last day (16 days later) » 

hi :)
Hi. What's up?
Im good and you?
what's wrong?
15:50
The weather outside is dreadful.
where are you from?
So i guess you dont like the winter :P
i dont like it either .. but i guess in europe the winter is much colder
I don't like the eternal rain.
yea it can make you sad
do you like measure theory ? ^^
15:55
I'm fairly impartial on that. Some nice things, others not so nice.
i think i just solved the question i wanted to ask you lol
Cool. What was it about?
i think your "impartial" is better than some very good students
$f_n , f \in L2$ and $lim f_n = f$ a.e
$||f_n|| \le M$
first i need to show that $f\in L\ ^ 1$
the second part is to show $||f_n- f||_1 \to 0$
the space is finite $\mu(X) \lt \infty$
so we get that $L2 \subset L1$
so the first part is easy
Yeah, that's a crucial assumption. Would be terribly wrong for infinite measure.
i found a mistake in my solution to the other part :/
i thought using Egorff thm.
you familiar with it?
15:59
Almost everywhere convergence gives almost uniform convergence when the measure is finite.
its supposed to be $||f_n||_2 \le M$
yea right so we have $A $ with $\mu (A \ ^ c) \lt \epsilon$ and $||f_n -f||_1 \to 0$ on $A$
Yes. And on $A^c$, Cauchy-Schwarz helps.
now im stuck ^^
Cauchy-Schwarz?
Famous inequality.
yea i know it
do you mean to use Holder's inequality?
16:02
$$\int_X \lvert f_n - f\rvert \cdot \chi_{A^c}\,d\mu$$
Well, Cauchy-Schwarz is the special case $p = q = 2$ of Hölder.
yea right. wanted to write it :P
so $||fg||_1 \le ||f||_2||g||_2$
you suggest taking $f_n-f$ and $x_{A \ ^ c}$ ?
Sounds like a plan.
so we get $||f_n-f||_1 \le ||f_n-f||_2 \epsilon$
on $A \ ^ c$
There's a square root missing.
i feel like $||f_n-f||_2 $ should tend to $0$ \
16:07
Need not be. But we don't need that. It's bounded.
right because $||f||_2 \le M$ also
right ? ^^
and you are right it should be $\sqrt{\epsilon}$
Yes. But even if it could be larger, we still would have $\lVert f_n - f\rVert_2 \leqslant \lVert f_n\rVert_2 + \lVert f\rVert_2 \leqslant M + \lVert f\rVert_2$.
right , because it's in $L2$ then $||f||_2$ would be finite
i think it would be bounded by M because of dominated convergance
Do we have a dominating function? Not necessarily.
$M$
wait no.
16:13
But we have weak convergence, and that implies $\lVert f\rVert_2 \leqslant M$.
im talking no sense
dont we need the convergance to be monotone to get that?
and the functions to be positive
Monotone convergence would immediately imply $L^2$ and $L^1$ convergence. If we had that, Egorov would be unnecessary.
how did you conclude $||f||_2 \le M$ ?
Weak convergence. The closed balls are weakly closed, and $f_n$ converges weakly to $f$.
But, as said above, we don't need that, a bound independent of $n$ is enough.
right ok
i have an exam on Thursday :P
16:22
Good luck.
Thanks. i think measure theory is the best course so far that i took
do you have a favorite field? i mean measure theory / complex analysis /algebra/ .. ?
Complex analysis, point set topology, topological vector spaces, analytic number theory.
I have an exam on complex analysis course in 2 weeks ^^
Can i have one more question ?
You could try.
$\mu ,v$ finite measures. i need to prove that there is disjoint measurable sets $X = A \cup B$ s.t $\mu \bot v$ on $\Sigma \cap A$ and $\mu <<v << \mu$ on $\Sigma \cap B$
i have a partial solution.
we have that either $\mu \bot v$ or there is $\epsilon \gt 0$ and $A \in \Sigma$ s.t $v(A) \le \epsilon \mu(A)$
if $\mu \bot v$ we are done
if not , we are not ^^
16:36
Have you looked at the Radon-Nykodim derivatives with respect to $\mu + v$?
wow you are fast :P
hm. let me try it
do you mean that we have $f,g$ s.t $d\mu = fd(\mu+v)$ and $dv = g d(\mu+v)$ ?
do i need to use the $\epsilon $ from my partial solution?
and the $A$ of course
You certainly don't need to. Whether it would be useful, I don't know.
alright . we have $\int_A f-g d(\mu+v) = \mu(A) -v(A)$ for all $A \in \Sigma$
any chance for a bigger hint ?
i dont see how to get those $A,B$
16:46
When, on some $M \subset X$, you want to have $\mu \ll v$, what conditions on $f$ and $g$ does that impose?
hmm
if $g=0$ a.e then $f=0$ a.e ?
or $f-g=0$ a.e ?
a.e. with respect to which measure? But note that $f + g = 1$ ($\mu + v$-a.e.).
right.
im dog asks for a walk ^^ i will think about your hints while walking with him. can i write to you like in an half hour what i've got?
I'll be away for dinner then, but you can, I'll read when I return.
17:46
@DanielFischer you there?
18:19
@Liad Not then.
first i thought taking $A=\{x: f(x) >g(x)\}$
and $B=A \ ^ c$
but now i think that the set $B= \{x: f(x) + g(x) = 1\}$
would be better
not sure if im right, im just checking it
its not working either
Not quite. On a set where $\mu \ll v$, you can write $d\mu = h\,dv$. What does that tell you about $f$ and $g$?
$fd(\mu+v) = hdv$ ?
i really dont know where to take this..
And $dv = g\,d(\mu + v)$, so …
f=hg
18:28
And since $f + g = 1$ (a.e.) …
(h+1)g = 1 a.e?
is there something obvious im missing?
$f = h(1-f)$, whence $h = f/(1-f)$ ($= f/g$)
alright
btw if we work with positive measure, do we know that $f$ is positive?
Nonnegative. And I was assuming we speak of positive measures. We'd need a couple of absolute values and some modification if we're speaking about complex or signed measures.
yea we are working with positive measures, just wanted to know
alright where we going with $h=f/g$ ?
18:37
When does that break?
when $g=0$ ?
so $B = \{x : g(x) \ne 0 , f(x) \ne 0\}$ ?
Yes. We could add any subset of the set where both vanish, but that only complicates things.
im writing it down to see if i understand it
so on $A$ we have that $\mu=v=0$ correct?
18:46
No. That may be, but usually isn't. Consider two point masses at different points.
but on $A$ the functions vanishes
so $\mu(E) = \int_E 0 d(\mu+v)$
At every point of $A$ one of them (possibly both) vanishes.
for all $E\in \Sigma\cap A$
i thought $A=\{x : f(x) = g(x) = 0\}$ , oops
so we can take $C = \{x : f(x) = 0\}$
$C \subset A$
and then $C , A-C$ would show $\mu \bot v$
on $\Sigma \cap A$
alright part 1 is done ^^
we saw that if $\mu <<v$ then the $h$ you wrote will be $f/g$
but we need to prove the converse dont we? that $\mu <<v $ on $\Sigma \cap B$
and $v << \mu$
18:52
So suppose $N \subset B$ and $v(N) = 0$. Then how do you see that $\mu(N) = 0$?
is it legal to say $d(\mu+v) = d\mu /f$ ? ^^
wait that's not giving something useful.
More conventional to write that $\frac{1}{f}\,d(\mu +v)$.
That's of course not valid everywhere, but on $B$ it's fine.
but it make no sense to me. i see the equation $d\mu = fd(\mu+v)$ as :
$\mu(M) = \int_M f d(\mu+v)$
so how can we write $d(\mu+v) = 1/f d\mu$ ? what does it mean?
the same? $(\mu+v)(E) = \int_E 1/f d\mu$ ?
It means $$(\mu + v)(M) = \int_M \frac{1}{f}\,d\mu$$
ok that fixes things to me
wasn't sure about it
so $v(E) = 0$
implies $\int_E g/f d\mu = 0$
does this implies $\mu(E) $ = 0?
19:14
$v(E) = 0$ implies $\int_E \frac{1}{g}\,dv = 0$.
you sure its $1/g$ ?
We could take any function. In view of what we want, $f/g$ is the more direct route, but $1/g$ is great too.
$0 = v(E) = \int_E g d(\mu+v) = \int_E g/f d\mu$
Yeah, that works too. We want $\mu(E) = 0$. Writing $\mu(E) = \int_E w\,dv$ yields that immediately. Writing it as $\int_E g/f\,d\mu$, we need to say that $g/f$ is strictly positive a.e. on $E$, hence $E$ must be a $\mu$-null set.
it is possitive because g and f both are positive
19:21
Yes.
im not sure why there is something that bugs me with this.
we have $\int_X f d\mu = 0$ iff $f=0 $ a.e
Using that $f \geqslant 0$. Yes. What bugs you?
we got $\int_E g/f d\mu = 0$
so $g/f = 0$ a.e , and this is not true
It is, because $E$ is a null set.
so its a claim , if $f\gt 0$ on $E$ then $\int_E f = 0$ iff $\mu(E) = 0$ right?
19:29
You need to write $\int_E f\,d\mu$ there. Yes, the integral of a strictly positive function is zero if and only if the domain of integration is a null set.
thank you very much
is it alright if i stay in this room and if i get stuck on something to consult with you?
you really helped me with that question ..
 
1 hour later…
20:38
@DanielFischer im trying to prove the claim you wrote. if $\int_E f d\mu =0$ , and $f>0$ .is there any nice way to show $\mu(E)= 0$? i cant say $f>c$ for some $c >0$..
Consider $\int_E n\cdot f\,d\mu$ for $n \in \mathbb{N}$.
hmm
its going to infinity O_o
so $\int_E \infty d\mu =0$
i got what you meant?
20:49
i must find a question that it will take more than a second to solve ^^
i think i found it
In mathematics, the Riemann hypothesis is a conjecture that the Riemann zeta function has its zeros only at the negative even integers and complex numbers with real part 1/2. It was proposed by Bernhard Riemann (1859), after whom it is named. The name is also used for some closely related analogues, such as the Riemann hypothesis for curves over finite fields. The Riemann hypothesis implies results about the distribution of prime numbers. Along with suitable generalizations, some mathematicians consider it the most important unresolved problem in pure mathematics (Bombieri 2000). The Rieman...
can you point me in the right direction? ^^
Look at the growth of the Mertens function.
lol. no idea what that is
im going to sleep now, thanks a lot for the help today.
can i stay in this chat and maybe ask you some questions tomorrow if i'll have some? i will try my best to minimize the amount of questions ^^
In number theory, the Mertens function is defined for all positive integers n as M ( n ) = ∑ k = 1 n μ ( k ) {\displaystyle M(n)=\sum _{k=1}^{n}\mu (k)} where μ(k) is the Möbius function. The function is named in honour of Franz Mertens. This definition can be extended to positive real numbers as follows: M ( x ) = ...

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