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00:23
huh? closed implies $G_{\delta}$ in a manifold
in fact, you can choose a metric on $M$, then $x\mapsto d(x,C)$ is a continuous function vanishing exactly on $C$ and a sufficiently close smooth approximation to this function will be a smooth function only vanishing at $C$
the latter point is technical, but still easier than Whitney extension
can you elaborate on the smooth approximation bit? i'm afraid i don't know very much about this
01:02
for a given continuous function $f\colon M\rightarrow\mathbb{R}$ and a given "threshold function" $\varepsilon\colon M\rightarrow(0,\infty)$, you can always find a smooth function $g\colon M\rightarrow\mathbb{R}$ s.t. $|g(p)-f(p)|<\varepsilon(p)$ for all $p\in M$
this is essentially because you can do it locally by constant functions and then glue together using a partition of unity. making this precise is somewhat technical, though
 
2 hours later…
02:42
@TedShifrin I'm curious as to proving all these different what seems like variations of triangle inequality. Are these some of the bed-rock calculations that we will be coming across in Calculus, or is this a really good chance to become intimately familiar with manipulating inequalities? (I'm referring to problems related to problem 12 in Chapter one)
Rigorous calculus is about estimates and inequalities. :)
OK...look forward to it then!!!
03:40
So far, I let $\alpha_i,\beta_i$'s be generators of $H^1(M_h)$ and $\alpha'_i,\beta'_i$'s for $H^1(M_g)$. If I let $f^*(\alpha_i)= \sum_{j=1}^g a_{ij}\alpha'_j+\sum_{j=1}^g b_{ij}\beta_j'$ and $f^*(\beta_i) =\sum_{j=1}^g a'_{ij}\alpha'_j+\sum_{j=1}^g b'_{ij}\beta_j'$ then $f^*(\alpha_i)\smile f^*(\beta_i) = \sum_{j=1}^g a_{ij}b'_{ij}-a'_{ij}b_{ij} = 1$. Is there something I can do more? @TedShifrin
03:54
Just start small. You’re too impatient trying to do the general case. It looks like you ignored my other observation, too.
hey ted, i need you :p
what's the definition of "in-boundary" and "out-boundary" in differential geometry?
Oh, I only saw the tagged chat. ok for $g = 1,h=2$ case, I get $f^*(\alpha_1)\smile f^*(\beta_1) = (a_{11}b'_{11}-a'_{11}b_{11})\gamma = \gamma$ and $f^*(\alpha_2)\smile f^*(\beta_2) = (a_{21}b'_{21}-a'_{21}b_{21})\gamma = \gamma$ @TedShifrin
04:19
You’re still missing the crucial element. What more is true about the $\alpha$ and $\beta$ Curves?
No clue, @lucas. Context?
just to confirm my observation: when the option is to Sort By Votes (not Active or Oldest), ceteris paribus (e.g., both answers having received exactly 0 upvotes and 0 downviotes), an Accepted answer is now sorted below other same-scored Answers, correct?
@TedShifrin differential bounded manifold M with boundary, submanifold N with codimension 1 contained in some connected component of the boundary, both oriented. N is said to be in-boundary if a positive normal points inwards (??? what does this mean); out-boundary analogous
Still not clear to me. So $N$ is a union of components of the boundary of $M$? I assume they are talking about whether the orientation agrees or disagrees with the orientation on the boundary (component by component).
04:41
@TedShifrin $\alpha_i\smile\beta_j =0$ if $i\neq j$ and $\alpha_i\smile\alpha_j = \beta_i\smile\beta_j =0$?
Yup.
Now look at pullbacks in the example case.
04:53
@TedShifrin I got 4 more equation $a_{11}b_{21} = b_{11}a_{21}$, $a_{11}'b'_{21} = b'_{11}a'_{21}$, $a_{11}b'_{21} = b_{11}a_{21}'$ and $a'_{11}b_{21} = b'_{11}a_{21}$.
@TedShifrin nope, N is a subset of a connected component
the more general context: the author is trying to define what is a oriented cobordism
$N$ has the same dimension as the boundary. Surely we're working with closed submanifolds here.
@love_sodam So think what all these equations are saying about the columns of your coefficient matrix.
the definition of oriented cobordism:
04:58
So $N$ is not a subset of a component. It is an entire component or a union.
I know what cobordism is.
the definition of in-boundary and out-boundary:
Don't give me links that require security crap.
I'm not dealing with that.
It's EXACTLY what I said.
i'm not understanding the whole thing, ted
05:01
The boundary of $M$ has a natural boundary orientation. They're taking a COMPONENT of the boundary with an orientation and asking whether its orientation agrees or disagrees with the boundary orientation on (all of) $\partial M$.
@TedShifrin the first claim is true because you just restrict the orientation of $M$ right?
I think you should start with something like Guillemin and Pollack and learn about orientations on manifolds with boundary.
Hirsch is much steeper going.
@TedShifrin it's really the first, first time i'm reading something about university-level geometry, so these concepts are a bit messy for me
Right. This is too sophisticated a place to start.
I also disagree with their final statement. They also have a non-standard way of defining orientations, to add insult to injury.
either way, i think i won't understand these today, unfortunately. i'm reading because i'm supposed to know them to construct the 2Cob category blah blah and i have a report due today
05:05
They're putting random orientations on the components of the boundary. The boundary has a natural orientation. They're saying "in" if the orientation disagrees with the boundary orientation, "out" if it agrees with the boundary orientation. If you take all the boundary components with their boundary orientation, all the components are "out."
@TedShifrin It looks like determinant of two vectors $f^*(\alpha_i)$ and $f^*(\beta_j)$
I think you should adopt a more reasonable approach to actually learning stuff, not cramming at the last minute.
Right, @love. Think about linear independence and dependence accordingly.
All those $0$ cup products tell you a lot of dependence.
@TedShifrin i slept < 20h in the last 4 days. life is teaching me
(teaching me not to be stupid ever again)
You keep getting yourself in this situation. Drop some of the courses.
Go to bed.
i can't :(
i need to finish this report. i mean, funding issues etc
05:11
Well, read what I wrote and move on. I cannot rescue you at the twelfth hour.
yeah, i know. but sincerely i keep getting in this situation because i procrastinate lots of things. i'm pretty sure therapy will help with that... changing bad habits whose toll is always this hell.
i'll keep writing. thanks ted
@TedShifrin $(f^*(\alpha_1),f^*(\beta_1))$ and $(f^*(\alpha_2),f^*(\beta_2))$ are linearly independent and all linearly dependent for all other cases. But as far as I know, the linear independent and the determinant argument works for vector space.
In this case, coefficients are $\Bbb Z$
Tensor with $\Bbb Q$, if you want. How can two vectors give determinant 1 if they’re both parallel to the same vector?
05:41
evening SE Math
 
1 hour later…
06:52
in my day people stayed up later than they seem to now
07:22
in my day people checked on granddad far less frequently
much to grandad's detriment
Indeed, we are now living in a post covid-19 apocalyptic world. 😷💉
07:39
people say mathematician are low in ego
reminds of gauss
$\frac{1}{2}n(n+1)$
07:54
classic
08:36
@zacts that's what math teacher mean when they say even kids can do it lol
today again I embarrassed myself by asking dumb question
 
2 hours later…
10:16
@copper.hat how are you doing? ;-)
@TedShifrin nice sentiment, but not always possible. I didn't have many, but I do remember pulling some all-nighters trying to finish something, or cramming for a biology exam.
 
2 hours later…
12:32
good morning
@BannedUser actually I had an idea with that unrelated to your post
I'm working through another text, the book of numbers by conway. I'm just tinkering a little bit.
$\frac{1}{2}n(n+1)$ gives the nth triangular number.
I kind of had the idea to connect structures together.
to form a chain or molecule of structures kind of.
$\frac{1}{2}n(n+1) + \frac{1}{2}n(n+1) + \frac{1}{2}n(n+1)$ could give a larger more complicated structure.
$3[\frac{1}{2}n(n+1)]$
also connecting different polygonal numbers together like this too.
doesn't have to be $\frac{1}{2}n(n+1)$
n(n+1) is the pronic number, the product of two consecutive integers.
I'm also about to begin the Introduction to Number Theory by Apostol.
conway does this actually in ch2 of the book. it's kind of like combining polygonal numbers into a jigsaw puzzle. I'm just tinkering with extending the idea a bit.
12:53
coolio
13:24
@LucasHenrique what source is this? seems kinda dubious, they're doing a non-standard convention for orienting the boundary
Frobenius algebras and 2D topological quantum field theories
by Joachim Kock
ok, that strikes me as the opposite of the kind of source one should first learn this material from
13:47
hi
if inserting a diagonal on $I\times I$ between endpoints b and d (call diagonal bd) gives us a triangulation of the torus, then we must have a topological embedding $h:bd->h(bd)$ such that $h(b)=h(d)$ and this is a contradiction since $h$ is injective
right?
14:14
@TedShifrin $f^*(\alpha_1)$ and $f^*(\beta_1)$ are lineary independent. But $f^*(\alpha_2)$ and $f^*(\alpha_1)$ are $\Bbb Z$-linearly dependent and $f^*(\alpha_2)$ and $f^*(\beta_1)$ are $\Bbb Z$-linearly dependent so $f^*(\alpha_1)$ and $f^*(\beta_1)$ are $\Bbb Z$-linearly dependent which is a contradiction.
but I wonder if this determinant argument holds for general case
Btw I found in Dummit foote chatper 11.4 that I can still use the result (relation between det and lineary dependency) for general commutative ring with 1 $R$.
14:32
@love_sodam Well, this is the real reason I love differential forms as opposed to singular cochains. Wedge product is skew-commutative. Cup product isn't quite. I haven't thought that part through.
in the vein of earlier conversations, i'm finding myself trying to look up the Weyl integration formula for U(n)
specifically U(2)
and boy do i not find it easy
esp. since i think i actually need it for a non-class function
P.S. before I take the cat to the vet at an ungodly hour. @love_sodam These are matrices of integers, so why are you talking about determinants with non-commutative rings?
I don't know none of this stuff, @Semiclassic.
Bye for now.
I'm talking about determinants with commutative rings.
15:09
0
Q: Non-existence of degree $1$ map $M_g\to M_h$ for $g<h$,

love_sodam If $M_g$ denotes the closed orientable surface of genus $g$, show that degree $1$ maps $M_g\to M_h$ exist iff $g\geq h$. Construction of degree $1$ map for $g\geq h$ is easy. I want to prove the converse using cup product. From now on, the basic idea is given by @TedShifrin. First I consider $(...

15:46
@TedShifrin back from the vet?
15:59
to focus my brain on something. suppose i have some rank-1 projector $P$ on $\mathbb{C}^d$. If I apply a unitary transformation, i get another projector $P'=U P U^\dagger$. Suppose I apply a random unitary transformation and average over $U(n)$, i.e., $\int_{U(d)} U P U^\dagger \,d\mu(U)$ where $\mu(U)$ is the left-invariant Haar measure on $U(n)$. I think this should just be the identity matrix $1_d$, up to a multiplicative constant.
16:33
Oh, I highly doubt that.
$n=d$ in the above, i keep slipping up on that
If we do $d=1$ and average over the circle, we can certainly compute this very explicitly.
Hmm, close. I think I get $1/2$ the identity.
well, the argument by invariance i'm seeing is that for any unitary $V$ we have $$\int_{U(d)} VU P U^\dagger\,d\mu(U) = \int_{U(d)} U P (V^\dagger U)^\dagger\,d\mu(U)=\int_{U(d)} U P U^\dagger V\,d\mu(U)$$
Any clever way of computing the last fifth digit of this number $((5^5)^5)^5)^5$?
Last five digits?
So mod $10^5$? Ugh.
16:37
via the left-invariance of Haar measure
so $V$ must commute with $\int_{U(d)} UPU^\dagger \,d\mu(U)$ for arbitrary unitary $V$
Note that you can simplify, though, and then look for patterns. $(a^b)^c$ simplifies to ... @barista
hence it's proportional to the identity
@Semiclassic OK, I'll buy that. Originally I was thinking $0$, but my quick back-of-Sudoku computation gave $1/2$.
and the constant can be found by tracing
yeah, my brain kept going to that too
this is a warm-up for the following problem, which i -think- i know how to address now
namely, use invariance arguments to compute $\int_{U(d)} (UP U^\dagger)\otimes (UQ U^\dagger)\,d\mu(U)$ for projectors $P,Q$ on $\mathbb{C}^d$
Is there any reason to expect the average of the tensor products should be the tensor product of the averages? Hmm.
It's actually not the average of the tensor product, either. :*(
16:42
The argument i've cobbled together is: Let $S$ act as the exchange operator on the tensor product, i.e., $S (u\otimes v)=v\otimes u$
Or is it?
and let $F(P,Q)$ be the above integral
I'm being slow. Is $PU^\dagger\otimes UQ = P\otimes Q$?
Matrices are certainly not scalars.
hmm. i don't think so?
No, I don't think so at all.
So this is not the average of the tensor products, at all.
16:44
the longer way to write the integrand is $(U\otimes U)(P\otimes Q)(U\otimes U)^\dagger$
which means we're not averaging over all unitaries on the tensor product, just those of the form $U\otimes U$
Right.
@robjohn I'm hitting yet another mid- (well, mid is no longer appropriate) life crisis :-).
This is reminding me of all sorts of integral geometry subtleties I dealt with back in my thesis.
@copper STILL?
the fact that $S^2=1$ and $S(U\otimes U)S=U\otimes U$ is the key to making this work, i think
so $SF(P,Q)S = F(Q,P)$
hmm, that's right. i was only able to actually calculate the case $Q=P$
I'm trying to convince myself without the computation that the $1/2$ is right. I'll leave you to your mess :P
16:47
@TedShifrin its recurrent :-). the son of an irish friend is visiting and just set off on a week long california trip, so we had a brief 'son' for a night and then a goodbye.
Well, @copper, it's cool to reconnect briefly. Look at the positives!
well, in the case $P=Q$ we have $SF(P,P)=F(P,P)S$ and therefore $F(P,P)$ can be diagonalized in the same basis as $S$
but that doesn't help with $P\neq Q$
@TedShifrin it was lovely. he'll be back. i'm just a bit nervous about his trip :-). can't turn off parent mode.
OK, @Semiclassic, I've convinced myself the $1/2$ is right. Start with projecting on the line spanned by $v$ and then on the orthogonal line. Average those. As we rotate, the average stays the same.
@copper Is he driving, hitching, what?
16:49
right
in the invariant calculation, it comes out from the fact that the averaging will leave the trace unchanged
Hell if I know what happens in larger dimensions.
Oh, that's nice.
and since tr(P)=1 for a rank-one projection, we need to end up with $1_d/d$
I should have thought of that. Bad Ted.
@TedShifrin driving one of our cars down US 1 to San Diego, then back through Yosemite (very rough approximation of itinerary).
Oh, I hope it's not the car that explodes.
16:51
boom
I don't know if Rte 1 is reopened everywhere. They had another landslide.
I presume you all checked that.
It's a beautiful drive. I did stop in Yosemite for 3 days on my way back from Berkeley about 4-5 years ago. But Yosemite to SD is a haul.
17:13
ok, here's a stab at the above. since $P$ and $Q$ are both projectors on $\mathbb{C}^d$, they're conjugate: $Q=WPW^\dagger$ for some unitary $W$
3
Q: Check if the following series converge

l0ner9$$\sum_{n=1}^{\infty}\frac{1 \cdot 4 \cdot 7 \cdot ... \cdot (3n+1)}{n^2 \cdot 3^n \cdot n!}$$ This is my solution: Let's rewrite the question: $$\sum_{n=1}^{\infty}\frac{(3n+1)!!!}{n^2 \cdot 3^n \cdot n!}$$ If we use D'Alembert's criterion: $$\lim_{n \to \infty} \frac{\frac{(3n+4)(3n+1)!!!}{(n+1...

I tried this a lot without using Raabe's test but no success.
The answer uses gamma function but I was trying to solve without that.
I think that I can use that to write $F(P,Q)=(1_d\otimes W)F(P,P)(1_d\otimes W^\dagger)$
and thus reduce the problem to the $P=Q$ case
hi @Semiclassical
o/
what a 'fun' problem
@Semiclassic You mean the usual trick of replacing $g\in G$ by $g_0g$?
17:17
right
But then your diagonal turns into something else.
i probably need to be a bit more careful that i'm being
hmm
Not that I'm paying much attention.
Probably meant $gg_0$, anyhow. Bi-invariant volume form.
17:18
yeah, i think i see what you mean
this argument gets me to $F(P,WPW^\dagger)=F(W^\dagger P W,P)$
which is neat
but not what i wanted
ultimately the case i'm interested in is $F(P,1-P)$
so maybe i should focus on that
Still with separate averaging?
not sure what you mean by separate. it's $F(P,Q)=\int (U\otimes U)(P\otimes Q)(U\otimes U)^\dagger \,d\mu(U)$
oh. if $Q=1-P$ then the integral splits into two terms
$\int (U\otimes U)(P\otimes 1_d)(U\otimes U)^\dagger\,d\mu = \int (UPU^\dagger)\otimes 1_d\,d\mu = \frac{1}{d}1_d\otimes 1_d$ for the first
So you've restricted to the diagonal here — same $U$ on both factors.
and $-F(P,P)$ for the second. so I actually am fine just looking at $F(P,P)$
right
so, my argument from earlier: since $S(P\otimes Q)=(Q\otimes P)S$, we have $SF(P,P) = F(P,P)S$
so $F(P,P)$ commutes with $S$ and therefore they share a common basis
Hence I should be able to write $F(P,P)$ as a sum of the projectors for $S$
Which, following some other stuff I know, should just be $(1\pm S)/2$
17:40
right multiplication by a fixed element in a ring allows us to view the ring as a subring of endomorphisms on its underlying abelian group. is there a name for rings with the property that every such endomorphism corresponds to right multiplication by an element?
18:10
and since $F(P,1_d-P)=\frac{1}{d}1_d\otimes 1_d-F(P,P)$, that means I can write $F(P,1_d-P)=A (1_d\otimes 1_d)+B S$
all that's left is to compute $\text{tr}[F(P,1-P)]=Ad^2+Bd=1$ and $\text{tr}[SF(P,1-P)]=Ad+Bd^2=0$
so $B=-A/d\implies A=1/(d^2-1)$
Confusing using $A$ and $B$ for scalars :P
I'll trust you.
hm, true
yeah, replace them with lower-case
Does that change the computation? :D
lol
inasmuch as it changes what i'd type out :p
$$F(P,1_d-P)=\frac{1}{d^2-1}\left[1_d\otimes 1_d-\frac{1}{d}S\right]$$
Hmm, not cool for $d=1$.
18:17
hm
you're right
oh. but the only projector in $d=1$ is the identity itself
$1-P$ doesn't exist
so this computation wouldn't make sense when $d=1$ to begin with
Oh, duh, I was using $SO(2)$ and projecting on real subspaces.
You didn't catch me earlier when I talked about a line and the orthogonal.
yeah
careless of me
Now I take it all back.
in some sense I might haven been better of working in terms of the projectors $P_{\pm}=\frac12(1_d\otimes 1_d\pm S)$, but i didn't want to use $P_{\pm}$ for that
guess I could have done $P_S$ for + and $P_A$ for - (symmetric and antisymmetric)
this is converging on the results i expected, at any rate
Well, congrats :)
18:24
yeah, glad i could get this working
it's too hifalutin for the purpose i initially had in mind, which is a pity, but i know a simpler calculation for that
not as illuminating but elementary
Is this all coming from that exercise from the unknown professor?
yes, though it's an outgrowth of that
Just shows to go: You shouldn't rip off other people's homework without making sure you know how to do it :D
specifically, i wanted to put together a solution where i showed two ways that don't work, and then how to combine them into a way that does work
and in the process i noticed something interesting about the second way
Interesting pedagogy.
Is this a grad course?
18:26
yeah
well
OK, then all's fair.
grad students + upper-division
we didn't end up assigning the problem, though
LOL, oh, OK.
Is this a QM course?
18:27
quantum computing, technically, but same difference
Ohhh, presumably at a higher level than you're planning to teach :)
the lecture notes we lifted that problem from are more advanced, yeah
the solution is sorta neat, though
you're looking for functions $f_A(\sigma\cdot a),f_B(\sigma\cdot b)$ on the sphere for unit vectors $a,b$
such that both take values in $[0,1]$ on the sphere, their averages on the sphere are both 1/2, and the average of their product should be $\frac14(1-\lambda\,a\cdot b)$ for some $\lambda$
first way that doesn't work: Pick $f_A=1$ when $\sigma\cdot a>0$ and 0 otherwise, and $f_B=1$ when $\sigma\cdot b<0$
those both average to 1/2 as needed, but the average of the product is computed via the overlap of these two hemispheres
OK, that makes sense.
my brain isn't working, but that'll end up being a linear function of the angle between $a$ and $b$
rather than a linear function of $a\cdot b$ itself
so that won't work
That doesn't sound correct to me, but I'm not going to work it out.
Very rare to get a linear function of actual angle.
18:36
i mean, think of a hemisphere from $\phi=0$ to $\phi=\pi$, and then another hemisphere from $\phi=\gamma$ to $\phi=\gamma+\pi$
the overlap is just from $\phi=\gamma$ to $\phi=\pi$
oh. i'm using the physics convention. so $\phi$ is polar angle not azimuthal
Granted. Oh, but you are using thus clunky indicator functions. I see.
I don't care.
OK, I yield.
Wait a minute.
i was right the first time anyways. i always mix up azimuthal vs polar
The area is not just proportional to the angle, is it? On a circle, it is. But on a sphere, I need to think about it.
18:39
it is. think of looking from the north pole
There's the $\sin\phi$ or $\sin\theta$ or whatever you have that you need to integrate. This is why zones of spheres have area dependent only on height.
right. i really did mean that the azimuthal angle goes from $\phi=\gamma$ to $\phi=\pi$
so no factor of sine
Yeah, it's like lunes.
right, 'spherical wedge' is what wikipedia calls it
That's for the solid ball.
On the surface, it's a lune.
18:41
ahh
alright, fair enough
OK, anyhow, I have yielded.
so anyways, that doesn't work
the next thing to try is choosing a distributions which are linear functions of $\sigma\cdot a$ and $\sigma\cdot b$
Howdy, demonic @Alessandro.
so $f_A(\sigma\cdot a)=\frac12 (1+\sigma\cdot a)$ and $f_B(\sigma\cdot b)=\frac12 (1-\sigma\cdot b)$
18:44
Why necessarily different signs?
because if we choose it like this, then the average value of $$f_A(\sigma\cdot a)f_B(\sigma\cdot b)=\frac14(1+\sigma\cdot a-\sigma\cdot b-(\sigma\cdot a)(\sigma\cdot b))$$
is just $\frac14(1-\frac13 a\cdot b)$
if we pick the same sign, we'd have gotten the wrong sign
Where did the "correct" sign come from?
an annoying choice at the start of the problem, honestly
Oh, you want the negative. Never mind.
the quantum calculation gives you wanting the average to be $\frac14(1-\lambda\,a\cdot b)$
18:46
This is a pretty intensive problem for an upper-division physics course. Is it natural from the viewpoint of physics?
it's coming from Bell inequality stuff
which I know not.
basically, you're trying to come up with a hidden variable model of quantum correlations
OK, so it is motivated.
and the lesson will end up being that you can do it, if $\lambda\leq 1/2$
what the present example does is show that you can make it work for $\lambda=1/3$, which is actually enough to establish it for $0\leq \lambda \leq 1/3$
but it doesn't get you to $\lambda=1/2$
18:49
Why did you choose those $1/2$ coefficients?
Oh, to get the right average value.
But if you stick another coefficient in front of $\sigma\cdot a$, you can adjust the outer coefficient.
Why can't you put a large coefficient there?
because $f_A\in [0,1]$
Outer coefficient knocks it back down.
then you'd lose the 1/2 average, no?
18:51
I was using the outer coefficient to make the average right.
it needs to be $f_A(\sigma\cdot a)=\frac12(1+\lambda \,\sigma\cdot a)$
and if $\lambda>1$, then $f_A(a\cdot a)=\frac12(1+\lambda)>1$
Wait, the $\lambda$ doesn't affect the average because the average value of $\sigma\cdot a$ is $0$.
So we need something in there like a square.
no? $\int \frac12(1+\lambda \sigma\cdot a)\,d\sigma/(4\pi) = \frac12$
18:53
Looks like something's happening here.
the average over $\sigma$ kills $\sigma\cdot a$, and all that's left is the $1/2$
that's normalized in the way i want it
I meant $(\sigma\cdot a)^2$ :)
Then there's a positive average value and you can adjust with $\lambda$ and the outer coefficient.
Nah, a @Balarka. It's all fake.
ah, i see what you mean. the problem is that if $f_A$ includes $(\sigma\cdot a)^2$, then that'll change the average value of the product
love_sodam posted his question because I didn't make further comments.
Oh, the average value of the product had to be bilinear.
right
including higher-order terms in $f_A,f_B$ will just spoil that
18:56
Yeah, that sorta ties your hands. "Never mind." (To quote Rosanna-danna.)
Yup, you convinced me.
@TedShifrin Alas, intellectual lethargy doth triumph curiosity
so it doesn't work for $f_A,f_B$ to both have support on hemispheres, and it doesn't work to have $f_A,f_B$ both be linear functions on the sphere
Something like that, @Balarka. It's interesting how people don't learn basic problem-solving skills any more.
@Semiclassic So it's impossible.
Throw in a bump function :D
nope. we need to combine them. have $f_A=1$ if $\sigma\cdot a>0$ and $f_B(\sigma\cdot b)=\frac12(1-\sigma\cdot b)$.
Oh, I see. Mix and match, rather than combine.
18:58
yeah
Sorta a cool problem, but requires hours :P
without loss of generality we can pick $a$ to be $e_z$, so we're integrating over the upper hemisphere
Of course.
Back to our original question :)
With the Gaussian.
18:59
@TedShifrin Been attending a student present rational homotopy theory from Griffths-Morgan. Quite a beautiful fact that rational differential forms on simplicial complexes can be extended off subcomplexes, despite being piecewise polynomial.
right. though that really is overkill here. by symmetry we know that the $x,y$ components of $\sigma$ still integrate to zero
Essentially $x^n$ acts as a bump function (vanishes at $x = 0$, is 1 at $x = 1$)
I have owned those notes since forever, @Balarka, but I rarely looked at them carefully.

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