then I think it's what I said.
01:19
I've got it working on iOS Google Chrome
Right.
There's a way to add bookmarks but it's annoying
what does it mean for one coordinate to be homogenous? I know homogenous coordinates for $\Bbb P^n(k)$, but a single coordinate?
No, he didn't mean that, @Mathein.
01:20
They're working projectively so that translations become linear.
Yeah I feel that about the money though. I’m heavily into stock forecasting and making new models. But I’m getting tired of it I really want to make sim games lol
“ Modern high school math should be about data science”
He meant to add an extra coordinate and homogenize. But he didn't say it right.
Yeah, a bunch of my math friends have been debating that seriously on FB, @Semiclassic.
Basically, high school math has become stat to a very large extent anyway.
I’d have to figure it out I’m not in the mood to troubleshoot my iPhone X right now
True semi
OK, I need to go cook dinner. Bubye, all.
01:22
here we do calc and linear algebra in high school, but not much stats
Stats is extremely useful
With a GARCH model you can make extra data that looks just like stock market data so if you take all the data yahoo finance offers you can basically use that to make an infinity size sample size
Then run different tests on it to try to make money
my main issue with that editorial is that calculus is part of what makes data science...well, science
If you don’t understand the tools you’re using to analyze your data, you’re liable to not recognize when those tools are failing
Yeah I agree
If you want to do serious data science, you need more math not less. a different subject focus, perhaps
Are you into data science I’m guessing
01:28
Not as such—I did theoretical physics
It’s almost the same thing just add in some python or R and you’re a data scientist lol
The following does seem to be true, though: most of data science seems to be optimization problems
And the idea that you could understand that without calculus is rather absurd
Yes I want to find out how many people are into in seriously I’m curious
Understand what
Understand how to solve optimization problems
Consider the proof of the following multivariable chain rule. What happens to the $E(h,k)$ term when dividing by $\sigma$ as highlighted in the red box?
01:34
Just slap a bunch of time series data into excel to where it looks like t(subscript 0) and then t(subscript 1)
I think they're probably just emphasising more on basic statistics (as they said - they want people to know how to use spreadsheets / understand difference between correlation and causation) -- presumably something about hypothesis testing etc.
Then you can forecast different methods. Any math you can think of
but also i do know people who wants to learn calculus after they became aware of it via ML - so it probably would help in motivating more people to learn calculus given the ML hype..
I recgongnize sigma and the v is rho I think
Yes loch that is true sadly
you can forecast any math you can think of with excel?
01:37
I only just became motivated to learn math when I found a use for it but I’m sold now
@MatheinBoulomenos a regular integral domain is normal
Yes with stock market data from yahoo you can get it from R studio crab repository “BatchGetSymbols”
Then just set it up in excel to study
But I’m struggling because the regular market indicators that are on the internet don’t work or barely work to the point of it’s not worth your time
@LeakyNun have you introduced Galois-Brauer descent in your Lie groups class?
@MatheinBoulomenos leider nicht
So I basically want to try custom stochastic calculus indicators and test for a better for to the positive returns
I’m sorry if I’m interrupting
@LeakyNun I'm TAing intro abstract algebra. Should I tell my students that a semidirect product is a 2-colimit?
I’m finding out that everyone here is highly into math
01:46
surprisingly, given that this is a math chat
Your sarcasm is squared
Anyone here watch Sentdex’s channel?
02:17
0
Q: Covariance between number of tosses to get heads and number of tosses to get tails

genescubaLet $X, Y$ be the random variables which respectively are the number of tosses to see your first head and number of tosses to see your first tail. What is the the covariance of $X$ and $Y$ $\mathrm{Cov}(X,Y)$

If anyone is familiar with covariance
It’s the exact same thing as correlation
just take the variance in the opposite category
It’s basically the real word or og word for correlation haha
I’m sure the awnser is a covariance of .5 assuming a 1 means it’s perfectly correlated
Perfectly Positively correlated I should say
speaking of dual categories, does the dual category of representable functors ever project into locally ringed spaces?
my question here is I know that cov(X,Y) $=E[XY] - E[X]E[Y]$
$E[X] = E[Y] = 2$ in a fair coin
But how can I think about $E[XY]$?
02:30
@genescuba should that be 1/2?
More to the point, what are the outcomes?
The chat isn’t rendering the signs I’m new to the mobile version and I tried safari and chrome
click show bookmarks
Getting it to work on mobile is a bit more annoying, yeah
oh nvm
You can save bookmarks in mobile safari, though
02:32
@Semiclassical why $\frac{1}{2}$
I have yet to get the dollar signs on mobile
what is $XY$
@genescuba well, why 2?
I’m gonna figure this out
so $E[X]$ is 2 because we have 1/2 chance of getting heads
02:33
Steve Jobs strikes back from the dead
and multiplying 1/2 * 2 gives us 1 which is like flipping twice to see 1 head
What are your outcomes, ie what value are you assigning to heads vs tails?
$$ \sum_0^1 f(n)? $$
can I do that?
Without values for your outcomes, it makes utterly no sense to talk about an expected value
Yoo
Team Trees is already more than halfway to their goal
02:35
YOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO
yo ho yo ho
Two people have donated a million trees
(Elon Musk and Tobi Lütke, CEO of Shopify)
we're going extinct by 2050
@Semiclassical so I guess when I am looking at $E[X]$ tails will be 0 and heads will be 1 right?
and the opposite when I look at $E[Y]$
Why opposite for tails?
02:37
I freakin put the MathJax code into the bookmark
It still won’t give me the latex
And you clicked on the bookmark while on this page?
Oh you’re a g
It's working?
Test: $\displaystyle\sum_{n=1}^\infty\frac1{n^2}$
02:40
I’m not sure how to execute the bookmark from this chat page
😅
@genescuba from what you’ve said so far, there’s no particular reason to assign 0/1 to tails/heads for X but opposite for Y
$$ |1+1+1|+|1+1-1|+|1-1+1|+|1-1-1|+|-1+1+1|+|-1+1-1|+|-1-1+1|+|-1-1-1|$$
I'm still calculating it
I did it I am the best
02:41
Broke: smoke signals
Woke: shine language
I can read
I’m woke now
It won’t change the magnitude of the correlation but it will change whether X and Y are positively or negatively correlated
Yay! $\phantom{So you can't see this then}$
02:42
he said right to semiclassical
I don’t know what’s going on semi sounds right
Oh and if you want to undo it you can refresh the page
Yeah no
But thanks for the heads up
you will have to renew the bookmark if you leave the page
02:43
well so for $Y$ we want to count tails rather than heads right so don't we switch
Fun fact: the sign for "siblings" in Japanese Sign Language is the middle finger
so for X I am saying 0:tails and 1: heads and for Y I am saying 0:heads 1:tails
@genescuba Are you -told- to do that?
If so, fine.
Gene what is this for
02:45
But right now you haven’t actually said what X and Y are supposed to represent
The funnest game of coin toss ever
> A musician was wandering in the jungle when he came upon a clearing that seemed to have acoustical merit. He prepared his violin and began to play.
The music was so beautiful that the wild animals started to gather, they lay down and they all listened. Even the predators were soothed by the music.
Suddenly out of the brush appeared a leopard, he pounced on the musician and tore him to pieces.
A lion asked the leopard “Why in the world did you do that?”
The leopard replied “Huh?”
Took me way too long to get that
What he was hard of hearing?
I don’t understand your math jokes
Def Leppard
😠
Oh yeah that plane went over my head
Well how long have you guys been here
02:49
sorry for the confusion @Semiclassical
Let 𝑋,𝑌 be the random variables which respectively are the number of tosses to see your first head and number of tosses to see your first tail. What is the the covariance of 𝑋 and 𝑌
I've known about this site for a few years
if that's what you mean
$\approx 1$ year
How much math have you learned
1 unit
1 unit of math haha?
02:51
Some people here helped me through a textbook
Dang that’s a lot. I saw some people posting about topology I think earlier I’m not sure if I can relate any time soon hahaha
Yo gene a coin toss is random so that means your awnser is uncorrelated or .5
I’m trying to get to stochastics and mabye complex analysis then I can branch into statistics like I need to
Then it’s back to the data bases and crunching numbers trying to get that alpha in finance
@genescuba ok. Note that the outcomes of X are 1,2,3,4,...
And same for Y.
Yup
so @Semiclassical Im having trouble thinking about $E[XY]$
what does $XY$ represent here?
Before that, let’s make sure you have EX and EY right
02:56
Sure
What are the probabilities for X=1,2,3,...?
Thats the end goal those 2 books right there
hmm so for $X$ = 1 its 1/2
and then for 2 its (1/2)^2, 3 its (1/2)^3 and so on
Electricity and robots baby
Right. So how do you compute EX?

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