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7:03 PM
If x is in D/S’ then x is not a limit point of S hence there’s a deleted nbd around x that doesn’t intersect S. Ohh and inside that nbd, I can’t go and say let V be a small nbd inside. Why? Because if there are two elements inside they will be separated by distance 1.
It still needs work
Nah, it’s fine. If a point y is such that d(x,y)=1 then y must lie in S.
 
yeah, OK. subsets of a discrete space can't have limit points
S' will be empty for any S, even if S is the whole space
 
You beat up my question to death again :)
Thanks a lot for that :-)
@Alex I think that needs more work. Unless I’m missing something, I understand that using Cesaro you can show that $\lim \frac {\sum x_n}n=\lim \frac {x_{n+1}}{n+1-n}\to 0 $. I’m not sure how you obtained $x_n\sim 1/n$.
 
@amWhy Ted is so fun to provoke; how else can one get smacked?!
 
@robjohn Good point! ;D
 
7:21 PM
@Koro $x_n-x_{n+1}=x_n^2\implies\frac1{x_{n+1}}-\frac1{x_n}=\frac{x_n}{x_{n+1}}\sim1$
 
What is $[\nabla_{\alpha},\nabla_{\beta}]g_{\mu,\nu}$?
 
Perhaps $\nabla_\alpha\nabla_\beta g_{\mu,\nu}-\nabla_\beta\nabla_\alpha g_{\mu,\nu}$? or were you looking for something more descriptive?
 
More descriptive, with christoffel symbols
that's true and i'm assuming connection is levi civita
 
@robjohn yes, thinking more on this made me understand :)
 
so it must be 0
but I want expression in terms of christoffel symbols
Or instead, I would like to know that $\nabla_{\alpha}(\partial_{\beta}g_{\mu,\nu})$ is
 
7:27 PM
is $\nabla_\alpha=\alpha\cdot\nabla$?
 
$\nabla$ is connection on manifold
 
@robjohn Is there an alternative way to write the proof without using Cesaro? A more elemental way?
I would like to write a proof without Cesaro 🤔
 
@Alex you could essentially reprove Cesaro
@WojciechKulma that image won't display
 
@robjohn I was thinking in the following way: we have $a_{n}\sim 0$
 
hey @robjohn, many thanks, I figured it out already!
 
7:38 PM
I will try to write again
 
$\partial_{\alpha}\partial_{\beta}g_{\mu,\nu}-\Gamma^{\sigma}_{\alpha \beta}\partial_{\sigma}g_{\mu\nu}-\Gamma^{\sigma}_{\alpha \nu}\partial_{\beta}g_{\sigma \nu}-\Gamma^{\sigma}_{\alpha \nu}\partial_{\beta}g_{\mu \sigma}$
is that it?
 
Does it work? We have $x_n \sim 0$. Suppose that $\sum x_n <\infty$ so wr have $\prod (1-x_n)\sim a>0$. But $x_{n+1}/x_{1}=\prod (1-x_n)\sim a>0$, contradiction to $a_n\sim 0$
$x_{n+1}/x_n=1-x_n$
 
It looks correct. But $x_n\sim 0$ is probably an abuse of notation? As by $a_n\sim b_n$, it is understood that $\frac {a_n}{b_n}\to 1$.
 
@Koro yes, but it's more easy to write that $\lim x_n=0$. I'm sorry :(
 
I see. But I like your argument to avoid Cesaro's theorem. :)
 
7:48 PM
Thank you so much for your corrections
 
You're welcome!
 
@Koro :3 thanks
For now I'll go play chess for a bit or maybe go for a run like @copper.hat :) Today seems to be a good day
 
@Alex unfortunately my 'running' is more fast walking. my competitive running days are over :-)
 
@copper.hat At some point in my life, I participated in a 5km race. I did not win, but I was in a position number 10 of a total of about 200 participants. Did you also do athletics?
 
@Alex just running, cross country.
i like outdoors stuff, but have some restrictions due to accumulated injuries :-).
 
8:01 PM
Copper, did you ever go to Hyderabad?
 
@monoidaltransform that's awful
 
@Koro Unfortunately the furthest south I went was Kolkata.
 
i know
i'm trying to get an expression for the commutator of the metric tensor
commutator of the connections on the metric tensor I mean
 
8:37 PM
are you sure you don't want curvature instead
 
what do you mean? The problem is : Calculate the left hand side of : $[\nabla_{\alpha},\nabla_{\beta}]g_{\mu \nu}=0$
@Thorgott
 
that expression does not make sense to me
 
$[\nabla_{\alpha},\nabla_{\beta}]g_{\mu \nu}=\nabla_{\alpha}\nabla_{\beta}g_{\mu \nu}-\nabla_{\beta}\nabla_{\alpha}g_{\mu \nu}$
@Thorgott
 
that still doesn't actually explain the symbols
there's a ton of implicit things going on when you write an expression like that and I want you to spell them out, both so that you get a better understanding of what you wanna do and so that I get an understanding of what you wanna do at all
 
So $\nabla_{\beta}g_{\mu \nu}=\partial_{\beta}g_{\mu \nu}-\Gamma^{\sigma}_{\beta \mu}g_{\sigma \nu}-\Gamma^{\sigma}_{\beta \nu}g_{\mu \sigma}$
which is 0
 
8:53 PM
writing down equations is not what explaining means
 
jay
9:07 PM
hi
people use the term robust quite loosely in mathematics right
 
@jay Context?
 
jay
for instance, say you have some method to solve ODEs $\dot{x}(t)=f(x(t))$, which only works ( or has only been proved for ) a small class of functions $f$, would it be ok to say such a particular method is not robust ?
I guess more specifically you would just say not yet generalised
i just hear people throw around the word robust and wonder if it has a more specific meaning than 'strong/healthy'
 
Maybe stability of a numerical solution?
 
@jay I don't like that usage very much.
I think that @TedShifrin has the context moar gooder.
In my experience (which is far from exhaustive), "robust" tends to refer to numerical methods.
A numerical method is "robust" if, for example, small perturbations or errors don't cause problems (i.e. if the method is "stable").
 
@monoidal if the covariant derivative of the metric is $0$ (which it is), then any further covariant derivative is the derivative of $0$.
 
jay
9:19 PM
@XanderHenderson hmm ok, I hear it outside numerics community too, anyhow thanks :)
 
@jay Which is why I asked for context.
 
jay
Yeah sorry I cant rememebr exactly
 
As I said, in my experience, "robustness" is an adjective which I associate with numerical methods.
 
jay
someone talking about martingales is all haha :)
yes I thought so too, cheers!
 
In the mathematical subfield of numerical analysis, numerical stability is a generally desirable property of numerical algorithms. The precise definition of stability depends on the context. One is numerical linear algebra and the other is algorithms for solving ordinary and partial differential equations by discrete approximation. In numerical linear algebra the principal concern is instabilities caused by proximity to singularities of various kinds, such as very small or nearly colliding eigenvalues. On the other hand, in numerical algorithms for differential equations the concern is the growth...
> Some numerical algorithms may damp out the small fluctuations (errors) in the input data; others might magnify such errors. Calculations that can be proven not to magnify approximation errors are called numerically stable. One of the common tasks of numerical analysis is to try to select algorithms which are robust – that is to say, do not produce a wildly different result for very small change in the input data. [emph added]
 
9:27 PM
I would not say that the word is used loosely, I would say that it is qualitative.
 
@TedShifrin yes ofcourse
But he wants us to find another expression of the covariant derivative
 
@copper.hat Something something condition number something something.
 
@monoidaltransform More generally, could you find an expression for $[\nabla_{i},\nabla_{j}]T_{a b}?$ where $T_{a b }$ are the components of a (0,2)$ tensor?
 
@XanderHenderson I have seen the term used in a variety of situations, not just numerical methods, but always in the context of a sensitivity of sorts. I suppose that just replaces one word by another...
 
10:03 PM
$T^{\sigma}_{\beta}g_{\sigma \mu}$ evaluate to? $T_{\beta \mu}$? Note the metric is on the right now
 
10:16 PM
I am forced to use the mobile interface for a while. I notice that the buttons at the top of the page to see responses and reputation don’t create a drop down menu like they used to. Is anyone else seeing this? On my laptop, they were working fine.
 
 
1 hour later…
11:29 PM
Can the manifold $\Bbb R^2$ be thought of as the gluing of four components along boundaries?
 
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