#advanced-pdes
1 messages · Page 4 of 1
a simpler example is the exterior derivative. I can express d locally as d/dx^i dx^i and solve locally for exact functions, but I have to piece them together to actually get a globally exact thing
this is where the topology of your manifold comes in
Evans proves that $W^{1,p}(U)\subset\subset L^p(U)$ for $p<n$, and claims that for $p>n$ it follows from Morrey's inequality and Arzela Ascoli
.whoever
I don't see how this is the case
Ok I see now
D^-h is bounded so it is bounded in L2 for any compact set uniformly in h. Now using that L2 is reflexive and a diagonalization argument, extract a subsequence of D-h which converges for all compact subsets. Finally, extract an a.e subsequence from this which ensures the almost sure bound.
I'm not sure but I don't think so
If you want to try searching online the keyword is "boundary integral method"
Oh actually I've changed my mind I think it is true
Oh nevermind I've changed my mind again
There is a normalizing factor in front but it doesn't scale the same way that the surface area of a sphere scales
Whatever just ignore me
I am pretty sure it is true, it always holds for all randomized numerical experiments I did
I think min-max would be violated if it were not true
Because then I can pick an f to make a point in the interior be larger or smaller than the points on the boundary
i.e. if w is not positive and integrating to 1 one the Dirichlet boundary
Ok I believe that
Doesn't hold for biharmonic though I think, because there is no max-min principle there
i.e. it models plate bending, and the bend can happen in the middle of the domain, resulting in a max/min away from the boundary
Thing is I have never seen it formulated as such, so I was wondering whether there's a reference discussing this property of the Laplacian's Green's functions
Boundary integral method literature probably
That's pretty sparse (at least from what I have found) when it comes to arbitrary mixed boundary conditions
The best I could find there was Melnikov's paper discussing Green's functions for a square boundary
You don’t have a mixed boundary condition though?
I do, Г_N and Г_D
In fact the tests I did are for such a boundary, and the Г_D boundary is even fairly arbitrary (not a square)
Oh wait they are not the same boundary?
Of course not
You can't prescribe both d_n u = 0 and u = f on the same boundary in general
Weak convergence implies subsequence converging a.e.?
Nope
Well not in Lp. It does for continuous functions/uniform-convergence
What do you mean?
If (X = C[0,1]) then ( f_n \rightharpoonup f \iff \sup_{n \in \mathbb{N}}\lVert f_n \rVert_{\infty} < \infty \land \forall x \in [0,1]: f_n(x) \xrightarrow{p.w.} f(x) ).
If (X = L^p[0,1], p \in (1,\infty)) then (f_n \rightharpoonup f \iff \sup_{n \in \mathbb{N}} \lVert f_n \rVert_{L^p} < \infty \land \forall x \in [0,1] : \int_{0}^x f_n \to \int_{0}^x f. )
cocat
In particular, weak convergence implies a.e. convergence for continuous spaces but not for Lp space
Even more simply, if it did then Lp convergence implies weak convergence which would imply Lp convergence implies a.e. convergence which is false.
But we only know weak convergence in L^2
Not weak convergence in the L^infty norm for C[0,1] right
Oh I did end up equivating weak and Lp convergence. Here's another route: Show that {f in L2 : |f| <=M} is a closed subspace in L2 and then use Mazur to show that it is weakly closed in L2 as well. This should prove your claim.
Wait what exactly did you prove the equivalence of
I didn't prove an equivalence. Merely that if the functions are bounded in Linfty then so is the L2-weak limit
Ok I don't see how to use mazur to show that it's weakly closed
The subspace is strongly-closed convex (why) subset so it is weakly-closed, by Mazur
Oh hmm ok I still don't see the proof but I have proved this in a different way before
In mathematics, Mazur's lemma is a result in the theory of normed vector spaces. It shows that any weakly convergent sequence in a normed space has a sequence of convex combinations of its members that converges strongly to the same limit, and is used in the proof of Tonelli's theorem.
Also is this the mazur you're talking about?
This is a corollary. Check Brezis book for the statement I am mentioning
Ok I just found out, it's actually much easier to look at it differently
L^infty = (L^1)*, and so clearly v_i exists in L^infty and D^{-h_k}_i u converges to v_i in the weak* topology, which is enough to conclude the remaining integral calculation
How are you going from "v_i is a L2-weak/weak* limit" to "v_i is in Linfty"?
I think the full argument (starting with a bounded $L^\infty$ sequence, ending in a weakly convergence subsequence in $L^2_\mathrm{loc}$) is just like:
By Banach-Alaoglu, closed balls in $L^\infty=(L^1)^$ are weakly sequentially compact, so given any bounded sequence $v_n$ in $L^\infty$, we can extract a subsequence with
$$v_{n_k}\to v $$
in the weak-$$ topology. This $v$ lies in the same $L^\infty$-ball as the elements of the sequence.
This means $$\int (v_{n_k}-v)\phi \to 0 $$
for any $\phi\in L^1$.
In particular, for any $\phi\in L^2$ and compact $K$, we have $\phi\cdot 1_K\in L^1$, so
$$\int_K (v_{n_k}-v)\phi\to 0 $$
for any $\phi\in L^2$ and any compact $K$. That is $v_{n_k}\to v$ weakly in $L^2_{\mathrm{loc}}$.
gomez
Hmm, yeah I suppose this is cleaner than extracting a L2 convergenct on all compact sets via diagonalisation and then using Mazur to conclude the bound.
yeah I didn't know what you were referring to with mazur tbh, but I am sure there are lots of ways.
This is what I was referring to in the use of Mazur. In particular, {f in L2 : |f|_\infty ≤ M} is a closed convex subspace that is strongly-closed, so by mazur's theorem (which states that any closed convex is weakly closed), we have that it is weakly closed. This lets us get the linfty bound on the weak l2-loc limit. But yeah, very round-about way which isn't prolly what Evans intended
okay fair enough, that sounds like it works too then. personally I just default to banach-alaoglu whenever possible in such questions because it's by far the fact about weak convergence I understand best, and it is very versatile.
Oh yeah, I definitely agree yours is prolly what Evans was intending too as well, given that he completely skips the argument out.
yea
The thing is I don’t see why we need to worry about L^2 at all
We just need the subsequence converges weakly in L^infty
Then that’s enough to say that int v_i phi = lim int D^{-h_k}u phi
Like we don’t need to worry about converging weakly in L^2
I havent looked it yet, but I think Evans never defined weak* convergence so that's why he might be reluctant to use it
Yes, I think you are right about this. There might be some reason like cocats guess about why Evans didn't write it this way but whatever.
Oh true yeah
im trying to better understand the motivation for sobolev spaces. brezis gives the following bvp
-u'' + u = f
u(a) = u(b) = 0
and reaches the attached picture
i don't see the relevance between that and this condition
i understand how the weak derivative makes sense, i just don't see why brezis picked the above example to motivate sobolev spaces
oh i should have maybe posted this in the analysis channel. lmk if i should move it
im trying the much simpler ode y'' = f
if we do the same integration by parts after multiplying by a test function we get
,tex (\int_a^b\varphi' y' = -\int_a^b f\varphi)
maximofs
Hello, any good references to learn about Lyaponuv and LaSalles principle please?
I think the point is that for the first equation to make sense, u and u' only need to be in L^{1}, which by defn of sobolev spaces means u needs to be in W^{1,1}. So rather than looking for C^2 solutions to the original eqn you can look for W^{1,1} solutions to the weak formulation.
yeah i understand that
i think over the time where i asked it to now i basically understood the motivation for the weak derivative though
thank you anyways
L^{1}_{loc} is sufficient
ye p good point
I'm stuck on this exercise. Suppose $P$ is a polynomial in $d$ variables and degree $r$. Let $m\geq \max(d+1, r-1)$ be so that $|P(ik)|\leq c(|k|^m+1)$ for some constant $c$ and any $d$ dimensional real vector $k$. Prove that the equation $P(\partial)u=F$ has a continuous Green's function.
porphyrion
I managed to prove $G=\left(\frac{1}{P(ik)}\right)^{\wedge}$ (inverse Fourier transform) is continuous and satisfies $\hat{G}=\frac{1}{P(ik)}$. We just need to show $G\ast F$ is a solution to the equation.
porphyrion
I know $u=G\ast F$ is a weak solution. However I don't know how to prove it's also a classical solution.
porphyrion
Any help for this problem
i think u_y identically 0 because its 0 on the full boundary of the square + maximum principle. maybe thats what the hint means? then u must depend only on x
but u is harmonic, so u''=0 gives u is linear
but the first constraint gives u(0)=u(1)=0, so u is identically 0
check the details i might be wrong lol
np
Does anyone know if there is a yudovich type well posedness equation for the barotropic vorticity equation on a rotating sphere
So specific
Christophe Lacave wants to know
For a rotating sphere I don't know, but I may remember something about rotating cylinders, but I don't think it was barotropic
For reference what I mean is $\frac{D(\zeta+f)}{Dt}=0$ and $u=\nabla\cross(\Delta^{-1}\zeta)$ as the system
守沢千秋
I don't remember exactly
For a function $F$ defined on some function space, the functional derivative $\pdv{F}{\rho}$ the radon nikodym derivative of the functional $\phi\mapsto\lim_{\ep\to0}\frac{F(\rho+\ep\phi)-F(\rho)}{\ep}$, is there any reason why to define it using the radon nikodym derivative and is there any motivation? Like taylor series maybe
Whoemily
Oh so we can view the functional derivative as the gradient of F at point rho
Let me type this out one sec
When we're looking at a functional, we're usually trying to do something like some energy minimization for example, so it's natural to want to find some landscape for it, i.e. what "direction" the functional is moving with small changes in the input
The integral,
[\int \frac{\delta F}{\delta \rho} \varphi dx]
is the L2 inner product between $\varphi$ and our functional derivative so the functional derivative is the $L^2$ gradient of $F$ and the above integral can be viewed as the directional derivative. If we consider the analogous case in some finite dimension space, for a vector valued function, $f(v)$, its directional derivative in the direction $u$ is defined $Df(v)[u]$, or $\nabla f(v)\cdot u$.
So when we are looking at our functional, we call $\epsilon\varphi$ the variation of $\rho$ for an arbitrary continuous (or smooth) $\varphi$.
[\varphi\mapsto\left[\frac{d}{d\epsilon}F(\rho+\epsilon\varphi)\right]{\epsilon=0}]
defines a linear functional so we can appeal to Riesz representation to find a measure so that
[\int \varphi d\mu =\left[\frac{d}{d\epsilon}F(\rho+\epsilon\varphi)\right]{\epsilon=0} ]
Through Radon-Nikodym, we let $d\mu = \frac{\delta F}{\delta p}dx$.
Kirbemily
What I'm more wondering about is like, the usual derivative has a justification that it's the best linear approximation, does there exist analogous statement for functional derivative? And now do we even rigorously state this and can we derive this definition of functional derivative using this rigorous statement
Ah I see, hm. I haven't seen an analogous statement to best linear approximation, like viewing it in terms of variations is where I've seen it discussed the most
I found this
The taylor expansion
Maybe this can help with justifying
It would make sense for the first term to be $\int\pdv{F}{\rho}\phi$ since we have a sum of the coordinates in the finite dimensional case
Whoemily
As I think about your question, first and second variations are analogous to first and second order approximations
The Radon-Nikodym bit is directly from Riesz-Representation so it should just come down to working things out analogous to a finite dimensional case
Hmm you can actually arive at this definition if you define the derivative to be ${\pdv{F}{\rho}}(\phi)=\lim_{\ep\to0}\frac{F[\rho+\ep\phi]-F[\rho]}{\ep\phi}$
Whoemily
But the calculation feels purely symbolic I can't quite put them in the right context
for the Gateaux differential, not really, it doesn't have to be linear
You would need a Frechet derivative
But afaik they typically define the functional derivative using the Gateaux derivative
How do we justify that maximizing a functional equates to setting gateaux derivative to 0?
in a similar way you justify nabla f = 0 being the stationary points of f
You're simply taking derivatives wrt "vectors", and those vectors happen to be functions
Well I know the intuition but how should you prove that?
Oh
Basically the gradient in each "direction" should be 0 but in this case direction is a function
When you write $\langle \frac{\delta F}{\delta \rho}, \phi\rangle = \int_{\Omega} \frac{\delta F}{\delta \rho} \phi = \partial_{\phi} F$
criver
You see that the functional derivative dF/drho is really the counterpart to the gradient
Calculus of variations
But the idea is similar to standard calc yes
The only difference is that your vector space is made up of functions now
Note that even if the Gateaux derivative exists, this doesn't mean that the Frechet derivative or gradient do
So the definition $\partial_{\phi} F(u) = \lim_{\epsilon\to 0} \frac{F(u+\epsilon \phi)-F(u)}{\epsilon}$
criver
Jusr gives you the directional/Gateaux derivative
This being equal to inner product of the functional derivative with phi requires a little bit more
Ahhh I finally see what you meant by L^2 gradient
That was really helpful thx
Sorry I realized that I wasn't as descriptive as I should have been there
As for books, Calculus of Variations by Filip Rindler seems to have everything you'd be interested in
https://encyclopediaofmath.org/wiki/Gâteaux_variation
https://encyclopediaofmath.org/wiki/Gâteaux_differential
https://encyclopediaofmath.org/wiki/Gâteaux_derivative
https://encyclopediaofmath.org/wiki/Differential
https://encyclopediaofmath.org/wiki/Fréchet_differential
https://encyclopediaofmath.org/wiki/Fréchet_derivative
https://encyclopediaofmath.org/wiki/Differentiation_of_a_mapping
https://encyclopediaofmath.org/wiki/Gradient
This part is actually misleading if you compare to other resources. I prefer the definition where the gradient is the Riesz representer of the Frechet derivative, and as such it requires a Hilbert space structure unlike the Frechet derivative.
https://encyclopediaofmath.org/wiki/Functional_derivative
https://encyclopediaofmath.org/wiki/Extremal
https://encyclopediaofmath.org/wiki/Variation_of_a_functional
https://encyclopediaofmath.org/wiki/Radon-Nikodým_theorem
https://encyclopediaofmath.org/wiki/Differentiation_of_measures
In short you have a few concepts: Gateaux variation/differential/derivative (terminology is unfortunately inconsistent in the literature, sometimes they require linearity, sometimes not) is a generalisation of directional derivative from calculus. Frechet differential/derivative is a generalisation of (total) derivative from calculus. When we speak of "differentiability" in R^n in calculus, we really speak of Frechet differentiability. The gradient nabla F is the vector such that for any v we have <nabla F, v> = D_v F, where D_v F is the directional derivative of F along direction v. If you assume that F:R^n -> R is continuously differentiable then the representation of the Frechet derivative as a matrix is the 1xn Jacobian J_F. Note that the "gradient" wrt the standard inner product is then the transpose of that, i.e. it is the Riesz representer of the functional. Similarly for F:R^n->R^m continuously differentiable the representation of the Frechet derivative is the mxn Jacobian J_F. The Radon-Nikodym derivative is a kind of derivative defined w.r.t. measures. The Euler-Lagrange equations essentially arise by setting the Gateaux derivative to be equal to zero, which typically results in ODEs/PDEs, that give you the stationary points.
if you have a bounded sequence in $L^{1}(0,T; L^{2})$ what weak limit can you identify if any? Perhaps something which is a radon measure in time but L^{2} in space...?
m6li
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assume we're on a bounded spatial domain
I doubt we can say anything. For example, if your spacial domain is a singleton, then L2(U)=R so that we have L1(0,T;R) functions bounded, but you don't have a weak limit (even a subsequence) merely from norm-boundedness (as it is equivalent to reflexivity)
@lilac barn But if you consider a bounded sequence in L^1 for example, we can embed into the space of radon measures and use the compactness of that space to deduce the existence of a subsequence converging to a measure
I am wondering if there is some way to do this in bochner spaces
Do you perhaps mean weak* convergent in the double dual? In any case, I would look here: https://mathoverflow.net/questions/250677/what-is-the-banach-dual-of-the-bochner-space-l-infty-omegax
ill take a look thank you
Well this has no answers…
sorry if this is the wrong chat but i am doing PDEs and idk where else this should go
my notes define this
and then say this
but clearly (unless im going insane) (m_uv)^-1 is equal to itself
and moreover, we defined the d'alembert as d_tt - laplacian, so isn't what they wrote actually - [square] ?
i know this is all super basic stuff but its irritating me and googling stuff comes up with physics i dont like
I think I know which pdf this is lol
I think throughout this whole pdf the notation of minkowski metric is inconsistent by a negative sign
is this a summer project btw
?????
It's because the d_mu also include time
what r the chances
So you get laplace - dtt
yeahh but this is minus square
because at least in these notes they defined it as dtt - laplace
that's what he meant by it's off by a sign
i feel like i might be needing a lot more help 😭
haha yes
Some authors alternatively use the negative metric signature of (− + + +),
i'm also struggling a bit in the last twenty or so pages in the notes haha
are you a third yr btw
when did u start
It's just conventions
i only started like few days ago so ur miles ahead of me
yes
last wed
thats still some impressive speed .. !
Can you link your notes? I am just curious what they have
ahh ok yeah i'm sure you're the one other person doing my project then lol
Thanks
Seems quite painful
Like Kolmogorov's $k^{-5/3}$ law, but for entropy?
lightyagami2010
The material
all that for a 3rd year project? bruh
Yes
Hello, I am wondering why bounded operators don't have continuous spectrum, in other words, why we can't find a bounded operator $T$ such that $\lambda - T$ is one to one and has a dense image while its inverse is unbounded. why this can't be the case?
Thank you in advance
Mikahopff
Of course they can.
Eg map from L^2[0,1] to itself that is multiplication by x.
Doesn't the fourier transform also have a continuous spectrum
so bounded operators can have a continuous spectrum?
I just told you this and provided an example.
Thank you, I am studying the example.
does anyone know stuff about homogenization here?
Where can I find a proof of sobolev functions is absolutely continuous when restricted to almost every single line parallel to a given axis
Have you tried proving it
if not in evans, it's probably in evans-gariepy
Thx I think I found what I need in there
can someone explain to me why cant i solve complex PDEs like navier stocks equstion with the laplace transform?
i mean not solve because i will need more equstions
but simplify it dramaticly
Yeah, linearity let’s you turn derivatives into a polynomial using the Fourier/Laplace transform
This makes solutions pop out
Oh ok ty
you can even write matrix ODEs that are linear and are not diagonalised by Fourier
e.g. d_t u = Au, where A is not circulant
Even if not diagonalisable you still have JNF.
My point wasn't that it is defective, it was that it could be diagonlisable by something else entirely. In the discrete case A is diagonalised by the DFT when it is circulant, e.g. it arises from discretisations of PDEs with periodic boundary conditions. DCT would be for reflecting/Neumann BCs, DST would be for clamped/Dirichlet, etc. There was a paper specifying the class of matrices diagonalised by those, it was a subclass of Topelitz + Hankel. We can plug in A with other eigenvectors there however, so u = P exp(tD) P^{-1} u(0) will not be given by the DFT/DCT/DST.
let $f$ be a measure, $g \in C_{c}$ on $[0,T] \times \mathbb{R}$. If I have the equality $$\int_{\mathbb{R}} g(t,x)f(t,dx) = \frac{1}{2}g(0,1) - \frac{1}{2}g(0,-1)$$ for any $t$ is it possible to deduce what $f(t, \cdot)$ will be?
m6li
Why are there two
two what
yes
Apply Riesz-Markov-Kakutani representation theorem
ah ok this says there exists some unique borel measure such that the above equality holds
i was wondering if there is some easy way to read off what f should be just from the equality
there probably isnt enough info to determine that though...
but can we say f is a difference of two deltas?
just from the information above
mor specifically
well
Yes because that's for all g in C_c
it just says for g supported on [0,T]xR
oops iddnt mean to delete
$$f(t, \cdot) =\frac{1}{2}\delta_{(1-t){+}} - \frac{1}{2}\delta{-(1-t)_{-}} $$
m6li
so we cant deduce this from the previous equality, right?
I have no clue what those deltas are supposed to be
the more I look at this the stranger it gets
is f supposed to be a measure on [0,T]xR
conclusion is im probably not
yeah
or an assignment of a measure on R to each t in [0,T]
no not that
Yeah this is not good notation
f is defined on [0,T] \times \mathbb{R}
isnt it like how people write \mu(dx) for the lebesgue integral though
I think I’ve seen that on a few math stack exchange posts and it weirds me out every time
well as it stands it's 1/2delta(0,1)-1/2delta(0,-1) anyway yeah
this guy seems to like it
Well I don't like it
being asymmetric in t and x is just bad
i think it makes sense in the context of the notation. because there the function f is cts in time with values in measure space
You do not need to try to justify poor notation
i must
I think the notation is somewhat common in stochastic stuff, idk why it's in adv-pdes
spdes
Stochastic pdes go in #advanced-probability
Can anyone explain me in a nutshell why V being limited and Lipschitz continuous on bounded sets implies that there is a unique global solution?
I know that locally Lipschitz gets us a local unique solution, and globally Lipschitz gets us a global solution, but this one is new for me
You have a unique solution on each bounded set, so you get a unique solution overall by gluing together those solutions
More detail: for each n we get a unique solution f_n on [-n, n] and f_{n+1} extends f_n by uniqueness
So we can glue together to get f
It's unique, because any two solutions have the same restriction to [-n,n] and hence agree there (and hence agree everywhere since this holds for all n)
I’d also like to know. All I know is that there exist no real characteristics for elliptic PDEs
In mathematics, the method of characteristics is a technique for solving partial differential equations. Typically, it applies to first-order equations, although more generally the method of characteristics is valid for any hyperbolic partial differential equation. The method is to reduce a partial differential equation to a family of ordinary...
Do you happen to know an answer to my question in #odes-and-pdes regarding the inverse Laplace transform of a PDE solution?
A problem is that the solution is transcendental in Laplace domain
Do the eigenfunctions of an adjoint differential operator of a PDE have a physical meaning?
For instance they pop up in solving a PDE by generalized Fourier transform (as kernels)
Or more specific, for obtaining algebraic equations of the boundary value problem in transformed domain. Then the eigenfunctions of the original differential operator are used to obtain the solution
The pdf claims that it's possible to solve for u along curves that are not characteristics
That's what I don't understand
What pdf
The screenshot
True but this is what I want to know
most helpful response
it is not about solving "along" the curve that is not a characteristic, it is solving the cauchy problem with initial data specified ON the curve that is not a characteristic.
that is, the equations with \phi, \psi are imposed along this curve.
Is it possible to have a solution to the heat equation where the initial condition has growth condition greater than e^{ax^2} for any a
Look at the tychonov solution
@gleaming lily
https://math.stackexchange.com/questions/3394147/the-tychonoff-solution-of-heat-equation-can-not-satisfy-the-growth-condition-nea I'm on phone, this question shows you what the tychonov solution is
What if we require the solution to be nonnegative
Then we have u=0
For the Cauchy problem
This is Widder's theorem, or just the representation formula theorem
For other initial data g, you get the representation formula where you integrates against a kernel
And this is unique
Oh hmm
If the widder representation integral doesn’t converge then there is no nonnegative solution?
Yes, or in general if u is not able to be uniquely determined by such a representation
Alright hm
So you can't start with an initial condition that's like
Say
e^{x^4}
Yeah, having unbounded initial data in R leads to issues
I have been looking at this for a while now:
and I cannot understnad where the Ito integral disappeared in (9)
Expectation of ito integrals is 0 because they're martingales
Also this should go in adv probability
hey, are you studying quant finance? can I DM you? 🙂 I would like to study that in the future as well & I don't know anybody who learns it
can I DM you as well?
I am not studying quant finance no.
I am just self-studying things I am interested in, the above was more in relation to diffusion processes in machine learning, though I don't really care about the machine learning part
I also HATE machine learning
It's not so much that I hate it, I have no practical experience whatsoever in it - I only took one theoretical ML course that was very outdated even back at the time. That said, I don't really plan to delve into ML either. The probabilistic diffusion papers seemed intetesting though and a good opportunity for me to learn a bit on stochastic differential equations.
Bruh currently taking a course in deep learning and professor said it grows a few chapters every 1-2 years because he must update so much😄
Does anyone know if the cutting planes proofs system or something similar has been generalized to a proof system for solving PDEs with constraints?
(This question is probably better suited to #foundations, but maybe someone has thought about it here.)
Hello.
Can anyone explain Shapiro–Lopatinskii condition to me please?
or recommend some references? Thank you in advance,
What do you mean by explaining ?
the intuition begind them, even though I am still not comforatble with the definition
The inuition behind it is to have (sufficiently) general non-degenerate boundary conditions to turn your favorite differential operator as an actual operator on Lp spaces over a domain
The condition is here to ensure the non-degeneracy of your operator (to have a sufficiently huge amount of BCs to close the (resolvent) equations somehow)
Since this is purely local
you can say okay up to localization and change of coordinates
you have a problem on the upper half-space
R^n_+
Then use partial Fourier transform
you will see that to ensure ivnertibility of the boundary layer operator to solve the boundary problem
the Lopatinskii-Shapiro conditions are arising naturally
There are those papers by Davide Guidetti 1991 about Elliptic problems on Besov spaces and Interpolation with boundary conditions
There is also the monograph by Peer C. Kunstmann and Lutz Weis about Maximal regularity that deal with those Lopatinskii-Shapiro conditions
The monograph on also on Lq maximal regularity by Robert Denk, Matthias Hieber, and Jan Pruss also review Lopatinski-Shapiro BCs and they prove (R-bounded) resolvent estimates
Thank you very much for the answer and for the references
Any good book recommendations
Eberhard
diracseasurfer
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diracseasurfer
We define by extension the even, periodic function of period p = 4 which
coincides with the function f (x) on the interval [0, 2]. Plot on the interval [−6, 2]
the graph of the function to which the Fourier series of the even extension of
The function f (x) converges
2b)i,ii
for the one its the same thing but impair anf another intervall
Ça a rien a faire ici. Au mieux #real-complex-analysis .
Oh I thought it was the differential equations channel
Well, the real way to do it is to show that u_m is a cauchy sequence in Lp*. Then it has to converge in Lp*.
To do that, use that it's a cauchy sequence in W1p and the inequality you proved.
The limit of this cauchy sequence in Lp* needs to be the same as the limit in W1p, because in particular both sequences converge in measure (and convergence in measure should be unique)
thankss
Yep, np
Hiya, so for part b I'm not sure what to take as f in the Galerkin expansion, unless they mean that PCE?
I'm referring to this f
I have a question regarding green's function on a $C^1$ boundary. my question is this true $\int_{\partial D}\frac{\partial G_{x}}{\partial \nu}=2\pi$? where $\nu$ is the outward normal vector to the boundary $\partial D$ and $G_{x}$ is the green function corresponding to a member $x\in D$, where $D$ is an open set. I need this result while reading a bit potential theory book. My intuition say this should be true because if I take $D$ as a open unit disc and the point $x=0$ then basiscally my poission kernel for disc is 1 so at the boundary it gives $2\pi$.
Vishnu das
Don’t post the same question in multiple channels
Hi. About sobolev spaces. Am I remembering it right that $H^2(K) \rightarrow C^1(\overline{K})$ for $K$ a rectangle in $R^n$? The arrow denoting continuous embedding. Where can I find these results?
phao
the key phrase is "Sobolev Embedding Theorem"
and the value 2 won't work in general I think, in general it needs go be larger depending on n
Thank you.
Hi! have anyone any clue for this one?
Any clue for this?
I don’t think this is appropriate for this channel
It is indeed not appropriate
The next steps have been confusing me (I've asked this in the help channel a couple of times but to no avail, so I thought I would ask here?)
I can rearrange the algebra to get p as a function of (x,t) but I don't think it uses any of the information from my initial density?
I guess the step to get density as a function of time?
rearranging the information I have gives me:
$\rho = \frac{\rho_{max}}{2}(1-\frac{x}{v_0t})$
SubsonicSpraak
This is the greens function associated with a laplacian?
take the heat equation $u_{t} - a(x,t)u_{xx} = f$ on $(0,T) \times \mathbb{R}$ where $a, f$ are given smooth functions. also assume $u_{0}$ is also smooth. I know if $a$ is constant we have the fundamental solution, but do we still have existence of a smooth solution if a is not constant?
M6LI
iirc on a bounded domain evans says the answer is yes
Depends on the smoothness of A
when I say smooth I mean C^infty
W.r.t. which variable ?
if both then evrything is okay
you also need some uniform boundedness and some positivity/non-degeneracy assumption
in fact i have that a is only a function of x, a is C^infty and 0 < a < 2
so i guess those assumptions are met. is there any ref i can look at for this, or does it follow easily from something else?
to be sure that you met the conditions, you need to assume some strict positivity at infty
a conditions like
yep a tends to some epsilon > 0 at +-infty for me
$0<\mathfrak{a}_0 \leq a (x) \leq 2$
Functionanatolysis
ah
ok perfecr
but what if 0 < a in general but a \to a_{0} at |x| goes to \infty
so a can dip below a_0
oh yeah right right lol
are the derivatives bounded too ?
yes
So here are the steps:
- 1 st, Prove that one can solve uniquely the resolvent equation lambda * u - a(x) D²_x u = f, for f in L², and Lambda >0
- 2nd, recover that u is in H² if f in L²
- 3rd, assume that f is in H^2 can you prove that u lies in H^4 ?
then by induction
if is in all H^s then the solution lies in all H^s
1st step tell you that that you that the operator L= -a(x) D²_x generates a strongly continuous (and even holomorphic) semigroup
the induction part from the 3rd step
tells you that
Functionanatolysis
in particular the solution becomes instantenously smooth
See Brezis Chapter 7 for more details
I am glad you don't have dependency w.r.t. the variable t
everything would completely fail otherwise
ahh ok I will try these steps
Thanks a lot
yeah its because a is just an initial density in fact
Relatively elementary definition thing I hope.
So I know that harmonic functions are defined as having zero laplacian.
I also know it can be shown that Harmonic Functions have the Mean Value Property.
Does this mean that the solutions of the Laplace Equation under arbitrary Dirichlet Boundary Conditions characterise all functions from $B_r(x_0) \to \mathbb R$ with the Mean Value Property in the dimension being considered ?
Ama Dablam
You can prove that a locally integrable function that satisfies the mean value property is harmonic
Thank you 🙂
I've got an exercise to do 🫡
,rotate
Does PDE stuff have any use in group theory stuff (think geometric group theory, algebraic groups, rep theory, lie groups, GIT etc?) Contemplating not doing a PDE course atm
Lie theory was invented for pdes or something
Do you mind elaborating?
Well I can’t because I don’t know anything about it
I don't know about the applications of PDEs in group theory, and at the first sight I don't quite understand how it can be actually used. But group theory can obviously help because of symmetries and so on, a good reference is P.J.Olver Applications of Lie groups to differential equations. There are also more algebraic stuff like differential Galois theory, which is quite analogous to the ordinary Galois theory but it studies the extensions of differential fields (i.e. fields with derivative).
Yeah why would someone care about differential field extensions if they exist?
I am sorry if I confused you. I think that this aspect is more historic for PDEs as it deals only with, say, one-variable linear diffeq. The point of differential Galois theory (or more generally and more precisely the theory of D-modules) is actually more algebraic in nature and useful by providing a framework to apply homological and sheafy stuff to differential equations. I am not an expert in PDEs, but they surely find their applications in algebra.
Ok that makes sense
Aight so I’ve got my first PDEs class and the teacher is already being kinda vague and I don’t like it. I’ve been hearing of the Dirac delta and fundamental solutions for a bit now but I thought we’d cover them reigorously here but it doesn’t seem like it. Teacher kinda just gave the definition of the Dirac delta as a functional without saying what it means to write something like $\Delta \phi = \delta$. So I was wondering if someone had a good resource on learning some basic distribution theory for pdes
𝓛ittle ℕarwhal ✓
So that I get an actual feeling for what I’m doing
Taylor maybe?
The book I like best is strichartz distribution theory and fourier analysis. You can just look at the early stuff. It's a concise and very friendly book though.
This here is defined in terms of integration by parts: loosely, phi should be such that for any f, integral phi(x) laplacian f(x) dx = delta(f) = f(0)
(If the boundary conditions are 0)
do you have references to differential Galois theory? Sounds interesting
I would say instead of learning and spending time on distributions, learn convolution and mollification. Then just go look at how the Dirac distribution is defined. I would argue this would be enough for intro level pdes. Learning distribution theory a bit properly would be an overkill.
.
Peter–Weyl Theorem?
Yeah I can already handle convolutions and mollification fine
Another suggestion is Friedlander-Joshi
Concerning D-modules there are a plenty of introductory resources on the Internet, for instance, lecture notes by A.Braverman, T.Chmutova, P.Etingof, D.Yang, Introduction to algebraic D-modules, but it can be tough for non-algebraists, so I think S.C. Coutinho, A primer of Algebraic D-modules would be a nice and very readable reading at first. Though my expertise of differential Galois theory itself is quite limited, it looks like the nCatLab page contains some good references.
Thanks a lot!
what are the 2 cases, is that what you're askin?
dx/a = dy/b = -du/c is the parameter independent way to solve it i I recall
however, not advanced PDE
I don't relaly know where to put this, but the problem arises in relation to a certain pde thing I'm doing.
I have a (let's say smooth) function $G(m,n)$ and its partial derivative with respect to $n$ is given by $G_n(m,n)$.
I also have a curve $y(x)$ which satisfies the differential equation
$$\ddot{y}(x) = G(y(x), \dot{y}(x))$$
Here, $\ddot{y}(x)$ is the second derivative of $y$ with respect to $x$, and $\dot{y}(x)$ is the first derivative of $y$ with respect to $x$.
I'm interested in the situation where the curve $(y(x), \dot{y}(x))$ forms a closed loop in the $ (m,n)$-plane. The closed loop means that, for some $a$ and $b$, $y(a) = y(b)$ and $\dot{y}(a) = \dot{y}(b)$.
My question is if, under these conditions, the following is true:
$$ \int_a^b G_n(y(x), \dot{y}(x))dx = 0 $$
Cursor
I've tried a few examples and they all seem to satisfy the condition, but obviously a few examples is not a proof
ive been wanting to jump into calculus of variations. does anyone have any recommendations for good resources to use to learn, also what prereqs should i mostly ideally have beyond vector calc, lin alg, and odes
the canonical recommendation is gelfand-fomin
keep in mind that if you want to learn super formally why everything works you'll need a good bit of analysis. but you can learn the ideas and how to do problems without that
analysis here being real and functional analysis
this is a bit of a degenerate counterexample, but it satisfies all your preconditions
Let
y(x) = 1
G(m,n) = mn
a = 0, b = 1
I havent actually seen any books that tackle variational calculus using functional analysis 
Sorry if this isnt quite considered an "advanced" pde, but I have been having difficulty with a laminar, 1D problem that I have been trying to solve using the polar coordinate form of the Navier-Stokes equations
Basically I have pressure-induced flow around an annulus
Are you going to tell us what the problem is
yeah, if you give me a moment
apologies for the poor picture
this kind of a problem
The issue is that, assuming my integration has been correct, in the polar coordinate form of the equations, the velocity curve in the r direction boils down to the form
V = r * (a + c1) + c2/r
and the only way to make this equation exist in the bounds of the problem is to set the constants to such values that the resulting equation is a vertical line
Yeah, thats included in the "a" term
I don't know what this means
it comes out to something like r/mu*dp/dtheta
But presumably you have some boundary conditions (no slip perhaps?) and you know the inner and outer radii of the annulus maybe?
yeah
And you can use this to solve for c_1 and c_2
but that gives me a solution that tells me there is no flow at all
which is the confusion
What does it give you
essentially a vertical line
I don't know what you mean by that
at v = 0
V is a function of r?
yeah
Oh I see
The function has the general form like this
What you're saying is that you get c_2=0 and c_1=-a right
In which case V is probably wrong
You've probably made an arithmetic error somewhere
Ive checked through the derivation multiple times and it seems right
im pretty confident that I got from the base form of navier-stokes to the general solution
actually, I am sure I have a correct form of the equation because if I instead use it calculate flow caused by a rotating annulus instead of pressure, its correct
the general form of that equation would work to model the flow, if I could add 2 more constants
that right there is exactly the profile that I would expect from this type of flow, where the green and blue lines are the problem edges
the problem is that equation looks like this:
I would need c3 and c4, 2 more constants to make that work
I figured I could probably fake C4 by just pretending I moved the problem bounds to fit, since the area under the curve would still be the same
but I have no way of getting C3
by that I mean I have no way of adding C3 to the equation
This isn't a valid example anyway since (y(x), y'(x)) doesn't form a closed loop
You didn't integrate correctly
The integral of 1/r with respect to r is not a constant
god damnit
so that gives me this mess
the first equation there being after the first integration
I'll work through the rest of that when I get into work tomorrow and report back
Can anyone help me to prepare for my examination. I am not able to figure out things right now.
People can try to help if you ask specific questions
criver
actually I think that's "an eigenfunction" of the adjoint
Can this be made to be a valid calculation?
Like can Hopf-Lax formula be made so that we are allowed to calculate with infinity
Okay, I have a weird integral problem which I think I've solved, but I need help ensuring its correctness/finding issues.
Suppose I have a function $G: R \times R \to R$
So we have something like: $G(x_1, x_2)$
Also, it will be important to consider the partial derivative of $G$ with respect to the second argument: $G_2(x_1, x_2)$.
And a curve $y(t)$ satisfying the differential equation:
$y''(t) = G(y(t), y'(t))$
I want to find out what the value of the integral:
$\int_t^{t'} G_2(y(t), y'(t)) dt$ is equal to.
Here's my draft solution. First I'm going to call $y''(t) = a, y'(t) = v, y(t) = x$.
Then the integral is something like:
$$\begin{align}\int \frac{da}{dv} dt \ &= \int \frac{da}{dv} \frac{dt}{dv} dv \ &= \int \frac{da}{dv} (\frac{dv}{dt})^{-1} dv \ &= \int (\frac{dv}{dt})^{-1} da \ &= \int (a)^{-1} da \ &= ln(a) \end{align}$$
What do you think about what I've done so far?
Cursor
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I'm really sus of what I've done, but I don't know if I have the analytical eye to see the mistake
I feell like I might have issues in one of the coordinate transforms
or in the fact that my integral is not over curves?
Since others have not said anything, let me say some things.
What concerns me in the computations is that all the derivatives only make sense to specific parameters and yet you reinterpret what is a function of which in every line. At a bunch of places you implicitly assume that the solution curve can even be expressed in terms of the other coordinate. For example already in the second line, if you integrate from v_start to v_end = v_start, like in your actual questions you need to solve, you get zero.
This might be fixable somehow by using integration formalism for manifolds.
Unfortunately I am not fluent enough with differentiable manifolds to do that (or alternatively say for sure that it is unsalvagable).
Help me please with Problem 16 Chapter 4 Evans book PDE. It states to discuss the sense in which $u(\cdot,t) \rightarrow g $ as $t\rightarrow 0^+$ defined by $$ u(x,t) = \frac{1}{(4\pi i t)^{n/2}} \int_{\mathbb{R}^n} e^{\frac{i |x-y|^2}{4t}}g(y)dy \ \ \ (x\in \mathbb{R}^n, \ t >0) $$
using Lemma 2.
For context $u$ is a solution of initial-value problem for Schrödinger's equation $i u_t + \Delta u = 0$, $ u = g$ at $t=0$.
Lemma 2: Let $a \in C^\infty_c (\mathbb{R}^n)$ and suppose $A$ is a real, nonsingular symmetric matrix. Then
$$\frac{1}{(2\pi \epsilon)^{n/2}} \int_{\mathbb{R}^n} e^{\frac{i}{2\epsilon}y\cdot Ay}a(y)dy = \frac{e^{i\frac{\pi}{4}sgn{A}}}{|\det A|^{\frac{1}{2} }} (a(0)+O(\epsilon)) \ \ \ \ \epsilon \ \rightarrow0 $$
My work: I took $A=$ identity matrix, so $sgn(A) = \det A = 1$. Replaced $a$ with $g$ and $\epsilon$ with $2t$, multiplied both sides by $\frac{1}{i^{n/2}}$. So all in all I got:
$$ u(0,t) = \frac{1}{(4\pi i t)^{n/2}} \int_{\mathbb{R}^n} e^{\frac{i |y|^2}{4t}}g(y)dy = \frac{e^{i\frac{\pi}{4}}}{i^{n/2 }} (g(0)+O(t)) \ \ \ \ t \rightarrow 0 .$$
But this is not particularly helpful to discuss sense in which $u$ converges to $g$, furthermore $g$ is not necessarily compactly supported? I am not sure how to proceed.
Gigrise
I haven't studied this particular example, but I would expect the answer you're looking for is convergence in the sense of distributions
because the lemma holds for compactly supported Cinfinity functions (test functions), I think you should be able use it to show that for any test function phi, we have that <u, phi> -> <g,phi> as t->0
\begin{align}
\Delta p = 0&\quad \text{in } D=[0,1]\times[0,1]\
\nabla p \cdot n = 0 &\quad \text{ on } \Lambda_0\
\nabla p \cdot n = \gamma&\quad \text{ on } \Lambda_1,\
p = 0&\quad \text{ on } \Lambda_2,\Lambda_3.
\end{align}
How can i proof that a solution of this PDE does uphol conservation of mass i.e.
$$\gamma\cdot L(\Lambda_1)+ \int _ {\Lambda_2}\nabla p \cdot n \ dx+\int_{\Lambda_3}\nabla p \cdot n \ dx&=0$$
Because i know that the Laplace equation yields a solution with zero divergence, so it should conserve mass. But how do i actually show it here?
Enoo58
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Divergence theorem with div grad u = lap u.
do you mean like
$$\int_D \Delta p dx = \int_{\partial D} \nabla p \cdot n dx=0$$
I dont really see how that helps me
Enoo58
The left side is 0. For the right, split the boundary into the integral over the 4 sides and use the boundary conditions
yes then i would get the equation
$$\int_{\Lambda_1}\nabla p \cdot n \ dx+ \int {\Lambda_2}\nabla p \cdot n \ dx+\int{\Lambda_3}\nabla p \cdot n \ dx&=0$$
For $\Lambda_1$ i can apply the boundary condition, however for $\Lambda_2,\Lambda_3$ thge boundary conditions are dirichlet conditions and not neumann conditions.
Enoo58
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So leave those integrals as they are and apply on the first one
You'll get what you have written in the screenshot
Wouldnt that give me a condition when it conserves mass and not show that it does it?
Would it be possible to argue, if conservation is not uphold then p doesnt actually solve the laplace equation?
I think I got it:
Because p is actually a solution it needs to fulfill
$$\int_{\Lambda1}\nabla p \cdot n \ dx+ \int_{\Lambda2}\nabla p \cdot n \ dx+\int_{\Lambda_3}\nabla p \cdot n \ dx&=0$$
which in turn means
$$\int_{\Lambda1}\nabla p \cdot n \ dx = -(\int_{\Lambda2}\nabla p \cdot n \ dx+\int_{\Lambda_3}\nabla p \cdot n \ dx)$$
otherwise it wouldnt be. For some reason I was trying to argue the other way around. Would that be correct?
Enoo58
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Unrelated question. Why do we wanna extend Fourier transform to L2 space? Is L2 somewhat better than L1? is L1(R^n) contained in L2(R^n) and we just wanna be greedy or is there other reason?
Oh it got inner product, so this is probably why.
Yea L2 can be realized as a inner product. And the Fourier transform will be unitary on L^2. As a consequence of the Reisz thorin interpretation the Fourier transform will map Lp to Lq the conjugate exponent
L2 >>>> every other space precisely because it has an inner product
L1 is not contained in L²
However L1 intersected with L² is a dense subspace of L² since it contains smooth compactly supported functions/Scwhartz fucntions
Fourier transform on L1 does not have a nice inverse; there is no nice characterization of functions which are the Fourier transform of an L1 function
Ohhh the inverse, this is actually nice argument.
Generally L1 is not a very nice space. In every other Lp space (p finite), boundedness of a sequence implies that a convex combination converges in Lp (for p=infinity you still get convergence of a subsequence, but merely in the weak star topology); for L1 this does not hold (although you can still get a.e. convergence)
Studying sobolev imbeddings, what is the gist of it? Would you say they interesting by themselves or mainly as a tool for regularity theory? For instance to know that if you have a bunch of high order weak derivatives then you actually have low order strong derivatives? Is this the way PDE/analysis people think about these results?
They're mainly a tool, but yes some people do study then for their own right.
does the following PDE fall into any class of known PDES? $$\frac{\partial f(x,t)}{\partial t}= -a \frac{\partial f(x,t)}{\partial x} - b f(x,t)+b \delta(x)$$
ProphetX
delta = dirac delta?
This is just linear advection but with a funky source term
is there hope to be able to solve this analytically?
or only numerical approximations can be given?
Method of characteristics
You will also want to be careful about what you mean by "solve" (strong or weak sense) given that the dirac delta is not actually a function
how can I deal with Dirac delta there?
I think you can deal with it in the naive straightforward manner
You should try to do it yourself first, and keep in mind that the integral of the dirac delta over an interval is 1 if that interval includes 0
would the characteristic system be $\frac{dt}{1}=\frac{dx}{a}=\frac{df}{-bf+ b \delta(x)}$?
ProphetX
I think I've asked this before in the odes-and-pdes channel, but haven't gotten an answer and since I'm back looking at this book, I still can't tell what the "frequency expansion" is here. Is that just the square of the angular frequency? Is it a Taylor expansion or a linear approximation? Is the O term the error term (thinking almost like Big-Oh notation)? Maybe someone could help shed on this, probably pretty simple thing here?
It's a taylor expansion (and also a linear approximation, it's a first-order taylor expansion)
the O is the error term like you said
The next line is pretty tricky though. Trying to figure out what they're doing
Ok, I kinda get it now
Sort of dumb though
@golden kraken let me know if you want help understanding that last line, it's a little opaque
Hi, I'm looking for the general solution of a 1D heat-equation. Is there such a general solution that contains all the possible solutions without given the boundary conditions or any limits? Thank you
Thanks a lot!
I was wondering if there was a general solution to the PDE without boundary conditions though.
In $\bR^2$, a subset S has the property that locally, one of the coordinates is a smooth function of the other coordinate. I.e. for any $p \in S$, there exists $U \subset S$ open such that $(U,x,f(x))$ is a chart on $\bR^2$ and $f$ is smooth.
Now I want to prove that S is a regular submanifold of $\bR^2$.
MS
I need to show that for each point in S, there exists a coordinate neighborhood $(U,\phi)$ on $\bR^2$ such that $U \cap S$ is defined by the vanishing of $1$ coordinate
MS
So, take $p \in S$. Then, $p$ is in some chart $(U,\phi_1,\phi_2)$ for $\bR^2$. The idea is to consider the neighborhood provided by the assumption, say $V \subset S$ with coordinates $(x,f(x))$. Then I need to show that on $S \cap U$ we kill one coordinate
MS
isn’t this #diff-geo-diff-top territory
Thank you!
I’ll take a look at it sometime today and will let you know, thank you again 🙂
sure. if you're familiar with using big O notation, it just takes a bit of manipulation from there.
This image is taken from Chap 4.2 in Pazy. Why does the fundamental theorem of calculus work here in eq 2.3? Is u(t) automatically an absolutely continuous function?
I heard that the Navier-Stokes equation problem is solved in 2 dimensions, can someone recommend some text regarding this? The original paper would be fine, but preferably some recent exposition about it
Ladyzhenskaya solved the 2d problem
The Mathematical Analysis of the Incompressible Euler and Navier-Stokes Equations: An Introduction by Bedrossian and Vlad Vicol,
Vorticity and Incompressible Flow by Bertozzi and Majda.
They both should have the proof.
Yes, FTC still remains valid for functions defined on real line with Banach-values. The proof is the same as the real case
,tex Yeah, I think I need some additional hints, as while I have an idea as to what is Big-O, I haven't really used it. I get the general form from $ A sin(A) + A sin(B) = 2A cos({A-B\over 2}) sin({A+B\over 2})$ and while I get the angle in the cos term, I have the following angle in the sin term: $ sin({2kx + \delta k - 2w(k)t - \delta k w'(k)t - O((\delta k)^2)\over 2}) $. I'm assuming the $ \delta k x $ term vanishes due to the fact that there is already a $ 2 k x $ term and $ \delta k << k$.
volkip
yes! so what happen here is that you can isolate the important bit of A = kx - w(k)t, and then we need to understand the behavior of sin(A + O(delta k))
here im folding the O(delta k^2) into the O(delta k)
If you have sin(A + h) for any h, we know that |sin(A + h) - sin(A)| <= max |sin'(x)| * h by the mean value theorem (since the most sin can grow is by the max of the derivative times the interval length)
but that's just h, since max cos = 1
so in particular, if |h| <= C delta k for some C, then |sin(A + h) - sin(A)| <= C delta k as well. That's what it means to say that sin(A + O(delta k)) = sin(A) + O(delta k).
in your case, you still have that factor of cosine multiplying both the sin and the O(delta k): but that's bounded independently of delta k, so it doesnt affect the O(delta k) term. and the final result is what they list in the book
Thank you! I'll be reading and re-reading this until it makes intuitive sense. You can fold O(delta k^2) into O(delta k), since for a small dk, O(delta k^2) <= O(delta k), is that right? And also, what happens to the delta k w'(k)t term in the angle?
Yes
that's getting the same treatment. delta k + w'(k)t delta k - O(delta k^2) is all O(delta k), since k and t are fixed.
What should I read to learn more about the Laplace transform. I see deltas in odes.
Should I read about distributions?
Distribution theory are just propaganda
Schwartz space would suffice

Yes your intuition was totally right!
In general, why one need convergence in sense of distributions? whats special about it?
Schwartz space is a crutch
its kinda the natural notion of convergence when you work with distributions
I guess in your example, it may be the case that it doesnt converge in any Lp space
so convergence in distribution is a weaker notion
If I would like to ask something about SPDEs, stochatical PDEs. Is here the right place?
kk thx
And that’s specifically because u is a function of at least (x,t), that is x, t, and k are fixed and we get the u for those specific values? For some reason thinking of this as a wave makes me think t is non-stationary hahaha
you're just looking for solutions in a particular form here, so there's no real rules about what you can or can't do. it's just heuristics to look for a good form for the solution.
that's why they're doing all these approximations
so we are thinking of x,t,k as fixed for the purposes of letting delta k be small, just because it gives us a way of getting a nice form for possible solutions.
in reality, maybe they're all related.
Thank you for taking the time to explain🙂
Ok so this was a question on my pde midterm. We were trying to show that $E=|x|$ up to some constant is a fundamental solution of $\Delta^2$, and we are allowed to assume $\frac{1}{4\pi|x|}$ is the fundamental solution of $-\Delta$. We have the representation formula that $f=-\Delta(f*(1/(4\pi|x|))$, so to show $\delta_0=\Delta^2E=-\Delta(-\Delta(E))$ we just need $-\Delta(E)=\frac{1}{4\pi|x|}$, which by representation formula we just need $E=\frac{1}{4\pi|x|}*\frac{1}{4\pi|x|}$
Whoever
PV integral?
The convolution
Yes, the integral diverges, but does taking the pv help?
Wait is this with tataru
No
Ye
Forget convolutions in your last step and just show Delta(E)=c/|x| by a direct integration by parts argument.
Oh breh
I mean your idea was clever and there might be a nice way to complete that line of thought, but I am in bed half asleep so let's keep things simple 🙂
np, gl with it. you should be able to get it pretty smoothly from here.
What do you guys think are the necessary prerequisites to tackle PDE's by Evans
main one is be very comfortable with multivar calculus.
Some basic familiarity with pdes is nice
nice but I think the early chapters e.g. with the quick run through the 4 basic linear ones is a decent intro even if you have never seen a pde before
most earlier pde course are just gross and computational
I don't think evans explains very much intuition about why we care about pdes though
I am doing a DRP with an undergrad this semester and we're doing evans
And that was a lot of the questions they had
Anyways it depends on how far you want to get
I suppose, so many of the PDE come from such tangible physical phenomena though...I have not specifically lectured a first grad course in pde but I wouldn't expect motivation to be so hard to come by.
For chapters 1-4 being very good at multivar is the main thing
For chapter 5 and onwards, functional analysis
I took the only PDE's course my Uni offers. Like you mentioned it was gross and computational (and fun), but i think the last few weeks of the class grazed a bit of the topics mentioned at the start of Evans' book? Stuff like the heat kernel, d'alambert's solution, characteristic curves, etc.
My question is: My uni offers independant studies, and I was hoping to have mine centered around the text. Besides multivar, do you guys think real analysis I and II is necessary?
Once again it depends on how far you want to read
Got it. Thanks!
What is a DRP?
Directed reading program, essentially reading course with grad student supervising undergrad and very informal and for any credit
Oh that sounds cool
Anything specific from multi thats important? It's been a while since I've taken in it.
Everything
Lol
i tried doing evans over the summer and i got hammered by my bad multi background
didn't even make it to the fun part ;-;
The multivariable calculus is the fun part though
Gigrise
forgot the absolute value. all good
Why is a hypercontractive semigroup analytic on Re z > 0? I cannot find a ref nor concoct a proof (I think L.Gross said so in his log-sobolev paper on page 1070, if I did not misread)
What is hyper contractive to you ?
Like exponential decay ?
Or polynomial Lp-Lq decay estimates ?
Which one is your Def
According to L.Gross def it is contractive on L1(m), and bounded from L2(m) to L4(m) at some time T, m is Gaussian measure
so i guess it's the second one (i am not sure if i understood what polynomial decay means)
On L² most semigroups are holomorphic
Mostly for self adjoint operator
Then several Additional boundedness properties on Lp spaces allows to extend the result of holimorphy on those other Lo spaces
LP*
This is a consequence from interpolation theory
There is a scheme of proof in the book by El Maati Ouhabaz
Using Stein interpolation theorem
For a statment in a similar spirit such as the one you are looking for, Proposition 3.12 & Theorem 3.13 of Ouhabaz's book Analysis of Heat Equation, p.95 to p.97.
He even discuss a littlebit what happens for the case of Gaussian mleasure
(not that much relevant here, since he deals with abstract semigroup on general Lp spaces, not necessarily w.r.t. the Lebesgue measure)
S1lv3rB3ard
Any help would be appreciated.
<@&286206848099549185>
What does blowup configuration mean?
This is the context
A reference to read something is fine also
It means when you encounter some singularities in your PDE solution you do some rescaling to magnify that singular part and study its shape there.
A model example would be semilinear heat equation that were extensively studied by M. A. Herrero, Y. Giga, J.J.L. Velazquez, Merle-Zaag in the 90s.
Ty
wanted to know if perhaps the diffop
$$\frac{\partial}{\partial x} - \frac{d}{dt}\frac{\partial}{\partial \dot x}$$
has a name?
Tom
or if maybe the right term has one
In mathematics, a Lagrangian system is a pair (Y, L), consisting of a smooth fiber bundle Y → X and a Lagrangian density L, which yields the Euler–Lagrange differential operator acting on sections of Y → X.
In classical mechanics, many dynamical systems are Lagrangian systems. The configuration space of such a Lagrangian system is a fiber bundle...
found it here. it just didn't have it's own Wikipedia page
unfortunately it's too much for me to understand, but if anyone has intuition they have about this operator (Especially geometrically) id love to hear
Try deriving the Euler Lagrange equations, and it naturally pops out
Yeah ik that, that's how I got there.
I'm just trying to see if theres more to it
if you interpret the derivatives as finite differences and thus fractions, you end up showing that the Euler-Lagrange operator is itself 0
which makes me think that the operator is kind of like a commutator, in that it's showing how much the derivatives fail to commute
it makes me think it should be a very geometrical operator
Right so if you learn lie theory then a lot of this variational stuff can be recast in the language of lie groups
Via the hamiltonian pov
oh awesome. guess that's a goal then
any recommendations for books?
Hi.
I'm not so sure if this is the right place to ask, but I'm inexperienced with Sobolev spaces. I was trying to find out about $f(x,y) = |xy|^s$ (defined on the cube $(-1,1) \times (-1,1)$, for $s$ positive integer. I was interested in knowing for which $s$ this is in which $H^k$. I was hoping I could find something telling me $f \in H^{s+1}$ but not in $H^s$.
phao
Any directions?
Sobolev spaces have decreasing inclusion as the regularity index increase so your thoughts are not really correct.
If s is even, then |xy|^s = x^s y^s, which is a smooth function, so it's in any H^k of a bounded set
What about s odd? Start with |x|. That's in H^0. Is it in H^1? Is it in H^2?
Remember that in sobolev spaces we care about the weak derivative, not necessarily differentiability
Oh. Thank you both.
Yes, that question was wrong. Sorry about that.
I saw your responses earlier today and then took some time to review some of the things I had studied about sobolev spaces. I didn't have the $\vert \cdot \vert$ in mind, it was this other one: $u_s(x) = |x|x^s$, which is in $H^{s+1}$, but not in $H^{s+2}$ ($s$ non-negative integer, assuming Sobolev spaces over the domain $I = (-1,1)$). I was trying to get to, actually, $f_s(x,y) = u_s(x)u_s(y)$, but got it wrong.
phao
Hey I am trying to load in a matlab file focusing on the pennes bioheat PDE and im not sure if this is working
Hello guys, can you tell me how can we derive the following inequality from self-adjointness of $A$?
$$ | (A- \lambda)^{-1}| \leq C | \lambda|^{-1}$$
when $\lambda$ is in the resolvent set?
Mikahopff
By Lax Milgram for Lambda with positive real part lambda×u -Au =f admits a unique solution in D(A)
The estimate folkows from testing u against it self.
we can't, because that inequality is false. the LHS will generally blow up as you approach the spectrum of A.
Can anyone dumb down what a cauchy problem is
i learned it as solving a pde with no boundary conditions (d'alambert's solution, heat kernel, etc) but it seems deeper than that
Wait what ?
Notice that the inequality holds for A = Laplacian on L²
(of the whole space)
blowing up near the spectrum is not issue
(I assumed the operator is non-negative, of course)
He just said A is self adjoint. This fails for even the identity operator as the LHS blows up as lambda -> 1.
How is it not? This is an estimate in lambda. If the resolvent's norm blows up as lambda approaches some point in the spectrum then the LHS blows up but the RHS doesn't (apart from at lambda=0).
In fact we have $|(A-\lambda)^{-1}|=\mathrm{dist}(\lambda,\sigma(A))^{-1}$ from the functional calculus.
grobmez
My bad I am too used to the non-negative self-adjoint case and real part of Lambda non-negative
It does not hold for bi-sectorial operators right
The identity is still a counterexample .
I am confused then! Am I missing something here?
For $A$ self adjoint isnt the distance here be replaced by |Im(Lambda)| ?
if you consider the Laplacian this won't be true I think
Depends on how much of the real line is in the spectrum. Distance to real line gives a weaker estimate. Distance to spectrum gives equality, as I said.
This is true but not optimal
Yes, the estimate is asserted along rays, not on the full resolvent set.
yes, I meant the equality doesn't hold
And specifically rays avoiding the read line except the origin.
This is fine, and easy.
thank you, then I will give it another try.
Oh Okay @quaint herald I got it. It does not hold in general because the this not the full resolvent set, but only a sector of it
Really my bad
so the angle is encoded in the constant
Indeed, a sector away from the real line (cone point at origin) would suffice.
Yep.
But who do resolvent estimates without being ina prescribed sector ?
WHO ?
GIVE ME NAMES
I got another question about Riesz basis, since those are sequences ${ e_i}$ that span the whole Banach space and every element is written in a unique way as a linear combination of elements of these sequence. Can the elements of this sequence be not orthogonal?
Mikahopff
orthogonality does not make sense in general Banach spaces
Thanks you for the remark. I think it is replaced by the minimality right?
wdym by minimality? linear independence?
there are sets of vectors (viewed as subsets of the Hilbert space R^n, for n large enough) which are linearly independent, but not orthogonal
yes,
General Riesz basis in Hilbert spaces are an example.
Ignore above
Any experts on non linear PDEs and the KdV / Linear Schrodinger equation want to have a crack at this:
The notes I'm trying to follow relate to Example 1 from this webpage:
https://wikiwaves.org/Properties_of_the_Linear_Schrodinger_Equation
While I can follow for $u( x,0) = u_0 \delta( x)$ The way the problem expression is formed is throwing me,
SubsonicSpraak
is there an ode channel?
Does anyone know where equation 8 in Evans sec. 3.2 comes from?
In particular, with the first order ode $F(Du,u,x)=0$ and $z(s)=u(\mathbf{x}(s))$ where $s$ parametrizes a characteristic and $\mathbf{p}(s)=Du(\mathbf{x}(s))$ is the gradient along the characteristic, Evans then comes up with an equation 8 which states [\dot{x}^j(s)=F_{p_j}(\mathbf{p}(s),z(s),\mathbf{x}(s))]
守沢千秋
It is motivated by equation (6) and equation (7). If (8) holds then the terms with second order derivatives of u in (6),(7) match, and you can combine them then to obtain an equation without dependence on second order derivatives (under the auxilliary assumption (8).)
so (8) becomes the equation for x', the procedure in my previous para gives the equation for p', and finally z' is just computed by the chain rule giving you your complete characteristic equations.
Definitely. It is connected to / motivated by classical mechanics and the Hamilton-Jacobi equation.
If you have a Hamiltonian $H(q,p,t)$ you get a flow in phase space by Hamilton's equations. The action functional $S(q,t)$ (comes from integrating the Lagrangian over solution curves) then can be shown to satisfy the first order nonlinear equation
$$\frac{\partial S}{\partial t}+H(q,\frac{\partial S}{\partial q},t)=0 .$$
(Notice this equation is of the form that is treated by the method of characteristics and is almost the general such equation.)
From the definition of $S$ using the integral curves of the Hamilton vector field, we can see that restricting $S$ to these curves gives us an ODE, and this is why characteristics work.
For this mechanics setting, the integral curves satisfy $\dot q_j=\frac{\partial H}{\partial p_j}$ from Hamilton's equations which is exactly the condition you asked about.
grobmez
afaik thats usually known as higher integrability, since regularity is to do with differentiability
no it is used in Lp contexts as well.
The standard examples of functions in L^p but not in L^q for a q>p are powers |x|^-a for a in (q^-1,p^-1). However this is never strict in the sense that |x|^-a does still belong to L^(p+epsilon) for some range of epsilons. What would be a good example of a function in L^p but not in L^q for any q>p?
never thought of this before but im finding msyelf needing it
okay so i ended up solving my exercise differently and technically ive gotten such a function in the process but i have very little intuition for how i wouldve found such a function without the context of my exercise so im still open to suggestions of nicer functions
whoops need to adjust exponent slightly my bad
I claim
$$f(t)=t^{-1/p}|\log t |^{-2/p}\cdot1_{[0,1/2]} $$ is such a function.
For any $q\geq 1$ we can compute
$$|f|_q^q=\int_0^{1/2} t^{-q/p}|\log t|^{-2q/p}, dt .$$
Noting that $|\log(x)|\leq Cx^{-\alpha}$ for any $\alpha>0$ and sufficiently small $x$, we can estimate
$$|\log t|^{-2q/p}\geq Ct^{\alpha}$$
so our integrand dominates $t^{\alpha-q/p}$ for any $\alpha>0$. Certainly then integrability fails for $q>p$ by comparison with $t^{-1}$ at the singularity.
But $q=p$ our integral is
$$\int_0^{1/2}t^{-1}|\log t|^{-2}, dt=\int_{|\log(1/2)|}^\infty u^{-2}, du < \infty.$$
grobmez
In Evans' proof of Harnack's inequality, he asserts without proof the fact that for a set V such that V is connected and closure(V) is compact, we can cover closure(V) by a chain of finitely many balls B_i (with i in {1, ..., N} for some N) each of which has radius r/2 (where r was fixed earlier) and each B_i is not disjoint with B_{i-1}.
Why is this the case? i mean it seems obviously true but i'm not sure how to formalize my intuitions
(not sure whether to ask this here or in the topology channel, since it's a topological lemma for a pde theorem)
Note that B_i(x) for x in cl(V) is an open cover of cl(V) (as the sets are open and contains every element of cl(V) by construction) so as cl(V) as compact, we have a finite cover. Now each set much have non-empty intersection with atleast another set as otherwise the connectedness assumption is violated so we can enumerate the set so that Bi is not disjoint with B(i-1).
mmm the intersection graph is a connected graph duh
and then we might repeat some of the Bi but who cares
(The latter claim needs some refinement as I believe you would have that each set will have non-empty intersection with atleast two other sets so that you can build up Bi-1, Bi , Bi+1 and so on)
if you look at the graph where the vertices represent the open sets in the finite cover, with edge between two vertices if corresponding open sets intersect, then it must be a connected graph as otherwise you could take the union of connected components to separate cl(V)
once you have the connected graph you can just order them in whatever order you'd like and then in between each pair, insert a path between them
Okay yeah thanks I had a similar function in the end
another simple example comes from taking a countable sum of cut off power functions centred at the naturals with suitable exponents.
does this mean the support of said functions is contained within U? or can it just generally be a compact support with no further restrictions
it has to be contained within U
ok thanks, the part i was reading made me suspect that was the case, but it didn't seem clear to me by the definition given
when you consider it as a function on U it has compact support
are there any "weird" solutions to Laplace's equation in 2 dimensions, or does this proof simply not exclude the possibility?
Well the u in this theorem with say C=0 is bounded. Subtract this u from an arbitrary solution v and you get that the Laplacian of u-v is zero, i.e. u-v is harmonic. This means that arbitrary solutions to the equation differ from u by harmonic functions, and there are lots of harmonic functions that aren't constant.
However, any harmonic function that is bounded must be constant (Liouville), which is why this theorem is true.
yes, which means that once you have some bounded solution to -Laplacian(u)=f, it must be unique (up to a constant), since otherwise you can subtract the two solutions to get a bounded nontrivial harmonic function
and the proof above exhibits such a solution for dimensions n >=3
i'm wondering about the case of n=2
you still have a fundamental solution Phi (involving the log), but the convolution can be unbounded as per the remark in your screenshot.
oh sorry, i see the confusion, my initial question didn't ask what i meant to ask
what i wanted to ask was if there were any weird *bounded solutions
Sure, I mean take any smooth compactly supported u you like and then define f to be it's negative Laplacian. Then you have such an equation with a bounded solution. There would be some functional analytic characterisation of which f in C^2_c have this property too.
If the comparison principle can be applied to a semilinear PDE, i.e. the nonlinear part is lipschitz, terminal is square integrable and the other condition is satisfied, could we then also apply the maximum principle?
What are the subscripts and nu and sigma here? More importantly, how are they bringing Delta H?
Merely using Youngs should get you
[ C(\lVert Au \rVert_{0,2}^2 + c ( \lVert H \rVert_{1,2}^2 + \lVert H \rVert_{2,2}^2) \lVert \mathrm{curl,} H \rVert_{0,2}^2) ]
first by applying Youngs on (A) and the remaining and then on the terms in front of curl.
cocat
Of course, we can adjust for the coefficients in front of the norms provided I know where the second term comes from
A derivation on Formula ( 3.6 ) of this paper
Thank you
I continue to think according to your ideas.
I dont wanna read the entire paper, if you can figure out how they bring the Delta, then that would be good. Otherwise, the idea spelled above should be sufficient for your purposes.
PYZ
PYZ
PYZ
In that case, just do the procedure as mentioned above and then finally add the |H|^4 term which is fine because it's positive
Thank you very much. You are really a genius.
Do you have any other math problem exchange platforms? I have many questions that I haven't figured out where to ask
math.stackexchange
thank you
Magnetohydrodynamic ❤️
Might have to start learning this...
My advisor wants to get into plasma dynamics
Everyone around me is going compressible 
I am going to plan to check free-(rough)boundary compressible Hall-MHD at some point
in 1 or 2 years the time I and someone else build a sufficiently efficient functional analytic framework
(based on my PhD Thesis mostly)
Check out Jin Tan's paper for weak solutions via Galerkin type methods.
very good paper
à la Leray type solutions for compressible Hall-MHD.
Okay
Sounds useful
I will care about shock formation and singularities and such so understanding the weak existence theory is important
I have this solution of a PDE problem: https://imgur.com/a/GHpYOzd
I don't understand how they can make c equal to 0 only on one side of the equation. Can someone enlighten me?
It's a typo I would think as they later onwards just identify x(t) by x.
I think that might be it
I have another question regarding this other solution.
Where did 1/z(0) come from in that solution to the differential equation?
Looks like they just took the constant from the solution of the antiderivative and made it equal to 1/z(0) or something. But why?
The boundary condition from integrating the left side. Also for such question, use #odes-and-pdes
what do you mean by "the boundary condition"?
How do I come up with a Lyapunov function for f(x,y)=(2y^3 - x^5, -x-y^3+y^5)? I'm getting really lost. Is there a standard way of finding one? I think that the critical point (0, 0) of the ODE (x', y')=f(x,y) is asymptotically stable since numerical solutions plotted near that critical point converge to it.
I tried expressing g(x,y)=L_{f(x,y)} Q (directional derivative of Q:R^2 -> R in the direction of f(x,y) at (x,y)), and then computing the derivative of g to try and find Q such that g is negative definite in a neighborhood of (0, 0), but I am getting nowhere.
You're integrating over s from 0 to s
How did you learn the finite element program for magnetohydrodynamic equations
Please don't post your question in multiple channels
okey
yoo damn
Is my solution to this PDE problem correct? https://imgur.com/a/98Lh0XP
I really am not sure if my approach is correct or not and I would appreciate if someone would help me find if my solution is valid or not.
Question regarding fractional sobolev spaces defined through FT and distributions, I would like to formally understand the following definition
$W^{s,p} = { u \in \mathcal{S}^\prime , \vert , \mathcal{F}^{-1}((1+{\vert \xi \vert}^2)^{s/2}\mathcal{F}(u)) \in L^p}$
I don't understand how $(1+{\vert \xi \vert}^2)^{s/2}\mathcal{F}(u)$ is meant, if it meant as a distribution thus as
$\mathcal{F}(u)((1+{\vert \xi \vert}^2)^{s/2} \cdot \varphi)$
It doesn't work cause $(1+{\vert \xi \vert}^2)^{s/2}$ isn't smooth enough. The only way to understand it from my perspective is, if we assume, that $\mathcal{F}(u)$ is an integrable function for some p or that $\mathcal{F}(u)$ is measurable and it defines with the mutplier a solid distribution. So how is this definiton meant to be read?
KIl
shouldn't the p be mapping to $\mathbb{R}$ instead of $\mathbb{R}^2$? If so then it look alright if you have the correct differentiability assumptions on u and p
KIl
What do you mean when you say that $(1+|\xi|^2)^{s/2}$ is not smooth enough? Isn't it $\mathcal{C}^\infty$?
4453
Don't worry about it, it happens.
yes you are right it is mapping to $\mathbb{R}$
xbr
In fact Bessel potential of any order s preserves the Schwartz class and is continuous w.r.t to the topology on the space made of Schwartz functions. In particular by duality it preserves continuously the class tempered distributions.
Thus this ask you if for a tempered distribution f, you can represent the tempered distribution (I-∆)^s/2 f by a Lp function
(Representation theorem for duality of Lp spaces)
Ok then another question maybe you know this, the fractional sobolev space (via Gagliado-SemiNorm) or the bessel space (through Bessel potential), for both of these spaces when do I know that the fractional Lalplace is defined (mutplierer with |xi|^s in FT) besides the case where p = 2?
I think usually you just check if the multiplier is bounded in Lp (defined on a dense subspace with bounded extension) and for that a sufficient condition is the Mihlin-Hormander multiplier theorem.
Exactly what Coat said
But for Bessel potential spaces you define it through the tempered distribution stuff
Then you can work with the formulation to show that, when s is non negative, your tempered distribution, whose image under the Bessel potential is represented by an Lp function, is then also an Lp function itself.
Ok great but no general statement known for it?
ah hell yeah thanks thats the kind of definitions i wanted thank you so much
its so much chaos if you try to get some info about fractional sobolev and laplacian without much headaches
Is there a Lyapunov function for the critical point $(0,0)$ of $\dot{x}=2y^3-x^5$, $\dot{y}=-x-y^3+y^5$?
Beous
Cause numerical solutions make it look like it's asymptotically stable.
but this thing feels impossible to find
Still have to write a conclusion, add equation numbers, and clean some stuff up like grammar and punctuation
Please tear me a new one
I think my section on method of characteristics is a bit lacking I dont have time to go deeply into the concept
and add a bibliography
Maybe im tripping but isnt this false? Feels like we need a uniform bound on the measure of the complement of suppu here. If it is in fact true please don't give me any hints since this is a assignment
Just want to make sure there isnt a mistake
This heavily true and a fudnamental result in pde theory, geometry, spectral theory, and many other realted subfields
Okay i figured it out
the issue was that i was trying to relate things to the version we had seen in class (|u-u_Omega| instead of u) which cant even work if the domain isnt Lipschitz anyways, and even if it was I could only figure stuff out that needed uniform bounds as mentioned above
but turns out it's just a simple IBP+Holder
This one is Poincaré(-Sobolev)-Wirtinger inequality
The one you have shown before is the Poincaré(-Sobolev) inequality
A thing to note is that the main counterexample are the constants. Both try to just weed this counterexample out: either by requiring mean 0 or requiring vanishing at boundary
yeah the moral of it is clear to me
thanks a bunch
in fact the minimal constant C reflects some aspect of the geometry of the domain Omega.
more precisely, it is intimately related to questions of isoperimetry.
What is their definition of unconditional stability?

