As discussed in previous notes, a function space norm can be viewed as a means to rigorously quantify various statistics of a function . For instance, the “height” and “width” can be quantified via the
norms (and their relatives, such as the Lorentz norms
). Indeed, if
is a step function
, then the
norm of
is a combination
of the height (or amplitude)
and the width
.
However, there are more features of a function of interest than just its width and height. When the domain
is a Euclidean space
(or domains related to Euclidean spaces, such as open subsets of
, or manifolds), then another important feature of such functions (especially in PDE) is the regularity of a function, as well as the related concept of the frequency scale of a function. These terms are not rigorously defined; but roughly speaking, regularity measures how smooth a function is (or how many times one can differentiate the function before it ceases to be a function), while the frequency scale of a function measures how quickly the function oscillates (and would be inversely proportional to the wavelength). One can illustrate this informal concept with some examples:
- Let
be a test function that equals
near the origin, and
be a large number. Then the function
oscillates at a wavelength of about
, and a frequency scale of about
. While
is, strictly speaking, a smooth function, it becomes increasingly less smooth in the limit
; for instance, the derivative
grows at a roughly linear rate as
, and the higher derivatives grow at even faster rates. So this function does not really have any regularity in the limit
. Note however that the height and width of this function is bounded uniformly in
; so regularity and frequency scale are independent of height and width.
- Continuing the previous example, now consider the function
, where
is some parameter. This function also has a frequency scale of about
. But now it has a certain amount of regularity, even in the limit
; indeed, one easily checks that the
derivative of
stays bounded in
as long as
. So one could view this function as having “
degrees of regularity” in the limit
.
- In a similar vein, the function
also has a frequency scale of about
, and can be viewed as having
degrees of regularity in the limit
.
- The function
also has about
degrees of regularity, in the sense that it can be differentiated up to
times before becoming unbounded. By performing a dyadic decomposition of the
variable, one can also decompose this function into components
for
, where
is a bump function supported away from the origin; each such component has frequency scale about
and
degrees of regularity. Thus we see that the original function
has a range of frequency scales, ranging from about
all the way to
.
- One can of course concoct higher-dimensional analogues of these examples. For instance, the localised plane wave
in
, where
is a test function, would have a frequency scale of about
.
There are a variety of function space norms that can be used to capture frequency scale (or regularity) in addition to height and width. The most common and well-known examples of such spaces are the Sobolev space norms , although there are a number of other norms with similar features (such as Hölder norms, Besov norms, and Triebel-Lizorkin norms). Very roughly speaking, the
norm is like the
norm, but with “
additional degrees of regularity”. For instance, in one dimension, the function
, where
is a fixed test function and
are large, will have a
norm of about
, thus combining the “height”
, the “width”
, and the “frequency scale”
of this function together. (Compare this with the
norm of the same function, which is about
.)
To a large extent, the theory of the Sobolev spaces resembles their Lebesgue counterparts
(which are as the special case of Sobolev spaces when
), but with the additional benefit of being able to interact very nicely with (weak) derivatives: a first derivative
of a function in an
space usually leaves all Lebesgue spaces, but a first derivative of a function in the Sobolev space
will end up in another Sobolev space
. This compatibility with the differentiation operation begins to explain why Sobolev spaces are so useful in the theory of partial differential equations. Furthermore, the regularity parameter
in Sobolev spaces is not restricted to be a natural number; it can be any real number, and one can use fractional derivative or integration operators to move from one regularity to another. Despite the fact that most partial differential equations involve differential operators of integer order, fractional spaces are still of importance; for instance it often turns out that the Sobolev spaces which are critical (scale-invariant) for a certain PDE are of fractional order.
The uncertainty principle in Fourier analysis places a constraint between the width and frequency scale of a function; roughly speaking (and in one dimension for simplicity), the product of the two quantities has to be bounded away from zero (or to put it another way, a wave is always at least as wide as its wavelength). This constraint can be quantified as the very useful Sobolev embedding theorem, which allows one to trade regularity for integrability: a function in a Sobolev space will automatically lie in a number of other Sobolev spaces
with
and
; in particular, one can often embed Sobolev spaces into Lebesgue spaces. The trade is not reversible: one cannot start with a function with a lot of integrability and no regularity, and expect to recover regularity in a space of lower integrability. (One can already see this with the most basic example of Sobolev embedding, coming from the fundamental theorem of calculus. If a (continuously differentiable) function
has
in
, then we of course have
; but the converse is far from true.)
Plancherel’s theorem reveals that Fourier-analytic tools are particularly powerful when applied to spaces. Because of this, the Fourier transform is very effective at dealing with the
-based Sobolev spaces
, often abbreviated
. Indeed, using the fact that the Fourier transform converts regularity to decay, we will see that the
spaces are nothing more than Fourier transforms of weighted
spaces, and in particular enjoy a Hilbert space structure. These Sobolev spaces, and in particular the energy space
, are of particular importance in any PDE that involves some sort of energy functional (this includes large classes of elliptic, parabolic, dispersive, and wave equations, and especially those equations connected to physics and/or geometry).
We will not fully develop the theory of Sobolev spaces here, as this would require the theory of singular integrals, which is beyond the scope of this course. There are of course many references for further reading; one is Stein’s “Singular integrals and differentiability properties of functions“.
— 1. Hölder spaces —
Throughout these notes, is a fixed dimension.
Before we study Sobolev spaces, let us first look at the more elementary theory of Hölder spaces , which resemble Sobolev spaces but with the aspect of width removed (thus Hölder norms only measure a combination of height and frequency scale). One can define these spaces on many domains (for instance, the
norm can be defined on any metric space) but we shall largely restrict attention to Euclidean spaces
for sake of concreteness.
We first recall the spaces, which we have already been implicitly using in previous lectures. The space
is the space of bounded continuous functions
on
, with norm
This norm gives the structure of a Banach space. More generally, one can then define the spaces
for any non-negative integer
as the space of all functions which are
times continuously differentiable, with all derivatives of order
bounded, and whose norm is given by the formula
where we view as a rank
, dimension
tensor with complex coefficients (or equivalently, as a vector of dimension
with complex coefficients), thus
(One does not have to use the norm here, actually; since all norms on a finite-dimensional space are equivalent, any other means of taking norms here will lead to an equivalent definition of the
norm. More generally, all the norms discussed here tend to have several definitions which are equivalent up to constants, and in most cases the exact choice of norm one uses is just a matter of personal taste.)
Remark 1 In some texts,
is used to denote the functions which are
times continuously differentiable, but whose derivatives up to
order are allowed to be unbounded, so for instance
would lie in
for every
under this definition. Here, we will refer to such functions (with unbounded derivatives) as lying in
(i.e. they are locally in
), rather than
. Similarly, we make a distinction between
(smooth functions, with no bounds on derivatives) and
(smooth functions, all of whose derivatives are bounded). Thus, for instance,
lies in
but not
.
Exercise 2 Show that
is a Banach space.
Exercise 3 Show that for every
and
, the
norm is equivalent to the modified norm
in the sense that there exists a constant
(depending on
and
) such that
for all
. (Hint: use Taylor series with remainder.) Thus when defining the
norms, one does not really need to bound all the intermediate derivatives
for
; the two extreme terms
suffice. (This is part of a more general interpolation phenomenon; the extreme terms in a sum often already suffice to control the intermediate terms.)
Exercise 4 Let
be a bump function, and
. Show that if
with
,
, and
, then the function
has a
norm of at most
, where
is a constant depending only on
,
and
. Thus we see how the
norm relates to the height
, width
, and frequency scale
of the function, and in particular how the width
is largely irrelevant. What happens when the condition
is dropped?
We clearly have the inclusions
and for any constant-coefficient partial differential operator
of some order , it is easy to see that
is a bounded linear operator from
to
for any
.
The Hölder spaces are designed to “fill up the gaps” between the discrete spectrum
of the continuously differentiable spaces. For
and
, these spaces are defined as the subspace of functions
whose norm
is finite. To put it another way, if
is bounded and continuous, and furthermore obeys the Hölder continuity bound
for some constant and all
.
The space is easily seen to be just
(with an equivalent norm). At the other extreme,
is the class of Lipschitz functions, and is also denoted
(and the
norm is also known as the Lipschitz norm).
Exercise 5 Show that
is a Banach space for every
.
Exercise 6 Show that
for every
, and that the inclusion map is continuous.
Exercise 7 If
, show that the
norm of a function
is finite if and only if
is constant. This explains why we generally restrict the Hölder index
to be less than or equal to
.
Exercise 8 Show that
is a proper subspace of
, and that the restriction of the
norm to
is equivalent to the
norm. (The relationship between
and
is in fact closely analogous to that between
and
, as can be seen from the fundamental theorem of calculus.)
Exercise 9 Let
be a distribution. Show that
if and only if
, and the distributional derivative
of
also lies in
. Furthermore, for
, show that
is comparable to
.
We can then define the spaces for natural numbers
and
to be the subspace of
whose norm
is finite. (As before, there are a variety of ways to define the norm of the tensor-valued quantity
, but they are all equivalent to each other.)
Exercise 10 Show that
is a Banach space which contains
, and is contained in turn in
.
As before, is equal to
, and
is contained in
. The space
is slightly larger than
, but is fairly close to it, thus providing a near-continuum of spaces between the sequence of spaces
. The following examples illustrates this:
Exercise 11 Let
be a test function, let
be a natural number, and let
.
- Show that the function
lies in
whenever
.
- Conversely, if
is not an integer,
, and
, show that
does not lie in
.
- Show that
lies in
, but not in
.
This example illustrates that the quantity
can be viewed as measuring the total amount of regularity held by functions in
:
full derivatives, plus an additional
amount of Hölder continuity.
Exercise 12 Let
be a test function, let
be a natural number, and let
. Show that for
with
, the function
has a
norm of at most
, for some
depending on
.
By construction, it is clear that continuously differential operators of order
will map
continuously to
.
Now we consider what happens with products.
Exercise 13 Let
be natural numbers, and
.
- If
and
, show that
, and that the multiplication map is continuous from
to
. (Hint: reduce to the case
and use induction.)
- If
and
, and
, show that
, and that the multiplication map is continuous from
to
.
It is easy to see that the regularity in these results cannot be improved (just take
). This illustrates a general principle, namely that a pointwise product
tends to acquire the lower of the regularities of the two factors
.
As one consequence of this exercise, we see that any variable-coefficient differential operator of order
with
coefficients will map
to
for any
and
.
We now briefly remark on Hölder spaces on open domains in Euclidean space
. Here, a new subtlety emerges; instead of having just one space
for each choice of exponents
, one actually has a range of spaces to choose from, depending on what kind of behaviour one wants to impose at the boundary of the domain. At one extreme, one has the space
, defined as the space of
times continuously differentiable functions
whose Hölder norm
is finite; this is the “maximal” choice for the . At the other extreme, one has the space
, defined as the closure of the compactly supported functions in
. This space is smaller than
; for instance, functions in
must converge to zero at the endpoints
, while functions in
do not need to do so. An intermediate space is
, defined as the space of restrictions of functions in
to
. For instance, the restriction of
to
, where
is a cutoff function non-vanishing at the origin, lies in
, but is not in
or
(note that
itself is not in
, as it is not continuously differentiable at the origin). It is possible to clarify the exact relationships between the various flavours of Hölder spaces on domains (and similarly for the Sobolev spaces discussed below), but we will not discuss these topics here.
Exercise 14 Let
and
. Show that
is a dense subset of
if one places the
topology on the latter space. (Hint: To approximate a compactly supported
function by a
one, convolve with a smooth, compactly supported approximation to the identity.) What happens in the endpoint case
?
Hölder spaces are particularly useful in elliptic PDE, because tools such as the maximum principle lend themselves well to the suprema that appear inside the definition of the norms; see for instance the book of Gilbarg and Trudinger for a thorough treatment. For simple examples of elliptic PDE, such as the Poisson equation
, one can also use the explicit fundamental solution, through lengthy but straightforward computations. We give a typical example here:
Exercise 15 (Schauder estimate) Let
, and let
be a function supported on the unit ball
. Let
be the unique bounded solution to the Poisson equation
(where
is the Laplacian), given by convolution with the Newton kernel:
- (i) Show that
.
- (ii) Show that
, and rigorously establish the formula
for
.
- (iii) Show that
, and rigorously establish the formula
for
, where
is the Kronecker delta. (Hint: first establish this in the two model cases when
, and when
is constant near
.)
- (iv) Show that
, and establish the Schauder estimate
where
depends only on
.
- (v) Show that the Schauder estimate fails when
. Using this, conclude that there eixsts
supported in the unit ball such that the function
defined above fails to be in
. (Hint: use the closed graph theorem.) This failure helps explain why it is necessary to introduce Hölder spaces into elliptic theory in the first place (as opposed to the more intuitive
spaces).
Remark 16 Roughly speaking, the Schauder estimate asserts that if
has
regularity, then all other second derivatives of
have
regularity as well. This phenomenon – that control of a special derivative of
at some order implies control of all other derivatives of
at that order – is known as elliptic regularity, and relies crucially on
being an elliptic differential operator. We will discus ellipticity a little bit more later in Exercise 45. The theory of Schauder estimates is by now extremely well developed, and applies to large classes of elliptic operators on quite general domains, but we will not discuss these estimates and their applications to various linear and nonlinear elliptic PDE here.
Exercise 17 (Rellich-Kondrachov type embedding theorem for Hölder spaces) Let
. Show that any bounded sequence of functions
that are all supported in the same compact subset of
will have a subsequence that converges in
. (Hint: use the Arzelá-Ascoli theorem to first obtain uniform convergence, then upgrade this convergence.) This is part of a more general phenomenon: sequences bounded in a high regularity space, and constrained to lie in a compact domain, will tend to have convergent subsequences in low regularity spaces.
— 2. Classical Sobolev spaces —
We now turn to the “classical” Sobolev spaces , which involve only an integral amount
of regularity.
Definition 18 Let
, and let
be a natural number. A function
is said to lie in
if its weak derivatives
exist and lie in
for all
. If
lies in
, we define the
norm of
by the formula
(As before, the exact choice of convention in which one measures the
norm of
is not particularly relevant for most applications, as all such conventions are equivalent up to multiplicative constants.)
The space is also denoted
in some texts.
Example 19
is of course the same space as
, thus the Sobolev spaces generalise the Lebesgue spaces. From Exercise 9 we see that
is the same space as
, with an equivalent norm. More generally, one can see from induction that
is the same space as
for
, with an equivalent norm. It is also clear that
contains
for any
.
Example 20 The function
lies in
, but is not everywhere differentiable in the classical sense; nevertheless, it has a bounded weak derivative of
. On the other hand, the Cantor function (aka the “Devil’s staircase”) is not in
, despite having a classical derivative of zero at almost every point; the weak derivative is a Cantor measure, which does not lie in any
space. Thus one really does need to work with weak derivatives rather than classical derivatives to define Sobolev spaces properly (in contrast to the
spaces).
Exercise 21 Let
be a bump function,
, and
. Show that if
with
,
, and
, then the function
has a
norm of at most
, where
is a constant depending only on
,
and
. (Compare this with Exercise 4 and Exercise 12.) What happens when the condition
is dropped?
Exercise 22 Show that
is a Banach space for any
and
.
The fact that Sobolev spaces are defined using weak derivatives is a technical nuisance, but in practice one can often end up working with classical derivatives anyway by means of the following lemma:
Lemma 23 Let
and
. Then the space
of test functions is a dense subspace of
.
Proof: It is clear that is a subspace of
. We first show that the smooth functions
is a dense subspace of
, and then show that
is dense in
.
We begin with the former claim. Let , and let
be a sequence of smooth, compactly supported approximations to the identity. Since
, we see that
converges to
in
. More generally, since
is in
for
, we see that
converges to
in
. Thus we see that
converges to
in
. On the other hand, as
is smooth,
is smooth; and the claim follows.
Now we prove the latter claim. Let be a smooth function in
, thus
for all
. We let
be a compactly supported function which equals
near the origin, and consider the functions
for
. Clearly, each
lies in
. As
, dominated convergence shows that
converges to
in
. An application of the product rule then lets us write
. The first term converges to
in
by dominated convergence, while the second term goes to zero in the same topology; thus
converges to
in
. A similar argument shows that
converges to
in
for all
, and so
converges to
in
, and the claim follows.
As a corollary of this lemma we also see that the space of Schwartz functions is dense in
.
Exercise 24 Let
. Show that the closure of
in
is
(the space of
functions whose first
derivatives all go to zero at infinity), thus Lemma 23 fails at the endpoint
.
Now we come to the important Sobolev embedding theorem, which allows one to trade regularity for integrability. We illustrate this phenomenon first with some very simple cases. First, we claim that the space embeds continuously into
, thus trading in one degree of regularity to upgrade
integrability to
integrability. To prove this claim, it suffices to establish the bound
for all test functions and some constant
, as the claim then follows by taking limits using Lemma 23. (Note that any limit in either the
or
topologies, is also a limit in the sense of distributions, and such limits are necessarily unique. Also, since
is the dual space of
, the distributional limit of any sequence bounded in
remains in
, by Exercise 28 of Notes 3.) To prove (1), observe from the fundamental theorem of calculus that
for all ; in particular, from the triangle inequality
Also, taking to be sufficiently large, we see (from the compact support of
) that
and (1) follows.
Since the closure of in
is
, we actually obtain the stronger embedding, that
embeds continuously into
.
Exercise 25 Show that
embeds continuously into
, thus there exists a constant
(depending only on
) such that
for all
.
Now we turn to Sobolev embedding for exponents other than and
.
Theorem 26 (Sobolev embedding theorem for one derivative) Let
be such that
, but that one is not in the endpoint cases
. Then
embeds continuously into
.
Proof: By Lemma 23 and the same limiting argument as before, it suffices to establish the Sobolev embedding inequality
for all test functions , and some constant
depending only on
, as the inequality will then extend to all
. To simplify the notation we shall use
to denote an estimate of the form
, where
is a constant depending on
(the exact value of this constant may vary from instance to instance).
The case is trivial. Now let us look at another extreme case, namely when
; by our hypotheses, this forces
. Here, we use the fundamental theorem of calculus (and the compact support of
) to write
for any and any direction
. Taking absolute values, we conclude in particular that
We can average this over all directions :
Switching from polar coordinates back to Cartesian (multiplying and dividing by ) we conclude that
thus is pointwise controlled by the convolution of
with the fractional integration
. By the Hardy-Littlewood-Sobolev theorem on fractional integration (Corollary 7 of Notes 1) we conclude that
and the claim follows. (Note that the hypotheses are needed here in order to be able to invoke this theorem.)
Now we handle intermediate cases, when . (Many of these cases can be obtained from the endpoints already established by interpolation, but unfortunately not all such cases can be, so we will treat this case separately.) Here, the trick is not to integrate out to infinity, but instead to integrate out to a bounded distance. For instance, the fundamental theorem of calculus gives
for any , hence
What value of should one pick? If one picks any specific value of
, one would end up with an average of
over spheres, which looks somewhat unpleasant. But what one can do here is average over a range of
‘s, for instance between
and
. This leads to
averaging over all directions and converting back to Cartesian coordinates, we see that
Thus one is bounding pointwise (up to constants) by the convolution of
with the kernel
, plus the convolution of
with the kernel
. A short computation shows that both kernels lie in
, where
is the exponent in Young’s inequality, and more specifically that
(and in particular
). Applying Young’s inequality (Exercise 25 of Notes 1), we conclude that
and the claim follows.
Remark 27 It is instructive to insert the example in Exercise 21 into the Sobolev embedding theorem. By replacing the
norm with the
norm, one trades one factor of the frequency scale
for
powers of the width
. This is consistent with the Sobolev embedding theorem so long as
, which is essentially one of the hypotheses in that exercise. Thus, one can view Sobolev embedding as an assertion that the width of a function must always be greater than or comparable to the wavelength scale (the reciprocal of the frequency scale), raised to the power of the dimension; this is a manifestation of the uncertainty principle.
Exercise 28 Let
. Show that the Sobolev endpoint estimate fails in the case
. (Hint: experiment with functions
of the form
, where
is a test function supported on the annulus
.) Conclude in particular that
is not a subset of
. (Hint: Either use the closed graph theorem, or use some variant of the function
used in the first part of this exercise.) Note that when
, the Sobolev endpoint theorem for
follows from the fundamental theorem of calculus, as mentioned earlier. There are substitutes known for the endpoint Sobolev embedding theorem, but they involve more sophisticated function spaces, such as the space
of spaces of bounded mean oscillation, which we will not discuss here.
The case of the Sobolev inequality cannot be proven via the Hardy-Littlewood-Sobolev inequality; however, there are other proofs available. One of these (due to Gagliardo and Nirenberg) is based on
Exercise 29 (Loomis-Whitney inequality) Let
, let
for some
, and let
be the function
Show that
(Hint: induct on
, using Hölder’s inequality and Fubini’s theorem.)
Lemma 30 (Endpoint Sobolev inequality)
embeds continuously into
.
Proof: It will suffice to show that
for all test functions . From the fundamental theorem of calculus we see that
and thus
where
From Fubini’s theorem we have
and hence by the Loomis-Whitney inequality
and the claim follows.
Exercise 31 (Connection between Sobolev embedding and isoperimetric inequality) Let
, and let
be an open subset of
whose boundary
is a smooth
-dimensional manifold. Show that the surface area
of
is related to the volume
of
by the isoperimetric inequality
for some constant
depending only on
. (Hint: Apply the endpoint Sobolev theorem to a suitably smoothed out version of
.) It is also possible to reverse this implication and deduce the endpoint Sobolev embedding theorem from the isoperimetric inequality and the coarea formula, which we will do in later notes.
Exercise 32 Use dimensional analysis to argue why the Sobolev embedding theorem should fail when
. Then create a rigorous counterexample to that theorem in this case.
Exercise 33 Show that
embeds into
whenever
and
are such that
, and such that at least one of the two inequalities
,
is strict.
Exercise 34 Show that the Sobolev embedding theorem fails whenever
. (Hint: experiment with functions of the form
, where
is a test function and the
are widely separated points in space.)
Exercise 35 (Hölder-Sobolev embedding) Let
. Show that
embeds continuously into
, where
is defined by the scaling relationship
. Use dimensional analysis to justify why one would expect this scaling relationship to arise naturally, and give an example to show that
cannot be improved to any higher exponent.
More generally, with the same assumptions on
, show that
embeds continuously into
for all natural numbers
.
Exercise 36 (Sobolev product theorem, special case) Let
,
, and
be such that
. Show that whenever
and
, then
, and that
for some constant
depending only on the subscripted parameters. (This is not the most general range of parameters for which this sort of product theorem holds, but it is an instructive special case.)
Exercise 37 Let
be a differential operator of order
whose coefficients lie in
. Show that
maps
continuously to
for all
and all integers
.
— 3. -based Sobolev spaces —
It is possible to develop more general Sobolev spaces than the integer-regularity spaces
defined above, in which
is allowed to take any real number (including negative numbers) as a value, although the theory becomes somewhat pathological unless one restricts attention to the range
, for reasons having to do with the theory of singular integrals.
As the theory of singular integrals is beyond the scope of this course, we will illustrate this theory only in the model case , in which Plancherel’s theorem is available, which allows one to avoid dealing with singular integrals by working purely on the frequency space side.
To explain this, we begin with the Plancherel identity
which is valid for all functions and in particular for Schwartz functions
. Also, we know that the Fourier transform of any derivative
of
is
. From this we see that
for all and so on summing in
we have
A similar argument then gives
and so on summing in we have
for all and all Schwartz functions
. Since the Schwartz functions are dense in
, a limiting argument (using the fact that
is complete) then shows that the above formula also holds for all
.
Now observe that the quantity is comparable (up to constants depending on
) to the expression
, where
(this quantity is sometimes known as the “Japanese bracket” of
). We thus conclude that
where we use here to denote the fact that
and
are comparable up to constants depending on
, and
denotes the variable of independent variable on the right-hand side. If we then define, for any real number
, the space
to be the space of all tempered distributions
such that the distribution
lies in
, and give this space the norm
then we see that embeds into
, and that the norms are equivalent.
Actually, the two spaces are equal:
Exercise 38 For any
, show that
is a dense subspace of
. Use this to conclude that
for all non-negative integers
.
It is clear that , and that
whenever
. The spaces
are also (complex) Hilbert spaces, with the Hilbert space inner product
It is not hard to verify that this inner product does indeed give the structure of a Hilbert space (indeed, it is isomorphic under the Fourier transform to the Hilbert space
which is isomorphic in turn under the map
to the standard Hilbert space
).
Being a Hilbert space, is isomorphic to its dual
(or more precisely, to the complex conjugate of this dual). There is another duality relationship which is also useful:
Exercise 39 (Duality between
and
) Let
, and
. Show also for any continuous linear functional
there exists a unique
such that
for all
, where the inner product
is defined via the Fourier transform as
Also show that
for all
.
The Sobolev spaces also enjoy the same type of embedding estimates as their classical counterparts:
Exercise 40 (Sobolev embedding for
, I) If
, show that
embeds continuously into
whenever
. (Hint: use the Fourier inversion formula and the Cauchy-Schwarz inequality.)
Exercise 41 (Sobolev embedding for
, II) If
, show that
embeds continuously into
whenever
. (Hint: it suffices to handle the extreme case
. For this, first reduce to establishing the bound
to the case when
is a Schwartz function whose Fourier transform vanishes near the origin (and
depends on
), and write
for some
which is bounded in
. Then use Exercise 35 from Notes 3 and Corollary 7 from Notes 1.
Exercise 42 In this exercise we develop a more elementary variant of Sobolev spaces, the
Hölder spaces. For any
and
, let
be the space of functions
whose norm
is finite, where
is the translation of
by
. Note that
(with equivalent norms).
- (i) For any
, establish the inclusions
for any
. (Hint: take Fourier transforms and work in frequency space.)
- (ii) Let
be a bump function, and let
be the approximations to the identity
. If
, show that one has the equivalence
where we use
to denote the assertion that
and
are comparable up to constants depending on
. (Hint: To upper bound
for
, express
as a telescoping sum of
for
, plus a final term
where
is comparable to
.)
- (iii) If
and
are such that
, show that
embeds continuously into
. (Hint: express
as
plus a telescoping series of
, where
is as in the previous exercise. The additional convolution is in place in order to apply Young’s inequality.)
The functions
are crude versions of Littlewood-Paley projections, which play an important role in harmonic analysis and nonlinear wave and dispersive equations.
Exercise 43 (Sobolev trace theorem, special case) Let
. For any
, establish the Sobolev trace inequality
where
depends only on
and
, and
is the restriction of
to the standard hyperplane
. (Hint: Convert everything to
-based statements involving the Fourier transform of
, and use either the Cauchy-Schwarz inequality or Schur’s test, see Lemma 5 of Notes 1.)
- (i) Show that if
for some
, and
, then
(note that this product has to be defined in the sense of tempered distributions if
is negative), and the map
is continuous from
to
. (Hint: First prove this when
is a non-negative integer using an argument similar to that in Exercise 36, then exploit duality to handle the case of negative integer
. To handle the remaining cases, decompose the Fourier transform of
into annular regions of the form
for
, as well as the ball
, and use the preceding cases to estimate the
norm of the Fourier transform of
these annular regions and on the ball.)
- (ii) Let
be a partial differential operator of order
with coefficients in
for some
. Show that
maps
continuously to
for all
.
Now we consider a partial converse to Exercise 44.
Exercise 45 (Elliptic regularity) Let
, and let
be a constant-coefficient homogeneous differential operator of order
. Define the symbol
of
to be the homogeneous polynomial of degree
, defined by the formula
We say that
is elliptic if one has the lower bound
for all
and some constant
. Thus, for instance, the Laplacian is elliptic. Another example of an elliptic operator is the Cauchy-Riemann operator
in
. On the other hand, the heat operator
, the Schrödinger operator
, and the wave operator
are not elliptic on
.
- (i) Show that if
is elliptic of order
, and
is a tempered distribution such that
, then
, and that one has the bound
for some
depending on
. (Hint: Once again, rewrite everything in terms of the Fourier transform
of
.)
- (ii) Show that if
is a constant-coefficient differential operator of
which is not elliptic, then the estimate (2) fails.
- (iii) Let
be a function which is locally in
, and let
be an elliptic operator of order
. Show that if
, then
is smooth. (Hint: First show inductively that
for every test function
and every natural number
.)
Remark 46 The symbol
of an elliptic operator (with real coefficients) tends to have level sets that resemble ellipsoids, hence the name. In contrast, the symbol of parabolic operators such as the heat operator
has level sets resembling paraboloids, and the symbol of hyperbolic operators such as the wave operator
has level sets resembling hyperboloids. The symbol in fact encodes many important features of linear differential operators, in particular controlling whether singularities can form, and how they must propagate in space and/or time; but this topic is beyond the scope of this course.
167 comments
Comments feed for this article
1 May, 2009 at 8:50 am
abc
Can the statement that H^{1/2}-functions don’t have “jumps” (I don’t know what this means for an L^p-function) be made precise?
1 May, 2009 at 10:01 am
Terence Tao
Dear abc,
Well, it is true that no piecewise smooth function with a jump discontinuity can lie in
; the Fourier transform will decay like
, causing a logarithmic divergence in the
norm. (This fact is loosely related to the Gibbs phenomenon, though that is more about the failure of absolute integrability of the Fourier transform, rather than the weighted square-integrability.)
Also, it is known that
functions, while possibly being unbounded or discontinuous, must at least lie in VMO, the space of functions with vanishing mean oscillation; functions with jump discontinuities do not lie in this class.
Finally, there are a number of results known that are consistent with the philosophy of
having no jump discontinuities, for instance it is known (by
map from the unit circle
to itself, despite the fact that such functions can be arbitrarily oscillatory (and in particular, discontinuous).
Brezis and Nirenberg, I thinkBoutet de Monvel and Gabber) that there is a well-defined notion of a degree (i.e. winding number) of an20 April, 2011 at 2:15 pm
Student
Dear Professor Terrence,
do you know an easy example of a function u in the space H^1/2(0,1) but not in the H^1(0,1) space?
Thanks!
6 August, 2011 at 3:25 pm
Anonymous
A triangle in (0,1).
27 April, 2014 at 6:30 am
Fan
uh-huh? the Fourier transform of a triangle decays like
, so if we multiply it by
we still have
decay, which is square integrable.
1 May, 2009 at 12:39 pm
Anonymous
Dear Professor Tao:
The entire blog entry instead of the preview is showing on the home page. [Corrected, thanks – T]
1 May, 2009 at 8:39 pm
lutfu
Dear Prof. Tao,
In exercise 29, in the definition of inner product you write ”…..is defined via the Fourier transform as …..”
on the right hand side do you mean Fourier transform of f and g or f,g themselves?
thanks
[Corrected, thanks – T.]
1 May, 2009 at 9:50 pm
timur
Thanks a lot for these notes! I find the insights, exercises and examples to be invaluable to play with.
I think some hats also missing in the definition of Hs-inner product just after Exercise 28.
1 May, 2009 at 9:52 pm
timur
Remark 4 (at the end) has a “yellow” formula.
2 May, 2009 at 7:27 pm
Polam
In Exercise 21, do you just mean that the Hardy-Littlewood-Sobolev theorem on fractional integration fails when p = 1? The Sobolev embedding theorem should be true for p = 1, i.e. $W^{1,1}$ should embed into $L^{d/d-1}$ in d dimensions for all d, and in fact this is equivalent to the isoperimetric inequality.
2 May, 2009 at 8:47 pm
Terence Tao
Oh, good point! I had forgotten all about this connection. I’ve corrected the exercise and added some relevant material about the endpoint Sobolev inequality and the isoperimetric inequality.
2 May, 2009 at 9:56 pm
lutfu
Dear Prof. Tao,
in the section 2. classical sobolev spaces, in example 2, you say ” cantor function despite having classical derivative a.e zero, the weak derivative is cantor measure….”
I did not understand this sentence. if a function has classical derivative, isn’t its weak derivative the same?
Could you please clarify this point?
and after exercise 12, you define Holder norm and in the second sup of the norm definition, should it be k or j?
3 May, 2009 at 7:34 am
Terence Tao
Dear Lutfu,
The classical and weak derivatives only agree for absolutely continuous functions (in the one dimensional setting), because one needs the fundamental theorem of calculus to apply to equate the two.
I suppose I should use k instead of j here in order to retain the claim of being the “maximal” concept of a Holder space, though for any reasonable domain the two notions would be equivalent.
4 September, 2016 at 12:24 pm
Anonymous
Do you have a hint about why “The classical and weak derivatives agree for absolutely continuous functions”?
4 September, 2016 at 12:27 pm
Anonymous
For “agree”, do you mean “agree almost everywhere”?
12 May, 2009 at 7:09 am
bk
Dear Terry,
1. are you sure you want to this notation:
” and for any constant-coefficient partial differential operator
”
instead of
2. “For instance, the restriction of
to
lies in
, but is not in…”
do you focus on the origin, or do you really want to say
[Corrected, thanks – T]
12 May, 2009 at 10:58 am
bk
Dear Terry,
You were in a hurry.
1. also take a look at the ‘denominator’ of the operator
2. according to your definition if |x| in C^{1,0}, it should be bounded, right?
I don’t enjoy being so wordy but I like your stuff so much that I want them to be typoless :).
[Corrected again – T.]
12 May, 2009 at 2:31 pm
future topics « 逝去日子
[…] 五月 12, 2009 作者为 曾经话说要如何 1. Schauder estimate/Rellich-Kondrakov type embedding theorem for Holder space—terry’s. […]
24 May, 2009 at 3:53 am
Antonio
Dear Terry,
there is a “formula does not parse” yellow message in the third paragraph (just after the list of examples).
Thanks for your work.
25 May, 2009 at 11:15 am
student
Dear Prof Tao,
Are sobolev embedding theorems also true for any open set?(bounded or unbounded)
And when we say fundamental solution, do we mean that a tempered distribution which satisfy the equation?(not just distribution, tempered distribution? right?)
thanks
25 May, 2009 at 10:17 pm
Terence Tao
Dear Student,
The situation with the Sobolev embedding theorems on domains is somewhat subtle. For one thing, one has to decide upon exactly how one is to define the Sobolev spaces and norms (cf. the discussion after Exercise 12). If these spaces and norms are defined on domains as restrictions of their
counterparts (or as the closure of smooth, compactly supported functions), then the embedding theorem on domains is a tautological consequence of that for
; but if they are defined differently then one has to take more care. Generally speaking, though, for sufficiently “nice” domains (e.g. bounded, with smooth boundary) the embedding theorems continue to hold no matter how one defines the Sobolev spaces and norms, but care would have to be taken if the domain starts developing very thin necks or has a fractal boundary. There is a close relationship between Sobolev inequalities and isoperimetric inequalities (see Exercise 22), so as a rule of thumb, any domain for which the isoperimetric inequality continues to hold, will also have a good Sobolev inequality. (Note that thin necks and fractal boundaries can allow a small boundary to enclose a large volume, thus leading to possible degradation of the isoperimetric inequality and hence Sobolev inequalities.)
Fundamental solutions can be either tempered or non-tempered, though in the latter case they can only be used to solve PDE with test function data (rather than PDE with Schwartz data).
26 May, 2009 at 4:07 am
student
Thank you very much Prof. Tao,
in exc 16 hint, I think there should be x in front of the integral.
26 May, 2009 at 4:09 am
student
excuse me, not for this post. exc 16 of Distributions.
14 June, 2009 at 4:00 pm
lutfu
Dear Prof. Tao
the conditions for Exc 24 is given different in some other sources.
for example like this:
are both equivalent?
thanks
14 June, 2009 at 4:54 pm
Terence Tao
Up to endpoints, yes. The
and
endpoints are often treated differently (and here it becomes important whether k, l are integers or not); I am including the
endpoints but not the
endpoints in my formulation, but the reverse is being stated in your example.
21 June, 2009 at 2:56 pm
Student
Dear Professor Tao:
I have a question about trying to extend Poincare’s inequality (or Sobolev Embedding) to negative derivative. In other words, if one has D^{\alpha-1}f where D is a differentiation, \alpha \in (0,1), and f some smooth function, how can we estimate such term? If one could extend Poincare’s inequality to negative derivative, then I suppose this norm can be bounded by that of f, analogously to how the norm of f can be bounded by the norm of its gradient in any Lp norm for p even 1 or infinity, but I do not know if this is true.
I also looked at Riesz potential from Stein’s book looking for answer to this question, but such inequality seems to be true only in Lp norm but not when p=1 or infinity.
Is there any way to estimate the negative derivative of f in sup norm? Can we at least say that the sup norm of negative derivative of f is bounded by the that of gradient of f?
Any share of thoughts would be appreciated.
Thank you.
22 June, 2009 at 8:39 pm
Terence Tao
Dear Student,
I am not exactly sure what kind of inequalities you are looking for, but generally speaking the Hardy-Littlewood-Sobolev fractional integration inequality provides all the relevant estimates, except possibly at endpoints
, for which the fractional integration estimates tend to fail.
Note also that in any of these inequalities, the right-hand side norm needs to have at least as many derivatives as the left-hand side, thus for instance one can hope to control a norm of f by a norm of
, but not conversely. This can be seen by considering high-frequency test inputs for f, such as
(in one dimension) where
is a bump function and N is a large frequency.
29 June, 2009 at 12:29 am
vedadi
Dear Prof. Tao,
is the following definition right?
for
and
we say that a function
is in
if
1)
is continuous and bounded
2)all partial derivatives upto and including order k are continuous and bounded
3)
derivative is Holder continuous (just kth order derivatives)
thanks
29 June, 2009 at 9:23 am
Terence Tao
Dear Vedadi,
Yes, this will give an equivalent definition of the Holder spaces. (If a higher derivative is bounded, then the lower derivatives are automatically Lipschitz continuous and thus Holder continuous also.) In fact there are quite a few useful equivalent formulations of both the Holder norms and the Sobolev norms.
14 July, 2009 at 10:55 am
sjt
In the first sentence you refer to some previous notes containing a discussion of function space norms. Are those notes available? If so, where?
14 July, 2009 at 11:47 am
Terence Tao
Dear sjt,
I was referring to my 245B lecture notes,
https://terrytao.wordpress.com/category/teaching/245b-real-analysis/
with Lectures 3,5,6,9 being perhaps the most relevant.
21 August, 2009 at 3:45 am
Student
Dear Professor Tao:
I would like to know if the change of sign upon integration by parts still holds when it is fractional integration by parts. In other words, instead of
D^{1}, where D is a differentiation operator,
with
D^{\alpha} for some \alpha \in (0, 1)
and for simplicity assuming f and g are compactly supported smooth functions,
do we have
– \int f D^{\alpha}g = \int(D^{\alpha}f)g ?
Related to this question,
do we have the usual product rule for fractional derivative?
I.e. do we have
D^{\alpha}(fg) = (D^{\alpha}f)g + f(D^{\alpha}g)?
Having read a little about Riesz potential, I have a feeling it is not so simple. But I could not definitively figure this out.
21 August, 2009 at 8:50 am
Terence Tao
Fractional derivatives should be more accurately denoted
rather than
; their Fourier symbol is
, whereas the symbol for the ordinary derivative D is
(give or take a factor of
, depending on one’s Fourier conventions). In particular, these operators are self-adjoint (as is any other Fourier multiplier with real symbol).
The Leibnitz rule for fractional derivatives only holds approximately (up to lower order terms); this “fractional Leibnitz rule” is one of the foundational results of paradifferential calculus. Taylor’s book “Tools for PDE” is a good reference here; see also my lecture notes at
http://www.math.ucla.edu/~tao/247b.1.07w/
21 August, 2009 at 2:09 pm
Student
Dear Professor Tao:
Thank you very much for your reply as well as suggested readings.
Best regards,
29 September, 2009 at 7:34 am
Studnet
Dear Professor Tao,
Is it true that $W^{k,2}\times W^{-k,2}\rightarrow L^1$ through the product map?
21 October, 2009 at 3:26 pm
Terence Tao
No; a product, in general, cannot become smoother than its factors (in sharp contrast to convolution), and since one of the factors has a negative regularity, the product will have negative regularity also. For a more concrete example, consider the product of
and
in one dimension, where
is a bump function. The first factor is bounded in
, while the second factor goes to zero in
norm as
. The product, however, does not go to zero in
norm, and so the product map is not continuous in these topologies. (One can use the closed graph theorem to then show that the product map will not stay inside
, if one interprets products in the distributional sense.)
21 October, 2009 at 2:47 pm
Anonymous
Dear Professor Tao:
Is there a connection of http://en.wikipedia.org/wiki/Fractional_calculus to Sobolev spaces with non-integer-regularity? E.g., is there an easy solution to finding the largest s so that
for a given
?
This is a great resource, many thanks!
21 October, 2009 at 3:22 pm
Terence Tao
Yes; for instance, a function
lies in
for some
if and only if
and
both lie in
, where
is the
fractional derivative of
. There are similar statements for other
-based Sobolev spaces (though there are technical issues at the endpoints
and
).
The functions
are not globally in
for any
, but one can show by various means (e.g. Fourier transform, Littlewood-Paley type decomposition, or the various potential theory characterisations of the Sobolev norms) that they lie locally in
for
whenever
.
21 October, 2009 at 5:57 pm
Anonymous
I mean, is it correct that the main term
using fractional calculus and this is simply why
for $\alpha-s>-1/2$ around x=0, since $ |x|^{\alpha-s}\in L_2 (0,1)$ ?
21 October, 2009 at 7:01 pm
Terence Tao
Yes; this can be done for instance using the machinery in the preceding lecture notes,
https://terrytao.wordpress.com/2009/04/19/245c-notes-3-distributions/
21 October, 2009 at 7:43 pm
Anonymous
Dear Professor Tao:
Let us define function f = the Heaviside step function. Your answer https://terrytao.wordpress.com/2009/04/30/245c-notes-4-sobolev-spaces/#comment-38496 implies that f is not in
, correct? Is there a direct reference?
Let’s the fun continue. Is it in
with s<1/2? What is
?
These are simple questions with very hard to find or figure out answers for non-experts, so your help is extremely appreciated.
20 December, 2009 at 12:46 pm
PDEbeginner
Dear Prof. Tao,
In exercise 3, it seems we need to time the function by the height
. In exercise 16, it seems that
is
.
[Corrected, thanks – T.]
5 January, 2010 at 3:38 pm
PDEbeginner
Dear Prof. Tao,
I think the condition in Ex 32 should be
.
I got stuck on prove the first step in your hint. I tried to use the Fourier inversion formula and the Cauchy-Schwartz inequalitie as in Ex 31, but this seems not to work. Could you give a little detailed hint.
Thanks in advance!
5 January, 2010 at 6:00 pm
Terence Tao
Thanks for the correction!
For Exercise 32, one uses the Hardy-Littlewood-Sobolev inequality (Corollary 7 from Notes 1) rather than Cauchy-Schwarz. I’ll put in a link to that corollary in the notes.
11 March, 2010 at 10:01 pm
anaon
The product rule for weak derivatives could be proven with the help of lemma 3 (i.e. C^\infty_c is dense in W^{k,p}) but here the proof uses the product rule :)
16 May, 2010 at 6:47 am
Simion
Dear Prof. Tao,
, given that for a function in such a space, there’s no decay requirement? For example, a constant function is in
, but can’t be approximated by a compactly supported one.
Perhaps I’m terribly wrong, but how can in Exercise 13 compactly supported functions be dense in
16 May, 2010 at 7:39 am
Terence Tao
Oops, you’re right. I’ve replaced
with
in the exercise.
30 June, 2016 at 2:03 pm
Anonymous
I can only tell from other resources that
is defined as the closure of
in
. I have also checked the index section of your book but I cannot find a definition. How do you define
in this note?
[See the paragraph immediately preceding Exercise 13. -T.]
23 May, 2010 at 11:39 pm
wrf
Dear Prof. Tao,
I have thought about a problem about the gagliaedo-nirenberg interpolation inequation. I want to know if it holds for the frational
derivative.
a chinese student
6 November, 2010 at 1:46 pm
xuhmath
I think there is a typo on Exercise 16: did you mean “the function
has a
norm” rather than “the function
has a
norm” to emphasize the contrast with Exercise 3?
[Corrected, thanks – T.]
18 November, 2010 at 12:25 pm
anthony
Dear Prof. Tao,
it should be Rellich-Kondrashov not Kondrakov. [Corrected, thanks. The exact Romanisation of Kondrachov seems to be somewhat in dispute, but “ch” seems to be slightly more common than “sh” in this case. – T.]
19 November, 2010 at 6:58 am
anthony
I’m pretty sure this is because of the influence of the classical book of Adams. As someone who actually speaks Russian I still think that Kondrashov is the correct english Romanisation because it produces the right pronunciation of russian “ш” (like in SHow) whereas “ch” (like in CHeck) corresponds to russian “ч”. The actual russian spelling is “Кондрашов”.
See http://en.wikipedia.org/wiki/Sobolev_inequality
[Thanks for the clarification. I confirmed this with a Russian friend of mine, and corrected the spelling. -T.]
12 January, 2011 at 1:20 pm
Abhishek
Dear Prof. Tao,
I am wondering if there is any inverse theorem for Sobolev embedding, namely when
is embedded in
.
12 January, 2011 at 1:23 pm
Abhishek
Sorry, I meant when
is embedded in
. Can something like this be said in high dimensions?
13 January, 2011 at 3:40 am
Terence Tao
In general, spaces with lower regularity cannot be embedded into spaces with higher regularity (the computation in Exercise 16 already shows this). I talk a bit about the general embedding relationships between function spaces in
https://terrytao.wordpress.com/2010/03/11/a-type-diagram-for-function-spaces/
There is however something called an inverse theorem for Sobolev embedding, but it is a bit different, referring to a classification of those functions f for which the Sobolev inequality is close to equality (roughly speaking, this occurs when f looks like a rescaled bump function). This is inverse theorem important in the theory of concentration compactness; see e.g. Proposition 4.9 of http://www.math.ucla.edu/~visan/ClayLectureNotes.pdf
21 April, 2011 at 7:26 am
timur
Just to complement what prof. Tao said; you can of course embed certain subspaces (e.g. with compactly supported Fourier transform) of L^q into e.g. H^k, with the constant blowing up as the subspace gets larger. These are called inverse- or Bernstein-type inequalities, and very useful in approximation theory and numerical analysis. The complementary inequalities are called direct- or Jackson-type estimates, and these concern subspaces e.g. with Fourier transform supported in a complement of a compact set, and the inequality sign is reversed (so compatible with the usual embedding theorems) as compared to the inverse estimates. The difference between direct-type estimates and the usual embedding theorems is that in direct estimates the constant tends to 0 as one removes larger and larger compact sets from the support of the Fourier transform.
22 February, 2011 at 1:26 pm
Sobolev spaces on manifolds « Secret Blogging Seminar
[…] Tao has a very comprehensive blog post on this, so I’ll be […]
21 April, 2011 at 3:36 pm
anonymous
Dear Prof. Tao,
What is known for Sobolev inequality on T^d (d-dimensional torus)? And, what would be a good reference? Also, on Riemannian manifolds?
Thank you.
22 April, 2011 at 11:29 am
timur
Emmanuel Hebey has a book on Sobolev spaces on manifolds, and I found that Palais’ seminar notes on the index theorem has many details worked out. But I would say the manifold case is not much different once you figure out how to transfer from local to global by using partitions of unity, and how this is equivalent to defining Sobolev spaces via covariant derivatives for integer indices. This is my quick answer; others will surely have deeper answers than mine.
1 September, 2011 at 6:15 pm
254A, Notes 1: Lie groups, Lie algebras, and the Baker-Campbell-Hausdorff formula « What’s new
[…] functions, but much stronger than the class of singly continuously differentiable functions. See this previous blog post for more on these sorts of regularity classes. The reason for the terminology in the above […]
16 December, 2011 at 10:51 am
254B, Notes 3: Quasirandom groups, expansion, and Selberg’s 3/16 theorem | t1u
[…] See for instance this blog post for a very brief introduction to Riemannian geometry, and these two previous posts for an introduction to distributions and Sobolev […]
20 December, 2011 at 7:11 am
254B, Notes 3: Quasirandom groups, expansion, and Selberg’s 3/16 theorem « What’s new
[…] See for instance this blog post for a very brief introduction to Riemannian geometry, and these two previous posts for an introduction to distributions and Sobolev […]
19 January, 2012 at 7:33 pm
Seungly Oh
Concerning Exercise 18, shouldn’t
closure of
should be something like
?
[Corrected, thanks – T.]
28 April, 2012 at 3:47 pm
Rex
In the statement of exercise 3, do you mean to call your frequency scale
instead of
? I don’t see any
in the function.
28 April, 2012 at 4:24 pm
Terence Tao
Yes, in this example the frequency scale
will be
.
30 April, 2012 at 8:50 pm
Jack
Dear Prof. Tao,
either in the note or in the index of your book. Do you mean
?
I can’t find the definition for
1 May, 2012 at 5:21 am
Terence Tao
30 April, 2012 at 9:16 pm
Jack
This might be a stupid question:
As the wikipedia said, embedding is a structure-preserving map. What structure is preserved in the “Sovolev embedding”? Is it the structure of normed vector space? Or other “structures”?
1 May, 2012 at 5:25 am
Terence Tao
The Sobolev embedding preserves the convergence of sequences (i.e. it is a continuous map) and the vector space structure (i.e. it is linear), but it does not preserve the norm (i.e. it is not an isometric embedding). Note though that the topology of the embedded space is a bit stronger than that of the ambient space; when
, there are sequences in
that converge in
norm but not in
norm. So, strictly speaking, it doesn’t fully preserve the topological structure (instead, it makes the topology a little weaker upon embedding), but it is still customary to abuse notation slightly and refer to this map as an embedding.
4 May, 2012 at 11:17 am
Jack
Hmm, any hint for finding sequences in
that converge in
norm but not in
norm?
29 July, 2012 at 1:03 pm
karabasov
Dear Prof. Tao,
can you, please, give references about Sobolev product theorems, like one in Exercise 27?
Thank you very much,
karabasov
29 July, 2012 at 10:05 pm
Terence Tao
Taylor’s “Tools for PDE” develops the theory of paraproducts, from which Sobolev product theorems can be deduced as corollaries.
22 August, 2012 at 2:38 pm
hassan jolany
What is the Schauder estimate on the space time Reimannian manifold in parabolic differential equation, ? (I mean on usual Hölder space )
29 December, 2012 at 1:04 pm
A mathematical formalisation of dimensional analysis « What’s new
[…] In fact, this condition turns out to be sufficient as well as necessary, although this is a non-trivial fact that cannot be proven purely by dimensional analysis; see e.g. these notes. […]
31 March, 2013 at 6:02 pm
anonCoward
I found the notation employed throughout this post to be a departure from the norm. Did you intend to write
[Corrected, thanks – T.]
7 November, 2013 at 5:36 am
functions in Holder space | Question and Answer
[…] I came up with this while I was reading this https://terrytao.wordpress.com/2009/04/30/245c-notes-4-sobolev-spaces/ […]
2 December, 2013 at 2:37 am
zuchongzhi
Reblogged this on Diary of a budding mathematican and commented:
Very nice article!
5 December, 2013 at 4:25 pm
zuchongzhi
Dear Professor Tao:
May I ask a hint to prove (III) in Exercise 14? After establishing (II), I found I could not establish (III) rigorously at the singularity
. Since I have
, I cannot cancel out the singularity as I have
at the bottom for
after introducing a cut off function
. I am hoping the part within the ball should vanish as
.
5 December, 2013 at 8:16 pm
Terence Tao
As suggested in the hint, you should first try the cases when f vanishes at x, or when f is constant in a neighbourhood of x. (The easiest case of all is when f vanishes in a neighbourhood of x, although this case is not large enough to be of much use by itself.)
6 December, 2013 at 3:26 pm
zuchongzhi
I understand. I think you mean to expand f(y)=f(x)+g(y-x), with g(y-x) vanishes at x, and f(x) a constant. The integration then gives me 0 by symmetricity.
27 April, 2014 at 6:44 am
Fan
There is comment “Many of these cases can be obtained from the endpoints already established by interpolation, but unfortunately not all such cases can be, so we will treat this case separately” in the proof of the embedding theorem. I can’t see what case isn’t covered by interpolation. If we fix
, then the allowed
is an interval, and we have already established two endpoints. Shouldn’t interpolation give us the whole interval?
27 April, 2014 at 7:09 am
Terence Tao
In some cases, the relevant interval is open (or half-open) rather than closed, so at least one of the endpoint estimates are not available.
27 April, 2014 at 1:43 pm
Fan
On the RHS of the last equation of Exercise 21, is it
norm instead of
norm?
[Corrected, thanks – T.]
27 April, 2014 at 5:39 pm
Fan
Sorry, but there is another
which should be
on the LHS of the last but one equation in Lemma 4.
[Corrected, thanks – T.]
24 November, 2014 at 4:02 am
eli
Your notes are really interesting. I’m wondering if you could suggest me a book or something similar for taking a look deep in this argument.
Thanks for your attention.
6 November, 2015 at 10:44 am
Anonymous
Is there a particular reason that this note works only in
instead of the general open subset
for
?
[See the discussion after Exercise 12. The loss of global tools such as the global Fourier transform is one key reason why the theory of Sobolev spaces on domains is significantly more subtle, particularly at or near the boundary, than global Sobolev spaces, although many of the techniques used in the global case can be adapted to some extent for more general domains, after some effort. -T.]
7 November, 2015 at 8:12 am
Anonymous
In the Navier-Stokes Equations by Constantin and Foias, there is a proposition says that
Let
satisfy the segment property. Then
is dense in
, for
.
There is no explanation for the notation
in that old book. Do you think it is the same as
in this note?
(Also, these two function spaces in the proposition have totally different domains, how can one be a subset of the other one?)
Can one understand in general that
is the "closure" of
?
As you put in the comment of a question recently asked under your post "function spaces", one should really focus on the mathematical ideas instead of the human-invented notations. So what is the essential idea for
and
here? I have a vague idea that we have two different behaviors (properties) of functions: having compact support (in the domain
or the whole space
^d?) and "vanishing" on the boundary (or infinity?). They are related to each other by taking closure in some topological space. Am I right?
8 November, 2015 at 3:55 pm
Terence Tao
I don’t know the notational conventions of Constantin and Foias, but they may be referring to the space of smooth functions that are compactly supported in
. Even if their notational conventions are absent or not completely accurate, one can jump ahead to the portion of the book where that proposition is actually used, to get some idea of what they were trying to do. (See also this previous article of mine on how to read mathematical texts.)
28 May, 2019 at 6:27 am
Anonymous
The excellent article on Google plus is unfortunately no longer available. Are you going to repost it somewhere else?
[Link updated – T.]
1 December, 2015 at 7:51 pm
Anonymous
Suppose that
the following Schauder estimates holds:
,
. Can we use some interpolation theorem to get
? Many thanks!
1 December, 2015 at 8:38 pm
Terence Tao
I doubt it, given that the inverse
to the Laplacian (on, say, a torus) obeys the first two estimates but not the third (
is bounded on Holder spaces, but not on
).
8 December, 2015 at 6:40 am
Charles Banqust
Is the function sin(x) on any sobolev space H^s(R)? Remember that the Fourier transform of sinx is (delta_{-1}-delta_1) /2i.
11 December, 2015 at 11:06 am
Anonymous
Do have a quick example to illustrate what you say in the beginning?
… a first derivative
of a function in an
space usually leaves all Lebesgue spaces, but a first derivative of a function in the Sobolev space
will end up in another Sobolev space
.
11 December, 2015 at 11:42 am
Terence Tao
Consider for instance the function
, where
is a smooth bump function equal to 1 near the origin. This function lies in every
space for every finite
, but it’s (weak) derivative blows up like
near the origin, and so will exit all the
spaces with
.
for someon15 May, 2016 at 5:21 pm
Anonymous
Why would
not blow up at
(Would you elaborate why it is in
)? Maybe I’m missing something. Did you mean something in
the function
for some (?) on 
[Corrected, thanks.
does diverge very slowly at
, but not enough to destroy integrability:
is locally absolutely integrable for any
. -T.]
11 December, 2015 at 11:49 am
Anonymous
Maybe I miss something in previous notes. I’m always confused about the concept “embedding” in the context of this note. Let
and
be two topological space. If there exists
such that
is a homeomorphism, then we say
embeds in
, right?
In Theorem 3,
…
embeds continuously into
.
Would you elaborate what “embeds continuously” precisely mean (and what does it mean “not embeds continuously”)?
When people write
how shall I understand “
“? Does it just mean “is a subset of”? The topologies of the two spaces on the two sides of “
” are different, why would the “inclusion” be interesting?
11 December, 2015 at 12:32 pm
Terence Tao
The precise definition of “embedding” depends on what category one is working in, but it usually means that there is an injective map that respects the relevant structure of the spaces one is working with. In the case of function spaces, this usually means an injective map that is linear and continuous (though one can ask for stronger embeddings, such as a bicontinuous, bilipschitz, or isometric embedding). In many cases, the embedding is given by an inclusion map (possibly after performing some standard identifications, e.g. identifying a locally integrable function with the associated distribution, or identifying a continuous function with the equivalence class of functions equal almost everywhere with that continuous function). In such cases, the former space
can be viewed as a subset of the latter
, so we often use
to denote the embedding in those cases.
In the case of the Sobolev embedding
, the embedding is given by the inclusion map, and is linear and continuous (but not bicontinuous). The continuity of the Sobolev embedding is equivalent to the
topology being stronger than the
topology on
.
20 December, 2015 at 2:26 pm
Anonymous
Let
be the space (without topology)
where
is a nonempty open connected subset of
.
It is said in the Navier-Stokes Equations by Temam that the closure of
in
and in
are two basic spaces in the study of the Navier-Stokes equations. While it is quite clear what the closure of
in
means, I don’t quite understand later one.
By definition,
is
which is defined as
the closure of
in the Sobolev space
.
What is the convention for the topology of
?
Is the same as the topology of
so that the closure of
in
is the same as the closure of
in
?
One can write the closure of
in
as
How about the other one? Do we have a norm for
?
23 December, 2015 at 2:54 pm
Terence Tao
Generally, when taking the closure of a space in a normed vector space, the topology given to the closure is the topology induced from that normed vector space, thus for instance
will be given the topology from the
norm.
More generally, when reading a mathematical text (such as Temam’s), one can often deduce the answer to questions like this simply by reading ahead in the text until the point where the answer to the question becomes important (e.g. when one starts establishing or using convergence in the space in question). See my discussion on this at https://plus.google.com/u/0/114134834346472219368/posts/TGjjJPUdJjk
31 December, 2015 at 3:25 pm
Anonymous
I’m confused. Is
the dual space of
or the dual of
?
1 January, 2016 at 4:39 pm
Anonymous
Hmm, this is a bad question. What really confuses me is what is the difference between the dual space of
and the dual of $H^1(\Omega)$ where
is the closure of
in
. Are they the “same”?
11 January, 2016 at 1:41 pm
Anonymous
Let
be an open subset of
. If
, then by extending
to be identically zero outside
, one has
. Do we have in general the similar result for
and
?
[Not always. See e.g. https://en.wikipedia.org/wiki/Sobolev_space#Extension_by_zero -T. ]
13 January, 2016 at 5:26 pm
Anonymous
Ah, the problem is on the boundary. So can we say that if
, then
by extending $f$ to be identically zero outside
?
6 March, 2016 at 2:09 pm
Anonymous
I don’t quite understand Exercise 30 and the remark right before it. Are we saying that
and since
, Exericse 30 shows that
is reflexive?
7 March, 2016 at 12:34 pm
Terence Tao
All Hilbert spaces are reflexive.
One can identify
with
using the general identification
provided by the Riesz representation theorem for complex Hilbert spaces. Exercise 30 provides a different identification
that is based on the
inner product rather than the
inner product. (These two identifications are consistent with each other since
and
are isomorphic Hilbert spaces.)
7 March, 2016 at 3:24 pm
Anonymous
Let
be a domain in
. Denote
as the closure of
in
. In his Partial Differential Equations, Evans gives the “Hilbert triple” (Gelfand triple)

is the dual of
.
where one has that
This gives an identification of
with
instead of
. But
and
are two different spaces. Why does this not contradict Exercise 30?
Also, as you said in the comment (https://terrytao.wordpress.com/2009/01/17/254a-notes-5-hilbert-spaces/#comment-466686) to a question in 245B notes 5,
as sets, hence
as sets. How could one put a proper subset between
and
(where
in the quoted case)?
8 March, 2016 at 5:13 am
Terence Tao
When the domain
is
, then
has no boundary, and the spaces
and
coincide.
Also, it is better to think of isomorphic pairs such as
and
as being equivalent or identifiable rather than identical, as the latter can lead to some confusion if one treats too many of the equivalences as equalities. For instance,
and
are equivalent (one can simply shift the standard orthonormal basis for the former by one unit to obtain the latter), but one can also identify the latter space as a subspace of the former. It is fairly harmless to treat one of these equivalences as an equality, but of course one cannot do so for both equivalences at the same time.
4 April, 2016 at 4:36 pm
Jack
Would the proof lemma 2 be still correct if one replaces
with
? I don’t have an example to see the difference.
[Yes – T.]
4 April, 2016 at 4:50 pm
Anonymous
Then when one replaces
with arbitrary open subset
of
, say an open ball, Lemma 2 is also correct, right? It seems that the proof can remain the same.
5 April, 2016 at 2:25 pm
Anonymous
A quick search on Google returns the Meyer-Serrin theorem which says that
is dense in
. Also, it is pointed out that one needs extra conditions for
if one want Lemma 2 be true when
is replaced with
. Looking at the proof of Lemma 2 again, I still don’t know which part would break down for general arbitrary open sets.
19 April, 2016 at 2:32 am
ll314159
Exercise 24 indicates that if
, then
, is it only for the purpose of the exercice or is it because the sobolev embedding is false in this case? Is it not the same embedding as the one indicated in Exercise 26 ? (Using the definition
)
19 April, 2016 at 9:58 am
Terence Tao
Exercise 24 fails at the double endpoint, for the same reason that Exercise 26 fails when
; see Exercise 20.
15 May, 2016 at 5:11 pm
Anonymous
Does the “width” of a function really mean “support” of a function in the beginning of this post?
…While
is, strictly speaking, a smooth function, it becomes increasingly less smooth in the limit
; for instance, the derivative
grows at a roughly linear rate as
, and the higher derivatives grow at even faster rates. So this function does not really have any regularity in the limit
.
What kind of “limit” should one understand in the discussion above at the beginning of this post? Or it doesn’t really matter?
15 May, 2016 at 5:46 pm
Terence Tao
The limit is in an informal sense for the purpose of the introductory discussion. By width, I refer to the measure of the support (so the width is a number, while the support is a set).
15 May, 2016 at 5:36 pm
Anonymous
In Exercise 3, I think you mean
… Thus we see how the
norm relates to the height…
[Corrected, thanks – T.]
15 May, 2016 at 5:44 pm
Anonymous
In Exercise 3, why “in particular how the width
is largely irrelevant”?
The norm is of at most
and
, so
should be relevant but
is not (since
does not appear in
)?
15 May, 2016 at 5:49 pm
Terence Tao
The frequency scale
is the order of magnitude of
, so the norm is comparable to
, which is an expression which is only barely connected to
through the bound
.
15 May, 2016 at 6:42 pm
Anonymous
…whose norm is given by the formula
where we view
as a rank
, dimension
tensor with complex coefficients (or equivalently, as a vector of dimension
with complex coefficients)
I just tried to read the scary lengthy article in Wikipedia (https://en.wikipedia.org/wiki/Tensor) to understand what is a tensor. That article says that an
tensor is an element of the tensor product (of vector space and its dual)
where there are $n$ copies of
and
copies of
.
Would you explain what is a rank
, dimension
tensor (and why is
a such tensor?) and how does it relates to the Wikipedia definition?
16 May, 2016 at 8:33 am
Terence Tao
A rank
, dimension
tensor is an element of
, where there are
copies of
. In coordinates, this would be an expression of the form
, where the
are scalars. A rank 0 tensor is a scalar, a rank 1 tensor is a
-dimensional vector, a rank 2 tensor can be viewed in coordinates as a
matrix, and higher rank tensors can more generally be viewed as hypermatrices.
The specific tensor
is the rank
, dimension
tensor with coefficients
.
is just
,
is the gradient of
at
,
is the Hessian matrix, and so forth.
15 May, 2016 at 7:28 pm
Anonymous
In building up the Gagliardo-Nirenberg-Sobolev inequality, one asks whether we can establish an estimate of the form
for certain constants
and
. By plugging in the inequality with the rescaled function
, one could have a motivation for the Sobolev conjugate of
.
Do we have similar motivation for those fractions in the statement of Theorem 3?
[Yes; see Exercise 23. -T.]
21 May, 2016 at 9:50 am
Anonymous
At one extreme, one has the space
, defined as the space of
times continuously differentiable functions
whose Hölder norm
is finite;
Do you mean
or
In what sense is this the “maximal” choice? Is it in the sense of sets as
21 May, 2016 at 11:57 am
Anonymous
In the remark after Exercise 12, is the following definition (I’ve seen in other places before but I can’t figure out if it is equivalent to the one in this note) for
equivalent to the one in the post (when
)?
Define when
,
(Can one defined
in a similar way as above when
so that one has some sort of “continuous extension to
for ‘
‘ “?)
21 May, 2016 at 12:03 pm
Anonymous
I guess this might relate to the Whitney’s extension problem, but I’m not sure about the details.
31 May, 2016 at 6:55 pm
Anonymous
I saw some books (e.g. Hunter’s Applied Analysis) define
as the space of all tempered distribution
such that (1) the Fourier transform
is a regular distribution (i.e. there exists some continuous or Lebesgue measurable function
such that
and the distribution is represented by
); (2) the distribution
lies in
. In this post, only (2) is given. Are these two definition equivalent?
28 June, 2016 at 4:43 pm
Anonymous
In Exercise 13,
Show that
is a dense subset of
…
Isn’t it true by definition of
? Do you mean
instead?
3 July, 2016 at 4:20 pm
Anonymous
My question is rather elementary:
In the motivation of the definition of the space
, you mention a key estimate
Would you elaborate how one can build up such inequality?
[Try checking the cases
and
separately. You can try the one-dimensional case first if you are not comfortable with working with multi-indices. -T.]
4 July, 2016 at 2:23 pm
Anonymous
Using the binomial theorem, one has
On the other hand,
Now take
Then
In the higher dimensional case, I guess the multinomial theorem would work.
It seems that you have an easy way to handle it by considering separately
and
. Would you elaborate?
5 October, 2016 at 5:31 am
Anonymous
I don’t quite understand the comment above. Why checking the cases separately would help. Don’t they give one half of the inequality but one needs the two inequalities both true for all
?
[One can prove both inequalities in the
case, and prove both inequalities in the
case, and these four facts together give the full claim. -T.]
3 July, 2016 at 5:09 pm
Anonymous
Typo in the line
Also, we know that the Fourier transform of any derivative
of
is
.
[Corrected, thanks – T.]
3 July, 2016 at 5:36 pm
Anonymous
The following part of the argument is a little confusing for me:
A similar argument then gives
By definition,
When applying the Plancherel, should the right hand side be
[Not quite: firstly,
should be equal to
, not less than or equal to
; the
factor should be raised to a power of
; and a multinomial coefficient
is missing. You might try first a small numerical example, e.g.
. -T]
5 July, 2016 at 3:00 pm
Anonymous
In Definition 1
is said to lie in
if its weak derivatives
exist and lie in
for all
…
A function
can one replace “A function” with “A distribution”, and “weak derivatives” with “distributional derivatives”?
Why do we need
to be at least locally integrable or is it forced to be so?
[From H\”older’s inequality, elements of
are automatically locally integrable for any
– T.]
5 July, 2016 at 3:17 pm
Anonymous
the space
Given a tempered distribution
, according to the definition in notes 2, its Fourier transform
is again a tempered distribution, which is a linear functional on the Schwartz space. By the definition in Notes 3,
is another tempered distribution. Must it be a locally integrable function? Why does it make sense to talk about a linear functional being in
?
[As in the previous comment, every
function is locally integrable and is hence a distribution. Of course, the converse is not true: most distributions are not locally integrable, and hence most distributions are not
. But some of them are. -T.]
5 July, 2016 at 10:05 pm
Anonymous
If
, then
is in
by definition. Does the comment also suggests that
is in
too? (Or how “bad” it could be?)
6 July, 2016 at 8:58 am
Terence Tao
If
and
is in
, then
is also in
. If
is negative, this is no longer necessarily the case, but
will still locally be in
.
6 July, 2016 at 4:29 pm
Anonymous
I don’t understand the point of Exercise 29.
We already conclude that
Why we only see
embeds into
?
that
Why it is not immediate that
?
6 July, 2016 at 5:00 pm
Terence Tao
The equivalence
was only established in the notes for
. To complete the proof that
, one must also verify the equivalence when
.
26 September, 2016 at 5:30 am
Anonymous
The Gagliardo-Nirenberg-Sobolev inequality (https://en.wikipedia.org/wiki/Sobolev_inequality#Gagliardo.E2.80.93Nirenberg.E2.80.93Sobolev_inequality) gives an embedding
when
is the Sobolev conjugate of
. This inequality can be proved using Hölder repeatedly. Can Theorem 3 be directly implied by this inequality?
[Yes – T.]
27 September, 2016 at 7:50 am
Anonymous
I can see that the GNS inequality implies the case where
. Why does it also imply the case where
is such that
?
27 September, 2016 at 8:10 am
Terence Tao
In that case one needs the more general form of the Gagliardo-Nirenberg inequality.
29 September, 2016 at 9:18 am
Daniele Gerosa
Dear Professor Tao,
in “Caratterizzazioni delle tracce sulla frontiera relative ad alcuni classi di funzioni in $n$ variabili” E. Gagliardo says that the problem of characterizing functions defined on the boundary of a suitable domain $\Omega$ which are traces of functions in Sobolev spaces was solved, in different ways, just for $p=2$ (e.g. N. Aronszajn, “Boundary values of functions with finite Dirichlet integral” or V. M. Babich & L. N. Slobodetskij, “On boundedness of Dirichlet integrals” (in russian)). Do you know any reference in which that case is treated and proved? The two I quoted between brakets are for me scarce, even in/from the library of my university. Basically, for an “historical purpose”, I’m looking for the proof(s) of the Trace Theorem for Sobolev Spaces ( https://en.wikipedia.org/wiki/Sobolev_space#Traces ) in the specific case of $p=2$; I think it relies on Fourier Transforms Theory
5 October, 2016 at 8:13 am
Anonymous
In exercise 36, in the LHS of the definition of the symbol
, it seems that
should be
. Also,
in the LHS of the next displayed inequality can be complex, so perhaps it should be replaced by its absolute value.
[Corrected, thanks – T.]
15 October, 2016 at 5:33 am
Anonymous
This might be a dumb question but I don’t quite get it.
Is the norm

?
equivalent to
[Yes. Try the
case first, using the fundamental theorem of calculus to estimate differences such as
. -T.]
15 October, 2016 at 10:45 am
Anonymous
In lemma 2, can the proof be used almost without modification to show that
is dense in
when
is a nonempty bounded open subset of
?
—-
in
for
being bounded in a very complicated way. He first established the approximation in
and then uses the partition of unity to put things together.
I ask this question since I saw in Evans PDE book proves the density of
However, in Lemma 2, the method seems much more straightforward: all one needs to do is just do the convolution with the standard mollifier on the whole domain
. No problem on the boundary since
.
15 October, 2016 at 11:39 pm
Terence Tao
Convolution with a mollifier has to be done with care when working on a domain
, since the convolution may end up not being supported in
(also, one has to somehow extend a function on
to a function on
before the convolution becomes well defined, and such an extension might not continue to lie in
).
25 October, 2016 at 3:49 am
Karim
Dear professor Tao,
, can i conclude immediately that
, where
and
(the Gevrey class
regularity)??
I have a question that is not very related to the aformentioned basic Sobolev chapter. But instead, it still related to Sobolev spaces framework which is the following:
Let is suppose that i have a function
15 December, 2016 at 6:44 pm
Anonymous
Dear professor Tao,
I have a question about Exercise 13.
For me it seems that there is a counter-example which cannot be approximated by test functions.
Say alpha=1/2, and f(x)=sqrt{|x|}. Then its “alpha-derivative” at x=0 is 1/2
but for every smooth function the derivative at 0 exists but must be 0.
So I think that the Holder norm between f and any test function is at least 1/2 in this case.
(We can make f compactly supported by replacing f with max{1-f,0})
I tried to prove Exercise 13 but I don`t see how being compactly supported is used.
Could I get some hints?
16 December, 2016 at 7:26 am
Terence Tao
Oops, you are right, the exercise as formulated is not correct. I have revised the exercise accordingly.
11 April, 2019 at 12:26 am
Wang Cong
Dear professor Tao,
excuse me, I want to ask you that, is C^\infty_0 dense in D^{1,2}(\Omega)? where \Omega is bounded, D^{1,2}(\Omega)=\{u\in L^{2^*}(\Omgea),u\inL^2{\Omega} . thanks.
11 April, 2019 at 3:11 pm
Terence Tao
Not when
has a non-trivial boundary, because the Sobolev trace theorem provides an obstruction. (Assuming that the boundary is sufficiently nice, of course.)
24 December, 2016 at 12:57 am
Anonymous
Dear professor Tao,
About Exercise (iii) of the Schauder estimate I am struggling to show LHS=RHS with the Lebesgue dominated convergence theorem but I couldn`t find an appropriate dominant function which is integrable. For part (ii) I was able to choose such functions but it also was not pretty. So I doubt that the theorem is the right key but I have nothing else. If I can get some directions they will be very helpful.
I also have a difficulty in showing that RHS is alpha-continuous. I mainly used the inequality
Plugging it into the difference
and diving the integral region
into
and
(M a large constant) and using the above inequality according the two intervals, I got the upper bound
Is there a smarter way to get the desired result? Or, am I missing some essential points?
24 December, 2016 at 4:52 pm
Terence Tao
I doubt there is an easy way to establish (iii) purely through the dominated convergence theorem. If f(x) vanishes, then one can split the Newton quotients converging to the LHS into two terms, a “global part” one of which will converge to the RHS by dominated convergence, and a “local part” which one can show to be small using the Holder continuity of f and the vanishing of f(x). One then has to treat the complementary case when f is constant near x by a different argument involving explicit calculation of the local portion of the integral.
For the Holder continuity, one should be exploiting the regularity of the kernel
rather than of
to handle the global part, since it is the smoother of the two factors.
8 January, 2017 at 7:36 am
Anonymous
Dear professor Tao,
should be revised to
, the space of
functions whose all j`th gradients go to zero as away from the origin, for the constant function 1 cannot be approximated by compactly supported functions in the uniform norm.
In Exercise 24 I guess the space
[Corrected, thanks – T.]
23 January, 2017 at 7:04 pm
Student
Dear prof. Tao,
, a_n to be determined later for the purpose, but
is equivalent to
, which is greater than
. So this example seems to fail (unless I made a mistake).
to make the infinity norm large, but the result was the same.
I am trying to prove the Sobolev embedding fails when (p, q)=(d, infinity), d>1 (Exercise 28). As suggested I tried with
I gave another shot with the function
Could you give me some directions?
[You have to use constructive interference between the
, say at the origin
, to make the
norm of
large. -T.]
8 February, 2017 at 4:43 pm
Anonymous
In Exercise regarding L^p Holder spaces, I am stuck in (i) to show
. For the other inclusion it was easy to use the inequality
up to a multiplicative constant depending only on alpha and dimension, but I don`t see how to approach the reverse direction with epsilon. I expected some inequalities like
, again up to a constant, but none of them are true or inadequate.
Can I get a hint or a useful inequality about this?
9 February, 2017 at 10:21 pm
Terence Tao
One has lower bounds of the form
(say) for small
, say
. This is enough to control the Fourier transform of the function on dyadic shells such as
by using the H\”older property for some well chosen set of shifts depending on
, and then one can sum in
to control the Sobolev norm. (The small frequencies in which
can be treated using the other component of the H\”older norm.)
11 February, 2017 at 2:27 am
Anonymous
Dear Professor Tao,
Can we define the Sobolev norm of a function f on a bounded, open domain by taking the inf of the sobolev norm of functions which restriction to the domain is f ?
[This does define a norm, but not necessarily the norm one wants. See the discussion after Exercise 13. -T]
18 February, 2017 at 12:43 am
Anonymous
Dear professor Tao,
In the Exercise of Sobolev trace theorem I proved it by Cauchy-Schwartz inequality, namely,
but I couldn`t see how the schur`s lemma is used.
Also that multiplication by
is continuous, the next Exercise, was also hard. I think I don`t understand the same thing.
Can I get some hint for this?
[You’re right, Schur’s test is difficult to use for the second exercise; I’ve modified the hints accordingly. -T.]
14 March, 2017 at 11:57 am
Salim Benarous
Dear T.Tao ,
What about homogeneous Sobolev spaces , relations(in terms of estimates) between homogeneous and classical and why thoses spaces are often used in PDE?
9 April, 2017 at 5:27 pm
Anonymous
How should one define the Sobolev space
for
? (One can define
and
. How can one put them together?)
6 December, 2017 at 1:45 am
Anonymous
Dear Prof. Tao,
be a bounded domain of
with Lipschitz boundary. If
, such that
is continuously embedded in
. Is
continuously embedded in the dual space of
? Thank you very much.
Let
6 December, 2017 at 12:30 pm
Terence Tao
Yes, the only thing that needs checking is that the obvious map from
into this dual is injective, which amounts to showing that any functional arising from a nontrivial
function cannot vanish on all of
, which I think can be done by using for instance the Lebesgue differentiation theorem and smooth approximations to the identity.
7 December, 2017 at 7:26 am
Jane
Thank you very much!
23 February, 2018 at 5:31 am
Sobolev Holder question
Dear Prof. Tao,
is it true that C^s \subset H^s = W^{s,2}? I imagine that it is true but I cannot provide an argument. Thanks in advance.
24 February, 2018 at 8:08 am
Terence Tao
Yes if one has a compact domain, but not in general. One can already see this at the
level where the question is whether
embeds into
.
26 June, 2018 at 7:12 am
Paul Hager
I was confused by the definition “… to be the space of all tempered distributions
such that the distribution
lies in
…”
A distribution that lies in
implicitly means that the distribution is an “ordinary” function?
26 June, 2018 at 11:29 am
Terence Tao
Yes, we view
(or more generally,
) as a subspace of the space of distributions (see the remarks near Exercise 8 of the previous set of notes).
26 July, 2018 at 10:43 pm
Rajesh
Prof Tao,
“…as the very useful Sobolev embedding theorem, which allows one to trade regularity for integrability…”. Thats the use of Sobolev spaces. In this context, Fourier and Plancheral methods come very handy, when the corresponding Sobolev space is also a Hilbert space. But that is not always the case…. Only L^2 based Sobolev spaces are Hilbert spaces. According to Sobolev emebdding, if the function in R^d need to be holder continuous, then its gardient needs to be L^p integrable with p >= d+1. So for d >1, we need p > 2, so the associated Sobolev space cannot have a Hilbert space structure. So in this context, we cannot use Fourier Plancheral techniques. “But if” (stress If)… I say, that I can always find a Hilbert space, for any d, (even for cases when d>1), how useful a tool that it would be, in the context of PDE. What would the impact be? Any examples of PDE, on which there would be impact? Appreciate your valuable comments…
Thanks and Regards
Rajesh