What is the type of this kind of pde?: For given $H:\Bbb R^3\to\Bbb R$: smooth function, $L:\Bbb R^3\to\Bbb R^3$: smooth vector field, $v\in S^2$, find a smooth function $f$ on $\Bbb R^3$ such that $L\cdot v = D_vf+Hf$
trying to decide whether it's worth posting this to the main site
suppose i want to find a sequence of rotations that takes me from one sphere orientation to another. in mechanics we usually do this via Euler angles, to the misery of all physics students
the standard decomposition is to look for a Z-X-Z sequence of rotations
and that makes sense, b/c in mechanics you've typically got the Z-axis picked out (by the direction of gravity, say)
but aside from that this sequence is arbitrary, e.g., one could instead look for a X-Z-X decomposition
suppose i know the Euler angles for that decomposition. how does one go from these angles to those for the Z-X-Z decomposition?
i imagine the answer is something something quaternions
looks like the Wikipedia page covers this well enough. oh well
Urgh. I'm doing 'prehab' at the moment. Not sure it helps, but the PT chap is interesting to talk to. He probably breathes a sigh of relief when I leave.
koro, you (or maybe your source) are using language a little imprecisely here. the integral formula that is often used to define the fourier transform on L^1 may not converge for elements of L^2. there is nevertheless a unique extension of the map defined by the integral formula (regarded e.g. as a map from S(R^n) into L^2(R^n) for example) to a unitary map on L^2(R^n). this extension, which is often/always also called "the fourier transform," does exist for L^2 functions.
unitary, or scalar multiple of a unitary, i guess, depending on how/whether you normalize.
so this thing you call "this approximated fourier transformation" may be just the fourier transform.
this is not something you can easily piece together across different references (whcih may use different definitions) but wherever the details come up, they would be in verifying that such an extension exists and is unique.
it might even be possible to set definitions up so that it holds more or less by definition, in which case it would probably be a theorem that such definition is implemented by an integral formula for L^1 functions or compactly supported smooth functions or whatever.
copper's vibe of "use some kind of approximation argument" is the right vibe, but the details of turning the vibe into a theorem might depend on exactly how the fourier transform is defined on L^2
yeah, it can look like cheating, unless the fourier transform is simply defined that way :) but it does take some thought to check that the "approximation" recipe makes sense.
rudin would definitely do it, the only question might be whether rudin uses some weird functional analysis definition by which the identities are trivial and the hard part is proving that they relate to the thing that people who aren't rudin would define via integral formulas.
i don't think he does anything that weird in his functional analysis book, but functional analysts sometimes do that.
Here is what I meant by “approximated FT”: I know that L^2 functions can be approximated by functions in S. Fourier transformation of functions in S also lie in S. S is a subset of L^2.
So we define the limit of Fourier transforms of approximation functions in S to be the FT of L^2.
@leslietownes these links have enough details. This will do.
it would be good practice to specify the context if you are using the term yourself, and if an author is using it, they should ideally supply the context. but a ring is (among other things) a group with respect to its addition operation, and without further context other than knowing that x is an element of a ring, i would start with a presumption that "the order of x" means the order of x in that additive group
Problem: let $X$ be a topological space. Prove that if $U$ is open, then $\partial U =\overline{U}\setminus U$. My work: since $U$ is open, $X\setminus U$ is closed and so $X\setminus U =\overline{X \setminus U}$. Hence, by definition of boundary, we have $\partial U = \overline{U} \cap \overline{X\setminus U} = \overline{U} \cap (X\setminus U)$.
Now, I would like to conclude by saying that $\overline{U} \cap (X\setminus U)=\overline{U} \setminus U$; I think it's true because $\overline{U} \cap (X\setminus U)$ means "being in $\overline{U}$ and being in $X$ and not being in $U$" and, since $X$ the universe set, saying "being in $\overline{U}$ and in $X$" is equivalent to be in $\overline{U}$. But I'm not sure that this argument is correct. Can someone confirm it or explain why is wrong?
the order of a group is the cardinality of its underlying set. the order of a ring is the order of its underlying group, i.e. the cardinality of its underlying set.
In mathematics, an order in the sense of ring theory is a subring
O
{\displaystyle {\mathcal {O}}}
of a ring
A
{\displaystyle A}
, such that
A
{\displaystyle A}
is a finite-dimensional algebra over the field
Q
{\displaystyle \mathbb {Q} }
of rational numbers
O
{\displaystyle {\mathcal...
this somehow reinforces me that we shouldn't use the word order when dealing with rings?
Suppose $f: [a, b] \rightarrow \mathbb{R}$ is monotonic. Prove that there exists $c \in [a, b]$ such that $\int_a^b f(x) dx$ = $f(a)(c-a)$ + $f(b)(b-c)$
I could prove it, but now I am trying to think if we can always choose c such that $c \in (a, b)$
@copper.hat Addressing your comment that people are demanding "pro forma rubbish": I don't think that anyone is asking for that. They are asking for context, which will help to explain what the asker knows, and what kind of answer they are expecting.
This is the policy on the site---it is part of a compromise, which is intended to reduce the number of homework problems dumped on the site. If you don't like the policy, lobby folk on meta to change it.
For what it is worth, I am not a big fan of the policy, because it still permits too much homework dumping.
@X4J If the function is constant, then you can choose $c=a$ or $c=b$. The proof I have in mind guarantees a $c \in (a,b)$, but perhaps the author has something in mind for some special cases in which either $a$ or $b$ can be chosen.
Suppose $f: [a, b] \rightarrow \mathbb{R}$ is monotonic. <br> Prove that there exists $c \in [a, b]$ such that $\int_a^b f(x) dx$ = $f(a)(c-a)$ + $f(b)(b-c)$
And it is true
The second is to determine if the following statement is true: Suppose $f: [a, b] \rightarrow \mathbb{R}$ is monotonic. <br> Prove that there exists $c \in (a, b)$ such that $\int_a^b f(x) dx$ = $f(a)(c-a)$ + $f(b)(b-c)$
I don't understand which part of the argument you are trying to change: are you looking for $f$ not monotonic, or for $c$ explicitly in $(a,b)$, rather than $[a,b]$?
say a functions f is in L^1 (R) and L^2(R) both. It is known that there exists a sequence of functions {g_n} in S(R) -Schwartz space that L^1 converges to f, and there also exists a sequence of functions {h_n} in S(R) -Schwartz space that L^2 converges to f. Question is: does there exist a sequence $\phi_n$ of functions in S(R) -Schwartz space, that converges to f in L^1 and L^2 both ways?
Note that if $f$ is monotonic, then $\int_{a}^{x} f(t)\,\mathrm{d}t$ is continuous, and so you can make some kind of intermediate value theorem argument.
@Koro doesn't convolution do the job? I think what you do is consider molifiers $\phi_n$, and then $f* \phi_n\to f$ in $L^p$ for all $p$ that $f$ is in
There is a tool in mathematics that I have used a lot of times and I'm still not confortable with. In fact I can't figure out (by this I mean that I cannot understand it geometrically) why does convolution regularize things. It is know for example that if $u\in L_{loc}^1(\mathbb{R}^N)$ and $f\in ...
In mathematics, mollifiers (also known as approximations to the identity) are smooth functions with special properties, used for example in distribution theory to create sequences of smooth functions approximating nonsmooth (generalized) functions, via convolution. Intuitively, given a function which is rather irregular, by convolving it with a mollifier the function gets "mollified", that is, its sharp features are smoothed, while still remaining close to the original nonsmooth (generalized) function.They are also known as Friedrichs mollifiers after Kurt Otto Friedrichs, who introduced them....
@Koro "to mollify" is a standard English word, meaning something like "to soften, or smooth out, or to reduce the severity of". The usage in mathematics makes perfect sense to me---a mollifier "smooths out" a function, in the sense that convolution with a mollifier gives you something which is in $C^{\infty}$.
@XanderHenderson yes, when I looked at the wiki page that Jakobian linked, I noted that 'Mollifiers' was not hyperlinked so thought it's a mathematical word. But digging deeper into the history of the word, it appears to have come from French.
@ThomasFinley we might try to start with the additive group, and worry about multiplication later. The only abelian with $6$ elements is $\mathbb{Z}/6\mathbb{Z}$, so we know we need to add some structure to it
Now we can consider all possibilities for multiplication, and rule out the case of non-commutativity step by step
it might be a little trickier if you consider non-unital rings as well
@ThomasFinley oh, I know, this should be easy actually, non-unital or not
just write $x = 1+...+1$, $y = 1+...+1$ and use distributivity for both $xy$ and $yx$
$1$ meaning the additive generator of the cyclic group, not necessarily the unit of the ring
If the addivitive group of a ring $R$ is generated by just one element $a$, then writing $x, y\in R$ as $x = na$ and $y = ma$, we'd have $xy = yx = nma^2$
so $R$ must be commutative
where $n, m\in\mathbb{Z}$
This automatically gives us commutativity of rings of square-free size, like $6$
@Jakobian Yes, that's the apparent idea. The main thing is to write elements of R $x,y$ in the form $ma,na$ where $R=<a>$ and $m,n\in\Bbb Z^+\cup \{0\}.$ The commutativity follows from the equality: $xy=(ma)(na)=(mn)(a^2)=nm(a^2)=(na)(ma)=yx,$ and we are done as $x,y$ are arbitrary elements of R.
This is precisely the argument that we have to do for this particular problem.
Prove that a ring of order $6$ can never be an integral domain.
My solution:
Let $R$ be a ring of order $6$ which is an integral domain. This means, that $1+1\neq 0\in R$ and we note that, $(1+1)(1+1+1)=0,$ a contradiction as $1+1,1+1+1\neq 0.$ So, $R$ is not an integral domain.
However, I fee...
munchkin just got her kindergarten report card, they had two behavioral remarks, one was "often rude to instructors," the other was "plays nicely with the fourier transform"
You made some uncalled for snide remarks a few days ago when I wasn't in the room. You think you're funny, but calling me out for being impatient when I was being extraordinarily patient with someone does piss me off. Just quit.
Hi everyone :) A few days ago I posted a question with BOUNTY+50 on the Gauss-Newton algorithm, starting from a nonlinear system. Is there anyone kind and talented enough to help me please?
The Gauss–Newton algorithm is used to solve non-linear least squares problems, which is equivalent to minimizing a sum of squared function values. It is an extension of Newton's method for finding a minimum of a non-linear function. Since a sum of squares must be nonnegative, the algorithm can be viewed as using Newton's method to iteratively approximate zeroes of the components of the sum, and thus minimizing the sum. In this sense, the algorithm is also an effective method for solving overdetermined systems of equations. It has the advantage that second derivatives, which can be challenging to...
OK, so this looks like using linear algebra to implement the least squares solution of an inconsistent linear system. Why are you trying to use this for a nonlinear system?
I won't republish the question link out of respect for everyone, to avoid spam, because I already published it yesterday in the group. You can find it in my profile. The question is titled "Gauss-Newton algorithm to solve a non-linear system?"
@TedShifrin I need a parameter to use in Poisson. I want to calculate this parameter using the Gauss-Newton algorithm, starting from a nonlinear system.
@TedShifrin My goal is to use Poisson (which is not relevant to this question, because with this question i just want to get the only parameter of Gauss-Netwon to use in Poisson) to individually calculate the probabilities of a football club scoring 0 goals, 1 goal, 2 goals, 3 goals, 4 goals, etc. etc. So I need to find a parameter using the Gauss-Newton algorithm.
@TedShifrin In an experimental test, i tried to use the Arithmetic Mean in Poisson, then i use the parameter 1.6 to calculate the probability that a football team individually scores goals, 1 goal, 2 goals, 3 goals, 4 goals, etc. etc. The results are decent, but I would like to get something more precise. So I thought of using another parameter, which is what i would like to find with the Gauss-Newton algorithm and the nonlinear system.
Oh, anyhow, reading more carefully in your Gauss-Newton link, I see that it is Newton's method in the multivariable setting. So I don't know what you expect us to do.
@XanderHenderson I was cranky last night. However, I think posting half-hearted efforts or regurgitating theorems does not constitute effort, and many reasonable questions get closed. Furthermore, it happens without allowing a reasonable amount of time for the OP to even respond.
@Horiatiki I find it very hard to decipher, and your handwriting doesn't help. Can you typeset the relevant material? So $F$ is the function with the parameter you're trying to solve for, and the givens are the $f_e$ values?
@XanderHenderson The closure is hard to undo, so it effectively removes the question. Absolutely makes sense for dups or near dups, but the requirement of 'effort' should at least allow some response time.
@TedShifrin The sheet is an extra attachment added, but it doesn't have much importance. I also wrote the things written on the paper in the application. Exactly, it's as you say
no, I am expecting a practical usage of the fact like Fourier transformations can be used in segregating specific frequencies from a mix of frequencies.
@Koro because $\Bbb R^n$ is contractible, a surface of genus $\geq 1$ has zero higher homotopy groups (as it has universal cover $\Bbb R^2$), thus group cohomology of surface groups may be computed topologically/geometrically
I may be missing context here, but Fourier transforms and their ilk have myriad 'practical' applications. (Not clear that faster communication of snapchat messages is practical.)
I was about to ask you, though. Can you just boil this down to an explicit question here. You have an overdetermined system. ONE variable only? The function with the one variable is the Poisson distribution with parameter (variable) $\mu$? @Horiatiki
However, motivating like that can be difficult, for example, the FFT is useful for computing convolutions, but then you have to explain why convolutions are useful and that gets you back to square one.
@copper.hat like integration has many practical uses and one of them is designing buildings etc., so does fourier analysis. What is "contractibility of R^n" good for practically?
@TedShifrin The basic, initial idea, is to start from List_Goals: [1, 2, 2, 1, 2] which i organize in the non-linear system, building it with the goals [1, 2, 2, 1, 2] and the number of times the event occurs
If the goals scored are <= 0 events, then i will have 0/5 = 0; If the goals scored are <= 1 events, then i will have 2/5 = 0.4; If the goals scored are <= 2 events, then i will have 5/5 = 1;
Contractibility of $\Bbb R^n$ implies manifolds are locally contractible, which implies they have a well-behaved covering theory. I'm no expert, but I'm fairly sure covering spaces of manifolds have applications in physics
@Koro Every closed $k$-form is exact. This settles classical questions in greater generality, generalizing every curl-free vector field has a potential, and every div-free vector field is a curl.
That's very real world if you deal with vector fields.
@TedShifrin With one variable, you would have the Hessian $2(f(x)f''(x) + f'(x)^2)$ and Newton's method would use this Hessian. Gauss Newton uses $2(f(x) \cdot 1 + f'(x)^2)$.
I'll go now and close the PC. I greet you and point out the link again in case it is needed. BOUNTY+50: Gauss-Newton algorithm to solve a non-linear system? I know it's a bit of a difficult question, I apologize for the difficulty. Thanks anyway for your attention :)
@copper.hat I have no idea why you are getting downvotes, as I am not one of the people who cast any downvotes. I would guess that @TedShifrin is correct, and that the downvoters believe that you shouldn't have answered the question.
Ultimately, the fact that PSQs are proliferating and the brigade is more militant will deter many long-term members like us from participating in the site.
@TedShifrin I know you are right. I'm sorry. This is the best I can show you. I have never used the Gauss-Newton algorithm. I'm just a math enthusiast. I just wanted to find a new parameter for Poisson. Then a Norwegian mathematician recommended Gauss-Newton to me. He gave me some initial advice and wrote me that paper. I am studying Gauss-Newton algorithm hard and I understand the theory of him, but I have difficulty solving it with practice