#advanced-pdes
1 messages · Page 8 of 1
tryingmaths
dominated convergence i guess..
the proof here assumes specific conditions upon f
for simplicity, but i'm wondering whether or not the proof works for any f in general
you can give a sense of this formula for f to be any L1 loc in time with values in S' (tempered distributions)
in particular f in Lp(R_+xR^n)
for any p
And for super fancier fucntion spaces
does the discussion that leads up to (12_s) also work these f as well?
For now you shouldn't concern yourself with full generality but merely learning the method. Pde theory becomes very technical once you start generalizing over basic assumptions
i see, also in my case the domain is a wedge of a unit circle, how does the regularity change with the angle?
i’m working with Poisson’s eq
u(r,theta)=(1+r^2)r^b sin(b*theta)
where the max angle is pi/b
Because of the r^b. Upon being hit by derivatives this function becomes singular at the origin generally.
ok got it
so if i had non convex wedge, like b<1, would the solution be in H^2?
man FUCK greens functions
the professor wants me to use the greens function representation and this is making me sad

is it more complicated to do this by greens functions?
nope, because r^(b-2) will blow up faster than r^(-1) which is not in L^2.
i see that makes sense. since u_{rrr} (third derivative) is only in L^2 for b>2, does that generally mean that u is only in H^3 (or higher) in (0,pi/2)?
since b<2 means the angle is greater than pi/2
its kinda interesting how that plays out then, u in H^3 for first quadrant, u in H^2 for second, u in H^1 for third
yep
well your function is changing, it's more about how singular your func is at the origin, which involves b in a very explicit way.
Did you actually try to go through the proof of the mean value theorem and see what modifications are needed?
the professor said to try using green's functions
In that case first start by calculating the Greens function for a ball of radius r
Actually Evans provide the expression in the next few subsections
for the unit ball
not for a ball of radius r

i assume its basically the same though
Yes, but there will be some changes involved. Try going through his proof and derive it for a ball of radius r.
Actually he gives it for ball of radius r as well
is this just turning the point dual to $\frac{rx}{|x|^2}$?
the breadwave
i guess i now show that $\int_{\partial B(0,r)} g(y)\frac{\partial G}{\partial \nu}(z,y) dS$ reduces to mean value of g around the boundary
the breadwave
(z goes to 0)
im just gonna assume this is true and the rest is ez
Hey guys, do you know if there is any general method that can allow me to investigate the asymptotic behavior of an ODE (at infinity)? Thank you.
Does this sound like a good motivation for studying Schauder estimates? It's just for myself.
We'd like to solve elliptic PDEs by the method of continuity, which require a priori estimates (and so we want to consider strong and not weak solutions). But we'd also like some form of compactness, which is why we need the Holder norm (so we can apply Arzela-Ascoli).
You won't get a single "general method", but it's basically the same thing as finding asymptotics of integrals. Tools like stationary phase, method of steepest descent, Watson's method etc are the basics.
For instance these can give you the classical asymptotics for special functions like Bessels in the various regimes.
(Perhaps I am misinterpreting your question, and you are more interested in geometric things like say a smooth flow on a noncompact mfld "at infinity". If so, please clarify.)
Sounds like these are what I want, but honestly I don't know much about those, so maybe I will look them up first, thank you!
Hi, I was wondering if anyone had any insight into a particular PDE I've been looking at which is of the form $z_{xx}\beta''+z_{yy}\alpha'' = 0$, where $\alpha$ is a function of x and $\beta$ is a function of y, both of which are periodic. I have studied this PDE for a while because of its physical relevance and have been able to derive about 4 types of solutions. However some of these solutions I feel I could have gotten to quicker if I knew more about fourier analysis and I'm wondering if any insight could be gained by doing something like fourier transforming the equation or if there are other integral transforms that could help me study it.
pewpew2385
You might like Olver's book: Asymptotics and special functions. I mostly cobbled together knowledge of this stuff from various sources like lecture notes (I recall a pretty nice set from Cambridge), but this book seems pretty detailed and has a view towards asymptotics of ODE solutions as you desire.
Do you have any assumptions on the sign of Beta’, alpha’, beta’’, alpha’’? If you do you can use theory from second order elliptic/ hyperbolic pde depending on these assumptions
Found them. These notes are quite compact and cover the basics. Of course the Olver book is more comprehensive.
@quick pagoda what is the meaning of the stare?
As a
kind of “I will note this down as a book I was unaware of”
I knew of it but I literally opened it for the first time about 2 mins before making that post :p
just browsed to the ../pure/analysis/asymptotics/ subfolder of my textbook collection, 99.99% of which I never have opened/never will open.
mood, I definitely have a few hoarded texts
Not quite that many to need sub that many subfolders, including one just for asymptotics, yet though
20g textbooks folder and 0.7g papers folder needs some amount of organisation haha.
it's a bit suboptimal but whatever, not very important
I’m only at like single digit GB 
Clearly gotta step up the hoarding game and grab the books I have on a to-do list
Haha my collection had a big head start as it was built off a massive torrent I grabbed as a UG many years ago. High proportion of useless books, but some good ones in there and a nice organisational structure that I built off.
Also for special functions there is an online database dlmf.nist.gov
It's got cool classical things like the Ramanujan notebooks, classic papers, old tripos exams, essays like mathematicians apology, mathematicians miscellany
Yes, of course the database is absolutely the best place to look up specific asymptotics for known special functions, he was asking about learning things like the asymptotic methods though.
stationary phase etc
Yes yes just wanted to plug it for people interested
yeah that db is super useful, has definitely saved me some elbow grease
Ah a lot of cool stuff but maybe not stuff of particular use or interest. Mine is mostly inflated by books I’ve grabbed as a possible reference to whatever specific topics, or especially padded around stuff I care about
yeah of course. everything I have added to this collection since then (which has accrued to be quite a lot by now) has been of this type
But even the other stuff has some uses, I occasionally mine old obscure books for problems when lecturing for example.
Random papers from the 70’s have a lot of random useful results
That's a good question. I have really allowed the case where they can have either sign. Initially when I studied the problem I looked at it from the standpoint of elliptic/hyperbolic, but because the coefficients are periodic, the discriminant of the PDE is nearly always mixed and alternates between hyperbolic and elliptic over the entire domain. I sort of abandoned that approach because of the difficulty is trying to glue together these different regions. The most important solution I've found is
$z = \alpha(x) \beta (y) - \int_{x_{0}}^{x}\int_{x'{0}}^{x'} \alpha (s) '' \alpha(s) ds - \int{y_{0}}^{y}\int_{y'_{0}}^{y'} \beta (s) '' \beta(s) ds$ due to the fact that in general, the fact that alpha and beta are periodic will allow for the integral terms to have a constant that is integrated twice, producing a quadratic source term. But I got kind of lucky finding this and needed to figure out how I could have figured this out with a more powerful approach like fourier transforms, harmonic analysis.
pewpew2385
How familiar are you with functional analysis?
@cobalt terrace My knowledge of it is pretty weak, I'm sure it will be better in 2 semesters though. But anything to guide me in the right direction would be nice. So far I have only gotten any of my results by using fourier series and just doing harmonic balancing to find my solutions. I'd prefer not to do that again to find my answers because its too involved when you have a double Fourier series you need to balance terms for.
I was reminded of methods that run under the general umbrella of "Floquet theory" or "Bloch theory". This even works if $\alpha$ and $\beta$ depend on both $x$ and $y$ (but with the same periods). The idea is that while the solutions of the equation are not going to be periodic, one can show that every solution is an integral over solutions which are "periodic up to a phase shift" in the sense that there are numbers $k_1, k_2$ depending on the periods of $\alpha$ and $\beta$ such that $z(x, y) = \exp(\mathrm{i}(k_1 x + k_2 y)) u(x, y)$, where $u$ is a periodic function with the same periods as $\alpha$ and $\beta$. But maybe this is not useful...
wolftoeter
Did you already consider to seperate the variables, i.e. $z(x, y) = v(x)w(y)$?
wolftoeter
@cobalt terrace I think you are probably right. Someone mentioned this to me before awhile back and I forgot about it. I had read into it a bit but felt it was a bit out of reach for where I’m currently at, but maybe I need to just take the timr to really try to understand it. It will probably help to understand the problem.
I did try separating variables and that is useful because you can get periodic solutions under some conditions. For example if both functions are cosine, you just have to solve two mathieus equations.
this is from evans
how did they take the derivtive if u wrt to t?
is it by chain rule or something?
In calculus, the Leibniz integral rule for differentiation under the integral sign, named after Gottfried Wilhelm Leibniz, states that for an integral of the form
∫
a
(
x
)
b
(
x
)
...
ok nice thanks
Dose some one have any reference for maximal Lp-Lq regularity for stokes operator. In particular I need something like this, $u'(t) + Au(t) = \textrm{div} (f)$ where $f \in L^p(0,T ; L^q(\mathbb{R}^n))$ where $A$ is the stokes operator
Math&Tea
Can someone suggest me a good book on PDEs where I can get the topics like, "Homogeneous Wave Eqns, Vibration of Finite Strings with Fixed length, Nonhomogeneous Wave Eqns," etc. Till now I've been studying the book Linear Partial Differential Equations for Scientists and Engineers by Tyn Myint -U and Lokenath Debnath but the explanations or the language of the book seems horrible imho. As for my background, I am an undergraduate student pursuing a Bachelor's degree in Mathematics. Now, coming back to my issue, it seems the syllabus of the course in our university is directly designed using the book I mentioned. So, if the recommended book that has the same sort of contents as this book, then it'll be very helpful in my case.
Look up for papers by Ken Abe. He has some results for Stokes operator
Thanks I will take a look
Evans should be sufficient
Assume $u \in L^{2^*}(\bR^N)$ and $\nabla u \in L^2(\bR^N)$ where two star is the sobolev exponent. I have $\varphi_R$ a mollification of $\varphi$, a smooth function with compact support. How can I estimate $\int_{\bR^N}|u\varphi| | \langle \nabla u,\nabla \varphi_R\rangle|dx$? Also, is this correct $$|\nabla (u\varphi_R)|^2 \leq |\nabla u|^2 \varphi_R^2 + |u\varphi_R| |\langle \nabla u,\nabla \varphi_R\rangle| + u^2|\nabla \varphi_R|^2$$?
мир
Ok, I will try to estimate $$\int_{\bR^N}|\langle \nabla u,\nabla \varphi_R\rangle|^2,$$so that I can Use Holder's inequality. Indeed, using Cauchy-Schwarz $$\int_{\bR^N}|\langle \nabla u,\nabla \varphi_R\rangle|^2 = \int_{supp \nabla \varphi_R}\norm{\nabla u}_2\norm{\nabla \varphi_R}_2 < \infty.$$Does this work?
мир
Here the inner product is just the dot product?
where is $\phi$
Yes
It is varphi
[ \int \lvert u \phi \rvert \lvert \langle \nabla u , \nabla \phi R \rangle \rvert \leq \lVert u \phi \rVert{L^2} \lVert \langle \nabla u , \nabla \phi R \rangle \rVert{L^2} \leq \lVert u \rVert_{L^{2^\star}} \lVert \phi \rVert_{L^q} \lVert \nabla \phi R \rVert{L^\infty} \lVert \nabla u \rVert_{L^2}. ]
cocat
one remark: you used Holder to start with but we (at least I) did not know if the inner product of the gradient of u with that of phi_r is in L^2
It is as shown in the last inequality
then I see that it is because you just use the fact that the gradient is still smooth with compact support and the gradient of L^2
of u is in L^2
yeah indeed
thank you
WTH what is this 💀
I'm in the first semester
When I see this, I don't know if I want to keep studying.
😭
yes but to apply holder one would need that varphi is in some Lr space? I meant to ask that? was it in some Lr space
varphi is smooth with compact support, hence in every L^p
ok, I miss understood then, I though you were emphasizing that varphi_R where smooth,
and they are
how exactly do you bound the inner product? I am sorry for being picky with the details
We have $$\int |\langle \nabla u,\nabla \varphi_R\rangle|^2.$$Do you use Cauchy-Schwarz? Because it seems like you just did $$\norm{\langle \nabla u,\nabla \varphi_R\rangle}2 \leq \norm{\nabla \varphi_R}\infty^2\int |\nabla u|^2$$
мир
At first I could restrict the domain of integration to the support of $\nabla \varphi_R$. Since it will have compact support I could use Cauchy-Schwarz so that $$\int |\langle \nabla u,\nabla \varphi_R\rangle |^2 \leq \norm{\nabla u}_2\norm{\nabla \varphi_R}_2|supp \nabla \varphi_R|$$
мир
Cauchy-Schwarz for vectors
Yes basically that's it
But that's not cauchy-schwarz? You would need the 2 norm on \nabla varphi_R?
Wdym?
I meant bound the inner-product via Cauchy Schwartz then bound the integral by just taking the Linfty norm out
Precisely, like this then
You can also just take the Linfty norm out and that's enough
But you get $|\langle \nabla u, 1 \rangle|^2$ and this seems different than the 2 norm of nabla u
мир
No, first use Cauchy-Schwarz to get the 2-norms of both and then take the Linfty out.
Here the 2-norm is the sequence norm
The Linfty is the Lp norm
I see
Ohhhh it's here
I am given this problem, which I have to solve for its generalized form (i.e. p instead of 2)
I've solved everything except the equation
specifically I think I need an inequality to help, but I don't know how to obtain it
I'm trying to go throw the first variation
But I really don't know how to go from here |Du + eDv|^p to |Du|^p + e |Du|^(p-2) <Du, Dv>
A colleague of mine asked chatgpt
it's just the first order approximation of the function e -> |Du + eDv|^p
ok this is like way out of my league but ok 😂
so like recap
we are trying to solve the PDE
du/dx + du/dy = 1
PDEs need to be given an initial condition
why do they 'need' it?
or, how do they 'need' it
cause just like how an ODE determines a solution only up to a constant
a PDE determines a solution only up to some “boundary condition”
but you can still get a family without it? no?
in this case our boundary comditioj shall be
so it doesnt need it we're just solving for a unique solution?
it needs to be specified where you are prescribing the boundary condition
in our case let’s take u(0, y) := f(y)
i.e. we prescribe the initial values along the y axis
And i claim this uniquely determines the solution to the pde
to see this, define for each real number z
the curve c_z: R -> R^2 as i described earlier
u is the vector function we're solving for, and we're choosing x=0 which somehow is an initial condition? not sure i follow
we are trying to solve for u
god said
and u is a vector function right
takes in a vector in R^2, spits out a scalar
u takes in a vector in R^2 and spits out a scalar?
god said, (this is part of the initial problem) that along the y axis
who is god
along the y axis
so basically like f(x,y) right?
yep
yep
we trying to solve for that
God said that in this problem
u(0, y) = f(y) for some given function f
i claim that just given this f
i can uniquely determine a solution to the whole PDE
god gave us only the values on the y axis
now i will extend it to the whole domain and in doing so solve for u
oh no orion is here
💀
How do u mute seriously i forgot
bro thought he could escape
if u is our solution, c_z seems like a random vector function?
what is it, and how did you determine it?
c_z is like a family of limes
lines
that i just pulled out of my ass
I defined it
oh lol
one line for each z
gotcha
it starts at (0, z)
yep
so now the magic is
g_z’ = c_z’ (du/dx, du/dy)
= 1
so we can solve for g_z exactly
clearly g_z (t) = f(0, z) + t
so if you plug in t=u
then the derivative of your space curve c_z(u) is 1
indeed
does that work for any family of space curves you pull out of a hat?
how 😭
because of the form of the pde
should i just accept this XD
well the pde says that du/dx + du/dy = constant
so clearly this says that the derivative is constant along straight lines with slope 1
“clearly”
clearly if u already know the method xD
😂
but if c_z'(u) = 1
d/dt c_z (u(t))
alr
huh
just plug in the definition of c_z
c_z(t) = (0, z) + t(1, 1)
c_z(u) = (0,z) + u(1,1) = (0,z) + (u,u)? im not understanding...
uh
u \circ c_z (t)
yeah
nty
u(c_z(t))
yea
sorry notation is hard on discord
wait i need to rederive how it was 1
use latex
right so
(u(c_z(t)))' = 1
how did we know this?
g_z ‘ = (du/dx, du/dy) \cdot (1, 1)
just calculus
multi variable calculus
to find the derivative of a composition
g_z is the gradient dot with (1,1)?
yep
oh i see
you compose the derivatives of each component
ye
thats how du/dx + du/dy = c
this was the original defining pde
yeah
du/dx + du/dy = 1
so if we plug that in
g_z’ = 1 as we desired
and now you can backsolve for u
g_z = f(0, z) + t by our derivation
but also g_z (t) = u (c_z(t)) = u(t, z+t) by definition
so that u(t, z+t) = f(0, z) + t
i feel like im missing something 😭
oh.l
g_z is the function g_z’ is the gradient
well we can compute g_z’ = (du/dx, du/dy) cdot (1,1) right
and c_z(t) you pulled out of a hat
uh
this is just du/dx + du/dy
which is 1 by our defining pde
we can compute (du/dx, du/dy) . (1,1), but how do we know thats g_z'?
g_z is
wait
u \circ c_z
oh a vector c_z(t) is inputted into a function of two variables (or a function of a vector) u(x,y)
g_z = our solution u(x,y)
g_z is not ur solution
oh
g_z is u (c_z)
ohh
or as i like to write it more unambiguously , u \circ c_z
its our random vector inputted into our solution
Indeed!
along the curve which we think of as parametrised by time t
differentiate this to find that u changes along the curve by 1
per unit time
right...
and then you can extend the god given values of u on the y axis
To any location in R^2
That’s the method of characteristics in a nutshell
We end up getting u(t, z+t) = f(0, z) + t
g_z = u(c_z)
so somehow, a random vector inputted into our solution is the gradient vector.
do we know this BECAUSE its a solution to the differential equation?
no,
we defined g to be that
and then differentiated it and plugged in our pde to find that g_z’ = 1
and then used that to backsolve for u
now if you want a solution in the form u(x, y) = something
change variables
t -> x, z -> y - t
we defined g_z to be the gradient? or we defined g_z to be u(c_z)?
latter
u(x, y) is not known to us yet
we are trying to solve for u(x, y) for general x, y
that’s what it means to solve a pde
ahaha
💀
fr 💀
but i think u can read evans ch1 now and have a decent time
alr
Thanks for listening to me rant
these results all follow from convex analysis? I haven't done any convex analysis so im not sure
uniform convexity for the continuity for all but at most countable x and strictly convex would imply uniqueness?
i can post context if needed
Non decreasing is what they used for continuity up to countable set
This is true for all monotone functions on R
@azure frigate
ohh im stupid thanks
Rotta
Compile Error! Click the
reaction for more information.
(You may edit your message to recompile.)
I am trying to do this exercise.
This of course gives that there is some x_0 in Gamma and a sequence x_n in P so that x_n converges to x_0 but I can not move from there to show the existance of some ball around x_0 on which u >=0
Expand out nabla u dot nabla u
Could you elaborate more?
Evans PDE C2 theorem 3
Rotta
This is a great problem. One approach is to enlarge your domain slightly near a point p on the boundary portion where we have vanishing. Consider the extension of u by zero on this enlarged domain \Omega'. Using the fact that u is harmonic you can show the extension v is harmonic (some work is required here, but not much). Then you are done by analyticity in the interior.
I don't know of any simpler way, in particular it is not clear to me what cocat's intended solution was. If you have trouble showing v is harmonic, I can give additional hints.
just done this with the equivalence of weak harmonic with harmonic
fantastic
Didn't get what cocat was hinting to either
sounded like the standard energy estimate way of showing that dirichlet and neumann data vanishing everywhere implies u=0.
but ofc we don't have that.
My initial idea was a bit complicated I guess and I could not finish it anyways.
yeah unclear to me how to make that kind of idea work.
This is $h(x, y) = \nabla h(x, y) \cdot (a, b)$. Fix $y$. Along curve $z(t) = h((0, y) + t(a, b))$ we have $z'(t) = z(t)$, so $h((0, y) + t(a, b)) = e^{t}h(0, y)$.
L
I see
does 1d anisotropy makes any sense, since anistoropy usually indicates the difference of behavior accross different axes
I'm trying to derive the Poincare Wirtinger inequality for the case H1_0 under the interval [-1,1]
I'm not sure if it's possible to go through Euler Lagrange
by this theorem, we know that the functional with lagrangian f(x,u,u') = u'^2 - pi^2u^2 has a minimizer call it uB for u bar = \overline u
Would it be possible to prove that uB is in H^2_0 and so through the E-L equations obtain the class of minimizers and the inequality?
I know for part b I should consider phi squared, but is the fact that the characteristics line “collide” prove that the solutions don’t exist in a classical sense? Or do I need to argue more
if anyone could help I rlly appreciate it!
Let $G(x,y)$ be Green's function on $\Omega$. Let $f$ be a bounded integrable function on $\Omega$. I was trying to prove that $\int_\Omega G(x,y)f(y) dy \to 0$ as $x \to \partial \Omega$. I could solve it using generalized DCT and weak Lp convergence. But I was thinking about something else. If $f$ were continuous, then we know that the integral satisfies the Dirichlit problem $\Delta u = f, u = 0$ on $\partial \Omega$. So the result holds trivially when $f$ is cont. Is there a way to carry some approximation argument and prove it for integrable $f$?
ru0xffian
Mollify f then study the difference of G mollified f and G f
Indeed: more precisely, there will be two characteristics propagating different values. To get a picture of this, check Evans Page 140.
Oki will do, thank u!
I haven't checked it for your case but most likely if there's an issue it would be like this.
oki oki
22
Does anyone know why the author does this step?
this is the setup and, the thing I'm confused about in a proof relating this is:
I'm confused about, why can't we a priori differentiate g wrt epsilon?
differentiating g wrt epislon is no problem, since epsilon -> g(x,epsilon) is C^1. But the point is that passing the limit epislon ->0 into the integral requires justification. So the point is you use DCT, and to get the upper bound on the difference quotient for g you naturally use the mean value theorem
sure, but why use the MVT?
Since g is C^1 wrt to epsilon, and pointwise in x, all of the arguments are C^1 functions in epsilon
doesn't the chain rule already imply
$g_\epsilon(x,0) = f_u(x.u,\nabla u) \varphi + \langle f_\xi(x,u,\nabla u);\varphi\rangle$
Trivial Lemma
Both of those functions are L^1 by Cauchy-Schwarz + (H3) + Young's inequality
So there's absolutely no need to do all this magic, innit?
or do we need it to prove the first line to the second?
exactly this, the DCT is needed to pass the limit into the integral
and do apply DCT, your 'dominating function' has to dominate the converging sequence, not just the limit
the converging sequence here are the difference quotients g(x,ep) - g(x,0) / ep, which you need MVT to estimate
can't I estimate them using the first order taylor series expansion at eps = 0? With an o(e)
so like g(x,e) = g(x,0) + [the chain rule]e + o(e)
since o(e) is in O(1) and Omega is bounded, it would follow right?
just feels more convoluted to me to use MVT*
Anyway, thank you in any case ^^
MVT is precisely taylors theorem with the remainder form, in the case 'k=0' where k is the degree of your polynomial
so its just identical
but from a moral standpoint i would prefer to call it MVT haha
could anyone give me a hint on this? I wrote it out using the definition but just struggling to find the right bounds..
Hint: duality.
(and this is the hint for most things you prove about distributions).
sorry i dont follow
Prove a related statement about how the FT acts on a convergent sequence of Schwartz functions, and leverage this to get the tempered distribution result for free.
how do you check whether $\hat{g_n} \to \hat{g}$ in the sense of tempered distributions?
L
<Fu,v>:= <u,Fv>
where F is the Fourier transform
u your tempered distribution
v a Schwartz function
reviewing for exam, and im not sure how to do part 2 of this problem, help wouls be appreciated thanks
Ok I think I got it, thank you!
I think you need to differentiate the integral, conmute the derivative with the integral, do chain-rule and replace u_t with -a . grad(u), then integrate by parts to use div a = 0
yes thats what i tried, but i couldnt get it to work, couldnt get diva
it works if we're integrating u but here we're integrating u^2
Do you get div(2ua)?
yes
Use product rule: you should get an integral that has an opposite sign than a previous step
sorry wdym, use product rule on div(2ua)?
Yes, div(2ua) = 2 grad(u). a + 2 u div(a)
but then grad(u) is nonzero
oh I just realized that I could write grad(u^2)= 2u grad(u). Is that what you mean?
I mean, you can. I was saying that, at some point, your integral reads -int( 2ua.grad(u) ), but after integration by parts and product rule it reads int( 2ua.grad(u) ). That suffices to conclude the integral is zero
(I was implying we did the same steps, my bad)
sorry, I dont get why that suffices to conclude the integral is zero. I thought we only know that u vanishes outside a compact set and that div(a) = 0. Could you elaborate?
A number is both nonnegative and nonpositive so it must be zero A number is equal to its opposite, thus zero. Whoops
Does anyone have a maths server about PDEs or maths in general that has an active VC?
It might not be the best channel so excuse me
Just said maybe some PDEs lovers here might recommend a server
Yes precisely: agrad u times u = a dot grad|u|^2/2 then IBP and Divergence free
oki, that’s what I did! Thank you
❤️
so for part a, i think i need to show that $u_xu_{xt}=-u_{xx}u_t$?
the breadwave
which idk how to do
Show that derivative of k + p wrt to t is 0
yes i know
i just need to show that if we differentiate p wrt t the inner integral reduces to -laplacian times u_t
integration by parts
Any good way to get into dispersive PDEs or Potential Theory?
having some trouble with part b
i think i got to that $k(t)-p(t)=\frac{1}{2}\int_{-\infty}^\infty h(x)^2-g'(x)^2 dx$?
the breadwave
idk if i differentiated d'lambert's formula correctly tbh
you didnt
yeah
i thought so
i got like
$\frac{1}{8}\int_{-\infty}^{\infty}(g'(x+t)-g'(x-t)+h(x+t)+h(x-t))^2-(g'(x+t)+g'(x-t)+h(x+t)-h(x-t))^2 dx$
the breadwave
but now t doesn't matter because x covers the real line so the value of the integral doesn't change if we kill t
so what goes on with that @azure frigate
regardless what is important is the compact support
i just dont think its necessary but you can do it i think
im just confused because its like
x covers the real line so even though t may be huge, when x is huge h(x-t) and g'(x-t) may not be 0
wait a minute...
oh nvm this problem is trivial
if we simplify the integral we get $\frac{1}{2}\int_{-\infty}^\infty -h(x+t)g'(x-t)+h(x-t)g'(x+t)-g'(x-t)g'(x+t)+4h(x-t)h(x+t) dx$
the breadwave
and now since we have 2 functions of compact support h(x+t)g'(x-t), when t is large 1 of them is gauranteed to be 0 as if h(x+t) is not 0 then x is close to -t, so -x-t is huge and therefore g'(x-t) is 0
nvm i got i tnak you
(does my reasoning look right)
Dispersive PDE : Ponce Linares' book or Tao's book
For Potential theory, it may have different meanings and then underlying goals so, be more clear please
Hi anatole
I'm good how are you
Fine, a bit busy tho. What are doin now, are you still doing research ?
Yep phd year 4
Hello. I have a question about the book Partial Differential Equations in Action (Third Edition) by Sandro Salsa. In section 4.6.2, it says that u_L is unstable and u_R is asymptotically stable. Also, somehow this leads to the phase diagram on the right being the correct phase diagram for the equation when q''<0. Could someone explain to me why they have that stability/instability and why this leads to the subsequent phase diagram? I think it might be something simple that I am just having trouble finding information about.
Are you still doing fluids
Geophysical fluids, yes
im trying to learn microlocal analysis and feeling very dumb. how do you show that the typical polynomial function with multiindex degree m is in the symbol class S^m?
this is from thibault lefevre's book
Oh dang that's computational stuff
i figure once i see the most basic example it should be obvious but everywhere online assumes that it is obvious
Ok so what does it mean to be in symbol class S^m
figured it out yesterday, i think the key was the compactness in the x variable
what not doing analysis for a year does to a man
Hi guys. Could someone tell me what the notation $(a \otimes b):(c \otimes d) $ means?
$a,b,c,d$ are vectors. I think the $:$ might denote the frobenius inner product, but I only know how it works for matrices. Is it maybe supposed to mean $\sum_{i} a_i c_i + b_i d_i$? I have never seen this notation
mcdnldsmngr
I would interpret that to be the matrix double dot product
a otimes b and c otimes d are both matrices
a otimes b = a dot b^T
Is that common notation? Because i think we use the abstract tensor product
Common notation for the matrix double dot product?
This
To be clear, $A:B=\mathrm{tr}(AB^T)$
Ye
Angetenar
otimes for the vector outer product is quite common
Lol well good luck
ty
is the diffusivity coefficient just a weight function in general case of diffusion models ?
no matter how i look at it, it is just a weight function, and the word is just charged to indicate diffusion instead of weight which is just very broad to indicate any behavior

heat equation
in many cases it can be interpreted as such.
I see, ty for insight
Does wave equation count as a pde?
The wave equation is indeed a pde
Then I choose the wave equation
Are there notable uses of the logarithm of a dirac delta? Does that work well - what notable properties does that distribution have?
How did you come across the logarithm of the dirac delta....
Thinking of the behaviour of score functions, alla log(p(x)), for sharp concentrations
How do you propose to interpret log(dirac delta)?
I'm basically asking if there's topics where it popped up, places where the various formal manipulations (whether there \delta is interpreted as extreme statistical location concentration (and where the log then ties to information functions) or not) have been performed and clarified, in the distribution sense
so what exactly is duhamel's principle
Duhamel's principle is something that you learn once to solve the non-homogeneous heat/wave equations and forget thereafter
$\partial_v u$ means conormal derivative of $u$.
Let $u \in H^1(\Omega)$ be a solution for a problem $Lu = F$ in $\Omega$ and $u = g$ on $\partial\Omega$, where $L$ is an elliptic operator.
Then i want to show that $|\partial_v u|{H^{-1/2}(\partial\Omega)} \leq C|u|{H^1(\Omega)}$, but i was able to show $$|\partial_v u|{H^{-1/2}(\partial\Omega)} \leq C(|u|{H^1(\Omega)} + |F-cu|{L^2(\Omega)}),$$ where $|c|{L^\infty} \leq M$. Is there a way to get rid of the $ |F-cu|{L^2(\Omega)}$ somehow? i was thinking something like $ |F-cu|{L^2(\Omega)} \leq |u|_{H^1(\Omega)}$, but i dont see that currently
Rotta
I have a question about this paragraph about the deconvolution being ill-posed, they wrote that it is basically because of deconvolution, but where does deconvolution appear? Is it because we're taking the inverse fourier transform of phi over u?
It's an ODE thing. See pages 73-74 of https://mtaylor.web.unc.edu/wp-content/uploads/sites/16915/2018/04/analmv.pdf. You can extend it to PDEs by rewriting the PDE as an ODE with values in a function space.
I think I'm required to say Navier-Stokes or Euler
Can't you say EFE with fluid matter sources?
What's EFE?
Einstein Field Equations
Ah, alright 
Seeing how none of that ever shows up in the research that I'm doing, no
Hey guys, sorry for jumping in out of nowhere, but I am dealing with the equation in the pic attached for p integer and p > 1. It resembles a thin-film equation but its not quite there. Has someone worked with something along this lines?
Well what do you want to do with the equation?
So as a little backstory, it stems from a physical model of a roughening solid surface.
Honestly, classification as a start so I can search works up on it would be great. Ideally, understanding of solution behvaiour (e.g. does it blow up in finite time) so I can implement a numerical scheme for it.
I've already played around with it's linearization and a family-viscek-type ansatz, though the resulting ODE in the second case wasn't really useful
This is a consequence of the ontoness of the trace operator from H¹(Ω) to H½(dΩ). It has nothing to do with the elliptic operator L. Actually this is needed to define properly L as an operator.
Or to define its Neumann BVP counterpart.
If we take the approach of only caring about the highest spatial derivative, we can simplify [A\frac{\partial^4u}{\partial x^4}\Rightarrow Apu^{p-1}\frac{\partial^4u}{\partial x^4}] and then you just look at [\frac{\partial u}{\partial t}=Cu^{p-1}\frac{\partial^4u}{\partial x^4}]
Angetenar
For which you can try searching for quasilinear biharmonic equation theory
i believe they did define what they meant by it, on the last paragraph, it is basicly the way g is defined taking u(x,t1) as input
oki, ty!
I have a question about this: So I derived the solution using Fourier transform wrt to variable x, but it also asks me to "be precise about the regularitary conditions", and I dont know how to get that.
I assume it makes sense to require g to be L1, (so the convolution with the heat kernel is L1 too) but what about the source term?
I hope someone provide some insight, i don't know really the answer, but i am assuming it wll boils down on the whatever regularity you used during the process to this point, so i would revise all what i have done and what kind of regularity was needed to make certain equalities or inequalities valid
i think the trace theorem doesnt work for the negative s
Think about it that way :
if you take the trace of u you end up in H½(dΩ), assume Ω is the half-space, then the then the normal derivative, you lose one derivative. we are perfectly fine
What CANNOT happen for the trace is when you have u in H^{s}(Ω),, with s<1/2. Without any further assumption, you cannot take the trace of u in H^{s-½}(dΩ), this is wrong in general.
How are you taking the normal derivative $\textit{after}$ taking the trace? The trace lies in $H^{1/2}(\partial \Omega)$, there is no normal direction to differentiate in.
I don't think an estimate like $$|\partial_\nu u|{H^{-1/2}(\partial \Omega)}\lesssim |u|{H^1(\Omega)} $$
can hold for $u\in\mathcal{C}_c^\infty(\Omega)$ without additional assumptions (*).
Density of $\mathcal{C}c^\infty(\mathrm{int}(\Omega))\subset H_0^1(\Omega)$ would imply that $\partial\nu u$ should vanish for $u\in \mathcal{C}_c^\infty(\Omega)$ vanishing on the boundary. But this is not true of functions like $u(x_1,x')=x_1\cdot \chi(x)$, where $\chi$ is a smooth cutoff equal to $1$ in a neighbourhood of the origin.
(*) Solving an elliptic eqn like in the original question is the kind of assumption that can save you.
grobmez
This was a moral idea. Of course you cannot since you are fixed within the realm of tangential variable.
Somebody here can share me a pythagoras poster?
A poster about pythagoras and stuff
Really wanna learn math
You don't need to solve the PDE just to be in the closure of some domain given by a non-negative sesquilinear form, if I am correct.
Defined over H¹.
Okay one may say "it solves a PDE" in some sense.
Let $\Omega' \subset \Omega$ be a lipshitz domain, then if u solves a PDE $Lu = h \text{ in } \Omega$ and $Lu = 0 \text{ in } \Omega\backslash\Omega'$ does that imply that the conormal derivative of u is zero on $\partial \Omega'$?
Here is a proof.
For the Laplacian
This is H½ of the boundary in the two last lines.
Huh? Maybe I am just sleep deprived (sleepless night last night), but how are you bounding H1 norm of v above by H1/2 norm of it's trace in second last displayed eqn? I agree the trace is surjective and so open, but it's certainly not injective on H1 so not bounded below.
I still think H1 is not enough, for the reason in my last post.
You only need surjectivity to get the reverse estimate
You have to think the otherway
for each prescribed boundary value in H^{1/2} I can find a v such that it is the trace, and since the functional cancels out H^{1}_0 this is fully well defined
This is the same as proving divergence free L2 functions admits a partial vanishing trace in H^{-1/2}
How so? Just abstractly, an estimate ||u|| =< C||Tu|| cannot hold for noninjective T...
It is more like
I choose the extension operator from the H^{1/2} of the boundary to H^{1}
if you prefer
Because i have shown my functional only depends on the boundary value of v.
So let g in H^{1/2}, and say instead I apply my functional to E(g)
Just the open mapping theorem does not say anything about bounded linear right inverse
But it says you can always chose some preimage uniformly in some ball
So either you use the open mapping theorem, either you use the extension operator from the boundary to omega
Okay, so you are NOT claiming that $$|v|{H^1(\Omega)}\leq C|v|{\partial \Omega}|_{H^{1/2}(\partial \Omega)} $$ for arbitrary $v\in H^1 $ then? This is what your secondlast line appeared to be claiming, which is what I was objecting to.
No absolutely not
grobmez
Yeah its not at all clear the way it was written, but then what is your final conclusion? That there is a well-defined neumann trace operator from the range of any extension op H^(1/2)(boundary) -> H^1(domain)?
H^{1}(O) -> H^{-1/2}(boundary)
u is fixed
I want to make sense of neumann trace of u
So you are claiming existence of a bounded neumann trace map H^1(O) -> H^(-1/2)(boundary) ?
If so, I think we are still in disagreement lol.
K_u is a functional on H^{1/2} so I represent it by an element of H^{-1/2}
That's what I proved
this element must be the Neumann trace
Or seemed to prove
according to you
well like we just discussed, your estimate in the penultimate line holds for v in the range of a fixed choice of extension operator, not for general v in H^1
We don't care, the estimate is valid for all v
And I did show in the middle it only depends on the boundary value of v
The extension operator was to make it simple
But the open mapping theorem make it fully arbitrary
and intrinsic
it can't be, like I said that would imply EVERY element of H^1 has "trace" zero.
where ?
Yes. That initial post of mine is pretty much the shortest summary of why (unless I am still misinterpreting your claim) we are in disagreement.
But I am also a zombie right now, so I apologise if I am totally missing your point.
Probably me, then
Probably I did something illegitimate
But that's not the open mapping part, since this is the standard argument.
Oh yeah
wait no
My sleepy take is that I think it comes down to the fact that when you formalise your penultimate line (e.g. using an extension operator), you are only getting the |v| =< |Tv| bound on the range subspace of your (noncanonical) choice of extension op.
The reason I used open mapping instead
basic Functional analysis
for Advanced PDEs
for undergrad PDEs vector calculus
Yeah, I think whatever you are doing there is what I disagree with (or do not understand), but we'll see how it looks to fresher eyes tomorrow.
Sure
Of course especially within Stochastic PDEs
are there any applications relating to isotopes
How would someone come up with such function v? I see that the first term is somewhat natural but the rest seems magical.
Okay, so I now know what you meant in the open mapping theorem part. Indeed that argument is a standard one, and is fine. This means I agree with you that your \gamma_u defines an element of H^(-1/2) for any u in H^1.
I am still not certain about why there is a discrepancy between your construction and my proof that no bounded Neumann trace map H^1 -> H^(-1/2)(boundary) can exist, but here is a very basic question: How exactly are you defining the Laplacian as a bdd map H^1 -> (H^1)*? Simply taking weak/distributional derivatives should instead land you in H^-1 = (H_0^1)*, so it looks like there is a duality pairing being used instead.
My current guess is that with the definition needed to make your construction work, it ceases to coincide with the classical trace for C^inf functions (apart from say if u is harmonic).
Actually I did think about it for the whole day
and we ARE both correct, but still you more than me
Because the Laplacian as a bounded operator from H^{1} to (H^{1})* is actually the Neumann Laplacian which is a fucking isomorphism.
The unbounded L² realization of the Laplacian given by the associated sesquilinear form (or the friedrich extension) is the Neumann Laplacian
So I just built the 0 map.
lol
my proof is not wrong just pointless
because the normal derivative was actually already 0, before I even know it
So we don't contradict each other, at least not directly with my useless proof. The claim of of the boundedness of the trace operator is wrong tho
and your argument is fully correct.
Haha right exactly, it was a subtle point. Okay, glad we are on the same page now and we both learned some things :).
Of course exactly your argument is how one proves Neumann traces exist in certain settings, e.g. for solutions to the Dirichlet problem.
But I did retry the argument, Du in L² and Lu in L², L being a nice elliptic operator in divergence form possibly with lower order terms, with the same argument give some "twisted" Neumann trace in H^{-1/2}.
yeah.
Yeah that kind of statement I believe.
Glad it was resolved, this would have tormented me if it was still unclear after today.
This point is actually necessary to build the Robin Laplacian properly
Me too
one more magically cooked comparison function.
While studying about PDEs I found that we can calculate the general solution of a PDE from it's complete solution.
The method goes like this:
If say, a PDE $F(x,y,z,p,q)=0$ where $p=z_x,q=z_y$ is given, and $f(x,y,z,a,b)=0$ is a complete solution of $F,$ then assume $b$ to be an unknown function of $a$ say, $b=\phi(a).$
So, the complete solution $f$ becomes, $f(x,y,z,a,\phi(a))=0.... (1)$
Now, differentiating the above equation wrt $a$ we get, $f_a(x,y,z,a,\phi(a))+f_b(x,y,z,a,\phi(a))\phi'(a)=0.... (2)$
In principle we can solve $(1)$ and $(2)$ to get $a=a(x,y,z).$
Substituting this in $(1)$ we have,
$f(x,y,z,a(x,y,z),\phi(a(x,y,z))=0.$ This is precisely the general solution of the given PDE as, $b$ is an arbitrary function of $a.$
Now, I wanted to implement this method using an example. So, suppose we have a PDE $z=pq$ having a complete solution $z=(x+a)(y+b).$
Now, proceeding in line of the above method, let $b=\phi(a).$
So, the complete solution becomes $z=(x+a)(y+\phi(a)).$
Differentiating the above equation wrt $a,$ we have,
$$0=(x+a)\phi'(a)+(y+\phi(a))$$
So, we have got $z=(x+a)(y+\phi(a))$ and $x\phi'(a)+a\phi'(a)+y+\phi(a)=0$ as the two equations.
But I don't know how to solve for $a$ such that $a=a(x,y,z)$ from the last two equations.
This makes me doubt about the validity of the method I described earlier for $(2)$ always has an unknown term (or function) $\phi(a)$ due to which finding $a=a(x,y,z)$ does not seem to be feasible at all.
Can someone please help me with this?
Franklin244
where did evans pull this
whats your question? are you asking how the strong maximum principle implies this?
yea
suppose that u is not positive everywhere in U and apply the principle to -u
wait a minute yeah this is trivial
Hey guys. I am bit stuck at this exercise from Dorina Mitrea's book. Intrinsically, I guess u hat should be naught or multiple of a dirac function. But clearly it's not true. Could you tell me what's wrong?
Not a multiple but a sum of derivatives of Dirac masses.
because fourier transform exchange multplications by powers of x into derivatives
First reduce to the case where the support is at 0 using the property of translation and transform. Then note that not only uhat has support 0 but also so does xi uhat. What can you conclude from this: aka what's the general distribution that you can construct which takes advantage of it)
would someone please mind helping a gal out? This has been driving me crazy: #help-29 message
I expanded on the question a bit as a post: https://discord.com/channels/268882317391429632/1304123540047532102
Would appreciate some help if you can
How to approach this?
Do you know what lambda is
Lesage
Ok what manipulations have you tried to apply to the inequality
I stuck in case where k is between u_l and u_r
Ok, what have you worked out in that case
$\lambda (u_r + u_l - 2k) >= f(u_r) + f(u_l) - 2f(k)$
Lesage
So I don't know how to proof this inequality
Hey, let r denote the distance from the origin and suppose G is a scalar function. Can anyone help me to compute $|\nabla (G(r) x_i /r)|^2$?
Buffet
The gradient is supposed to be the euclidean, so I believe we are seeing $r = |x|$
Buffet
So, can anyone help me computing $|\nabla ( G(|x|)x_i/|x|)|^2$?
Buffet
What's there to compute?
A starting point would be the gradient of $G(|x|)x_i/|x|$ but I am getting because I am getting Kroenecker deltas..
Buffet
there might be something easier
Do you know what the gradient is in spherical coordinates
is this channel appropriate for asking questions of ode?
I cannot find one dedicated to ode, and my question is not quite the early uni level
#advanced-analysis for advanced odes
thank you!
If I remember correctly it can be either strictly convex or strictly concave, but not both (convex on one part, concave on the other)
Ok so if f is strictly concave, negate it so that it's strictly convex
Then apply convexity to this inequality
I don't understand what it means? Convex means that second derivative is greater than 0, right? How to apply it here?
What other properties do convex functions have?
$f(λx1+(1−λ)x2)<λf(x1)+(1−λ)f(x2)$
$f(\lambdax1+(1−\lambda)x2)<\lambdaf(x1)+(1−\lambda)f(x2)$
You'll want to fix your latex but yes, you will want to use this
I guess I can redefine k as $\alpha * u_r + (1 - \alpha) * u_l$?
Yes
Lesage
Could someone give me some ideas on this
the method of characteristics tells me that there exists a unique solution in the neighborhood of the initial curve
I have that the solution is of the form u = u_0(s)*e^{-2t} and I know s is implicitly a function of x and t
not sure what other conditions need to be imposed
11
this is from second page of evans
second editions evans pg 193
what does the notation |.,.| mean in this case?
this is what my copy says
oh wait i see it now
for the same example
i thought that they let v(x,t)=u(x, it)
so that they can plug in it in place of t
but wouldn't that solve $iu_t-\Delta u$
lmao
instead of $iu_t + \Delta u$
lmao
oh wait nvm i should be v(x,t)=u(x, t/i)
Uh could anyone help me with this (a)? I'm just so gigantically stuck, I know it is supposed to be zero by using the laplacian and the fourier transform property but I just cannot do the direct computation and see how it is equal to zero.
Ok, how do you start with computing the fourier transform
I think that you are missing something in the first integral
what
I included the phi at the end
in case thats what you mean
oh I missed the integration limits
there should be four
do you have any suggestions
Shouldn't you be taking a fourier transform and not integrating against a test function
i thought the equation means if we look at it as a distribution it is equal to zero
thats why I integrated against a test function
am i wrong
because i am certainly stuck lol
No I don't think you should do that
oh
i believe $\hat{u}$ is notation for the fourier transform of $u$, so you have to take the fourier transform of just $u$
rain
no need to take fourier transform of eq 1
Yeah I think we are not allowed to do that here
The simpler way I mean
That’s why I provided the longer way first. The simpler way is for your own education
I acc got the exact same proof of you did but I was agonizing over it for hours…. Tysm though
I was agonizing over how I could multiply the two Dirac deltas while in reality I shouldn’t multiply them out in the first place, I should just separate them and treat it as two different transforms
I didn’t write it the way you wrote it, I wrote out the integral. That’s why I thought it would be the multiplication of two Dirac deltas
Well, the second derivative I mean
I hope the presentation I provided is clear
Yw!
Does the pde in this channel stand for partial differential equations
No it stands for potentially dangerous equations
Nice
I got a question that asks me to prove that the solution of this eqn is unique by energy method, so I supposed there are two solution u1, u2 and w=u1-u2, and then I did the calculations hoping to conclude something. But this is what I got and I cant really determine the sign. Did I do something wrong here?
You wanna get an energy inequality and Gronwall and use the fact that the difference is 0 when time is 0
oh I didnt know gronwall, I'll look it up, thanks!
Oh, actually I think we dont need to do that. For this, we denote E(t)= the integral of w^2 at t, and then the equation I got says E'(t)<= a constant times E(t). But E(0)=0 and E is nonnegative. Hence E must be 0 for all t>0
How is your "hence" following without Gronwall?
I thought its like a calculus argument
Well "Gronwall" is a calculus argument.
I just ask because this is a point at which I have seen a few erroneous arguments from students before. Afaik Gronwall (or equivalent) is the main way to draw such a conclusion.
E'(t) <=0 at t=0 but then E(0)=0 so it must decrease, but then E>=0 so it must stay zero. If we suppose there exists a point where E>0 then it must be E'>0 for some t but then that leads to a contradiction since we can "push" the t back to t=0 to reach a contradiction.
I know its not rigorous and I should write it out rigorously, but this is a 5-minute quiz question so I thought an answer like this should've been enough
Does this sound ok
The "pushing the t back to t=0" sounds fishy.
Here is a related question to build intuition. Suppose we instead had:
E(t) >= 0 for all t
E'(t) =< 2E(t)^(1/2)
E(0)=0.
Would these hypotheses also imply E is identically zero in [0,inf) ?
I think so yeah
E(t)=t^2
Picard lindelof moment
Yep, you can think of this as related to the fact that local uniqueness of ODE sols breaks down when we are no longer Lipschitz.
It's a very common and extremely natural trap to fall into, otherwise I wouldn't have said anything in the first place.
E'(z) = 0 tells you that a linear approximation at z will look flat
it doesn’t say you can’t approximate your function by a quadratic
It is probably worthwhile to pretend you haven't seen my counterexample, and try to write down a proof of your original claim with full details/generality.
Likely you will understand the issue whilst doing so.
Sorry, do you mean I can just use this inequality? And I think I can take a to be zero, so it is bounded by zero for all t. Does that sound right?
I was not aware of this inequality, and I now see that I was being sloppy. But I dont have the time to review the details rn so I will have to go back to it later.
Yep, this inequality is how one correctly draws the conclusion that E is identically zero. My message was just about you clearing up your personal confusion about your original sketch involving "pushing t back to zero" not working, and leading to an incorrect conclusion in the modified situation I gave.
Does this inequality not work if u is replaced by u^2?
Idk exactly what you mean by this, but in the original energy question, if you had an estimate like E'(t) =< E(t)^2 you would still be okay. An example argument is as follows.
For any s at which E(s) vanishes, you get E(t) =< 1 for t near s by continuity, and so E'(t) =< E(t)^2 =< E(t) and the usual Gronwall then gives you vanishing in this small interval about s. If E were not identically zero you could carry this out at s = inf {t : E(t) nonzero} to get a contradiction.
@void flame
Ohhhhh
yeah my calculus skills are rusty, or I'm just too stressed to think properly lol
Thank you so much❤️
no worries, you'll be fine :). like I said, this is an extremely common trap.
hope I didn't add to your stress. for short quizzes such technical points probably won't be super relevant.
no your explanation was really good, I think the lecturer realized this question was too involved (nobody did it) and changed it to a homework question instead. So the details are much appreciated!
There is a way to make this sort of an intuition rigorous and it's called the bootstrap/continuity argument and it's pretty much equivalent to Gronwall
You can look into Tao's book on dispersive PDEs for more info on it
Oh, oki will make a note of it
Is this an okay channel to ask perturbation theory questions? I'm confused about this problem in Bender and Orszag:
This is the statement of the problem, which is less than helpful:
This is from Gilbarg-Trudinger. Is there any other reference for this result? I would like to see a different proof or maybe another exposition of the same proof.
Check Evans
Evens refers to G-T for a proof 
Well he does give a proof in a simpler setting.
Yeah i wanted to see if there is another exposition of the proof in G-T. There are some points that are confusing me. I will just drop them here later.
Yes
any idea from which book this defintion is or can someone give me a similiar result in any book? its from here https://math.stackexchange.com/questions/612047/sobolev-spaces-on-boundaries
can anyone help me solve this?
i can show my work- my professor has an interesting way of doing it.
I think this is more appropriate for #odes-and-pdes
Assuming $\partial \Omega$ is a smooth manifold, you can just use the definition of Sobolev spaces on compact manifolds $M$ given in https://link.springer.com/book/10.1007/978-3-031-33859-5. For smaller smoothness $k, \alpha$ of the boundary, the same definition should work; you just have to be careful about the invariance of the Sobolev space under coordinate transforms of the given smoothness.
L
Big ty
Seeing these evans questions gives me mega trauma
<@&268886789983436800> ??


f

Does someone have an exact definition of what a breather solution is?
Does anyone know how to get all smooth solution of a constant coefficient PDE? Characteristic method applied to first order case. I don't know how to deal with higher order. I believe there is a general solution.
Can someone help me understand the last line, I do not understand when it says "is the domain of the part..."
Does it not just mean the restriction of A^k in D_A?
ohh, I was confused with the wording they have used, so it says, D_A (\theta + k,p)
is domain of restriction of A^k in D_A?
Do you reckon this could be true
greenface98
Have you checked that it is true for a few simple examples
Seems to have some issues
this is from evans appendix
ive never learnt lesbesgue'es diffeerentiaiotn theorem before but can someone tell me why its almost everywhere converges
and at which x is this not true?
Functions in L^1 are only defined up to null sets. For example, the LHS of (i) is independent of the representative for f but the RHS is not
so you're saying that f(x0) doesn't exist for x0 in a null set?
If you change $f$ on a set of measure $0$, $\frac{1}{Vol(B(x_0, r)}\int_{B(x_0, r)}f,dx$ does not change, whereas $f(x_0)$ can be modified arbitrarily.
L
that's how you know that (i) can at best hold for a.e. x_0
ok thanks i think i see it now
i have a question related to this question of chapter 5 of 11
but if $u$ were differentiable everywhere but the $Du=0$ almost everywhere then is $u$ still a constant?
lmao
been trying to prove this for a long time but can't
wlog $U$ is a ball. I think using an approximate identity might work.
L
Use a mollifier
yeh tht works i think
You can redefine A^k as an unbounded operator on D_A(theta,p) as a new ground space instead of X, then the domain of A^k defined on D_A(theta,p) is D_A(theta+k,p).
x in D_A(theta,p) (included in X) such that A^k belongs to D_A(theta,p).
More generally when it is well defined: For Y a Banach space which is a subspace that imbeds continuously in X, A an unbounded operator on X. The part of A in Y is the ""restriction-co-restriction"" of A to Y with domain { y in D(A)nY s.t. Ay belongs to Y}.
A condition to show it is well defined, is stability of Y by the resolvent of A
which trivially holds for operators that generates a bounded analytic semigroup, and Y to be the associated real interpoaltion space.
Without loss of generality assume one may assume every Banach space of interest is a Hilbert space
Also ‘normed ‘ is assumed for any Banach space
actually I did precise normed because in my work I may use normed but non complete spaces, and consider the part of A in such kind of non-complete real interpolation spaces.
But you are right
I am trying this problem and want to check my idea. We pick and increasing sequence of annuli $A_i \subset A_{i+1} \subset \cdots$ Without loss of generality we can assume that u is bounded below and that $\inf u$ on the exterior domain is 0. Now we notice $\sup_{x,y \in A_i}|u(x) - u(y)| \leq \sup_{A_i}u - \inf_{A_{i}} u \leq (k_i-1) \inf_{A_i} u$. The inf over $A_i$ goes to zero and so we would be done if we can bound the sequence of constants $k_i$
ru0xffian
I have a vague idea of how to bound the constants but want to make sure that so far I am not doing something stupid.
Say I had this functional on L_t on hilbert space H
Where epsilon is distributed according to isotopic Gaussian on R^d
Acting on maps phi from R^d to R^d
And say I had a C_2 curve of functions F_t
How might I show this
Where that operator is the frèchet laplacian
Should my strategy be to express F_t w.r.t so ON basis for my Hilbert space and say that laplacian is the sum over second the directional derivatives over all those basis functions?
And that maybe hope I can show that objective is diffetentibale in time without blowing up?
Frechet derivatives remain very exotic to me
It’s kinda hard to find any info on functional valued PDE’s
The sum of differentials things is not necessarily differentials
Is L_t your original expectation?
Each value t produces a loss functional L_t which is that expectation over epsilon when plugging in that value of t
And I wanna show something about the curve F_t induced by the minimization of each of those functional. Take F_t to be C_2 smooth ( in time) curve satisfying F_t = armin L_t
It’s very hard to find theory on functional valued pde’s
Are they to nasty to even warrant consideration?
What have you looked for?
There should be lots of books on theory for calculus of variations
Yeah that’s def where to look, ive just been looking at ‘functional pde’s’
Or variational pde’s
But overwhelmingly it’s people using variational methods to solve pde’s of finite spatial dimensions not people studying pde’s on functionals
I see, Now it is much more clear. Thanks a lot
Why didn’t any of you nerds tell me that the laplacian of a quadratic functional over a Hilbert space is infinite
I’ve been trying to say something about it this whole time and didn’t realize one of the terms in my equation wasn’t even finite
bard
not sure where i should start on problem 4
problem 3 is just an ez pz cole-hopf transformation
What progress did you make with energy estimates
For many reasons very deep, such kind of estimate cannot hold in general.
C will depend necessarily on \varepsilon and T.
Moreover, you also need to control the time regularity of your boundary value.
This is an L^q-maximal regularity estimate for the initial Boundayr value problem.
Assuming $\varepsilon=1$ for simplicity, one requires $$\partial_x h(\cdot,\cdot,0)\in \dot{\mathrm{H}}^{1/4}t(\mathbb{R}+,\mathrm{L}^2_x(\mathbb{R}_+))\cap {\mathrm{L}}^{2}t(\mathbb{R}+,\dot{\mathrm{H}}^{{1}/{2}}x(\mathbb{R}+))$$
This is necessary and sufficient.
Functionanatolysis
If you want further insights on why such spaces, feel free.
where do i start 
First, recall the divergence term in the E-L equations, and, as per the hint, think about ways that you can get (close to) the left hand side of the equation as the divergence of something
Further hint: ||In 1D, ((e^x)u’(x))’= e^x u’(x) + e^x u”(x) = (e^x)(u’(x)+u”(x))||
(The further hint is not too much of a spoiler if you are still unsure)
aight cool
alli need to show is $e^{-\varphi}DuDv=ve^{-\varphi}(D\varphi Du-\Delta u)$ and gg?
the breadwave
is there a general rule of thumb for which transformation i should try using whenever i see a PDE
It’s not only that (bc you’ll need to get it in the right form), but the leading e^(-phi) term is right
It’s not extensive, but usually the answer really is some type of exponential for linear problems. For parabolic problems, for example, something like e^(b•x+at) is usually enough to simplify the problem to a simpler form
In above $\mathcal{L}_D$ is the Dirichlet Problem $\Delta u = f$ with boundary data $g$. I was reading some paper where they mentioned this. As far, I can only show similar result in $\mathbb{R}^n$ with zero boundary data using Calderon Zygmund theory but am not able to prove it for bounded domain and boundary data, dose someone know about any reference for this.
Math&Tea
This is heavily non-trivial. This is not only Calderon-Zygmund theory, but also boundary layer theory, and use perturbation of invertible operator by a compact operator (or more generally by operator with Fredholm index 0)
The two main references for this are Jerison & Koenig(1995) and Fabes Mendez & Mitrea (1999). Where this is done in the more general framework of bounded Lipschitz domains for 2-e<p<2+e. The C¹ case with the full range of Lebesgue exponents 1<p<+∞ as a special case.
This is the standard Laplace and inverse Laplace transform
i need to show that the inverse is indeed correct

as in derive the formula?
no
just show that the integral does indeed become u(t)
Let $\overline{\mathbb{D}}$ denote the closed unit disc in $\mathbb{C}$ and $\varphi \in C^\infty(\overline{\mathbb{D}})$. Is there a simple way to show that a solution $\psi \in C^\infty(\overline{\mathbb{D}})$ exists for
$$ \frac{\partial \psi}{\partial \overline{z}} = \varphi, \quad \textrm{where} \quad \frac{\partial}{\partial \bar{z}} \coloneqq \frac{1}{2} \left( \frac{\partial}{\partial x} + i \frac{\partial}{\partial y} \right)? $$
Yilian
i don't really need to know the exact form of the solution, just the existence (i.e. i want to show that the operator $\frac{\partial}{\partial \overline{z}}$ is surjective as a map from $C^\infty(\overline{\mathbb{D}}) \to C^\infty(\overline{\mathbb{D}})$.
Yilian
implicit derivation formula
well, its stated on the left that your taking an inverse transform of a transform, effectively recovering the original function
or if u(t) is a known function then you can prove it pretty easily
$\partial_v w$ is conormal derivative of $w$.
Suppose that $\Omega$ is a Lipschitz domain and let $\Omega'$ be a compact subset of a $\Omega$.
Let $w:\Omega\rightarrow \mathbb{R}$ be a solution for a problem \begin{equation*}
L^w = \begin{cases}
h &\text{in } \Omega'\
0 &\text{in } \Omega\backslash \overline{\Omega'}
\end{cases},
\end{equation} $w = 0$ on $\partial\Omega$, where $L$ is an elliptic operator and $h \in H^1(\Omega')$ is a solution to a problem $Lh = 0$ in $\Omega'$.
Do we have an estimate $|\partial_v w|{H^{-1/2}(\partial\Omega')} \leq C|w|{H^1(\Omega)}$?
By the Green's identity we have
$\Phi(w,Eg) = (Eg, L^*w){L^2(\Omega)} - (g , \partial_v w){L^2(\partial\Omega)}$, where $E:H^{1/2}(\partial\Omega) \rightarrow H^1(\Omega)$ is an bounded extension operator. It follows that
$|(g , \partial_v w){L^2(\partial\Omega)}| \leq C|g|{H^{1/2}(\partial\Omega)}|h|{L^2(\Omega')} + C|g|{H^{1/2}(\partial\Omega)}|w|{H^1(\Omega)}$, dividing by $|g|{H^{1/2}(\partial\Omega)}$ by together taking the supremum yields us $|\partial_v w|{H^{-1/2}(\partial\Omega)}\leq C(|h|{L^2(\Omega')} + |w|{H^1(\Omega)})$. I think using the assumption that $L^*w=h$ might give us an estimate $|h|{L^2(\Omega')} \leq C|w|_{H^1(\Omega)}$, which then would imply the the inequality.
