advanced24 min studyLesson 389 in Mathematics

Rellich–Kondrachov compactness

Obtain strong subsequences from bounded Sobolev families and diagnose loss of compactness through concentration and translation.

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What you’ll understand

  • State compact embeddings strictly below the critical target with bounded-domain hypotheses.
  • Distinguish continuous embeddings, weak subsequences, and strong subsequences.
  • Use oscillation, concentration, and escape examples to locate failures of compactness.

A bounded energy sequence can still have infinitely many distinct shapes. Compact embedding says that the same sequence becomes manageable when viewed in a weaker target norm: some subsequence converges strongly there. This is the mechanism behind many existence proofs and limit passages in PDEs. The choice of target, the domain's boundedness, and the strictness of a critical exponent are all essential. A theorem about one weaker norm cannot be promoted to strong convergence of the original derivatives.

The target topology is part of the theorem

Let Ω⊂Rn\Omega\subset\mathbb R^n be bounded with Lipschitz boundary. If 1≤p<n1\le p<n, then W¹,ᵖ embeds compactly into Lᑫ for every 1≤q<p∗=np/(n−p)1\le q<p^*=np/(n-p). If p=np=n with n≥2n\ge2, every finite q is allowed. On a bounded interval, the endpoint W¹,¹ also embeds compactly into every finite Lᑫ, but generally not into L∞. If n<p<∞n<p<\infty, compactness holds in continuous functions with the uniform norm, and in Hölder spaces with exponent strictly below 1−n/p1-n/p. These statements mean every bounded source sequence has a target-convergent subsequence. The whole original sequence need not converge, and its limit need not have a chosen classical derivative.

A continuous embedding only bounds the target norm by the source norm. A compact embedding adds subsequential strong convergence and is therefore stronger. Reflexivity of W¹,ᵖ for 1<p<∞1<p<\infty can already provide a weak source subsequence, but weak convergence alone does not give norm convergence. Combining weak energy convergence with strong convergence of functions in a suitable Lᑫ target often permits nonlinear lower-order terms to pass to the limit. Derivative-dependent nonlinearities can require additional monotonicity, convexity, or compactness arguments; Rellich does not automatically settle them.

W1,p(Ω)⋐Lq(Ω)(1≤p<n, 1≤q<npn−p)W^{1,p}(\Omega)\Subset L^q(\Omega)\quad\left(1\le p<n,\ 1\le q<\frac{np}{n-p}\right)
The double inclusion symbol denotes compact embedding; bounded Lipschitz geometry and a strictly subcritical q are assumed.↔ Scroll wide equations horizontally.

Translation control explains compactness

For a whole-space W¹,ᵖ function, the difference between a function and its translation by h has Lᵖ norm at most ∣h∣∥∇u∥p|h|\|\nabla u\|_p. Prove this for smooth functions by the fundamental theorem along segments and then use density. A bounded energy family therefore has uniformly small translations. To obtain compactness, one also needs spatial tightness: the family cannot carry its mass arbitrarily far away. For a bounded Lipschitz domain, use an extension with support in a common bounded neighborhood, so both requirements hold.

The Lᵖ compactness criterion then provides a strongly convergent subsequence in Lᵖ. Continuous Sobolev embedding supplies a higher integrability bound, and interpolation upgrades convergence to intermediate subcritical exponents. Finite measure handles smaller exponents. This proof outline identifies why boundedness and domain geometry appear: one controls escape of mass, the other supplies a uniform extension. For a zero-boundary closure on a bounded arbitrary open set, zero extension can replace the Lipschitz extension step, yielding useful compactness versions without the same boundary regularity.

∥u(⋅+h)−u∥Lp(Rn)≤∣h∣∥∇u∥Lp(Rn)(1≤p<∞)\|u(\cdot+h)-u\|_{L^p(\mathbb R^n)}\le |h|\|\nabla u\|_{L^p(\mathbb R^n)}\quad(1\le p<\infty)
A common derivative bound controls small translations; a separate tightness condition prevents spatial escape.↔ Scroll wide equations horizontally.

Three different obstructions

High-frequency functions can prevent strong convergence in the original energy norm while disappearing in a weaker norm. For example, dividing a sine wave by its frequency makes its function L² norm tend to zero while its derivative L² norm stays fixed. Concentrating bumps instead demonstrate failure at the critical Lᵖ-star target: their supports shrink but their critical norms remain positive. Both examples are compatible with the subcritical theorem. They show that derivative order and critical scaling are concrete restrictions rather than technical qualifications to ignore.

On the whole space, translating a fixed compactly supported bump farther and farther away preserves all its Sobolev norms but can destroy strong Lᵖ compactness. Every fixed compact region eventually sees zero, yet the global norm remains unchanged. Local compactness may still hold, while global compactness fails through escape. In an existence proof, identify which obstruction a hypothesis rules out: confinement addresses translation, subcritical targets address concentration, and a weaker derivative order addresses high-frequency variation. Boundedness of one source norm alone cannot rule out every kind of loss.

Compact in L², not in H¹

On (0,2π)(0,2\pi) let uj(x)=sin⁡(jx)/ju_j(x)=\sin(jx)/j. Check its H¹ bound and L² limit, and show that no subsequence converges strongly in H¹.

  1. Orthogonality of integer sine and cosine modes gives ∥uj∥22=π/j2\|u_j\|_2^2=\pi/j^2 and ∥uj′∥22=π\|u_j'\|_2^2=\pi. Thus ∥uj∥H12=π(1+j−2)\|u_j\|_{H^1}^2=\pi(1+j^{-2}) is uniformly bounded.

  2. The function norm tends to zero, so the entire sequence converges strongly to zero in L². This is consistent with the interval compact embedding.

  3. For distinct positive integers j and k, the derivatives are orthogonal cosine modes. Therefore ∥uj′−uk′∥22=2π\|u_j'-u_k'\|_2^2=2\pi, so no subsequence is Cauchy in the derivative norm and none can converge strongly in H¹.

The result

The same bounded sequence is strongly convergent in the weaker function norm and noncompact in its original energy norm.

Explore the model

Interactive lab

Interactive lab · heat

Compare high-frequency decay at a common time

Pause and Reset; set mode n to 2 and diffusivity κ to 0.5, then Step once. Predict amplitude e−1e^{-1}. Reset, set n to 6 and κ to 0.5, and Step once; predict e−9e^{-9}. The common time is 0.5 in each run, so the larger frequency decays much more strongly.

Compare high-frequency decay at a common timeThe exact periodic heat-equation mode is u(x,t) = exp(−κn²t) sin(nx), on [0,2π]. Playback advances physical time. The initial sine is shown separately, and the unnormalized L² norm is √π exp(−κn²t). This analytic instrument does not run a finite-difference solver or test discretization stability. Current readings: Current amplitude: 1; Spatial L² norm: 1.772; Decay rate · κn²: 3.6 /s. All parameters are adjustable with the labeled controls below.Periodic heat equation mode 3 at time 0: the amplitude is 1.0π/2π3π/22π−1−0.500.51x · periodic intervalTemperature perturbation uExact mode · n = 3
Current temperature modeInitial sineCurrent amplitude
Current amplitude
1
Spatial L² norm
1.772
Decay rate · κn²
3.6 /s
t = 0 s

The exact periodic heat-equation mode is u(x,t) = exp(−κn²t) sin(nx), on [0,2π]. Playback advances physical time. The initial sine is shown separately, and the unnormalized L² norm is √π exp(−κn²t). This analytic instrument does not run a finite-difference solver or test discretization stability. Parameter changes pause playback and recompute the model at the current elapsed time. Reset restores both parameters and returns time to zero. Playback starts paused. Adjust either parameter, then choose Play or Step.

Look forExact heat damping suppresses high modes and illustrates why smoothing can aid compactness. The finite mode range and one-mode display do not prove a subsequence theorem or simulate concentrating bumps.

Check your understanding

What does compact embedding of W¹,² into L³ on a bounded Lipschitz domain in R³ imply?

Try it yourself

Take a nonzero smooth function ϕ\phi supported in the unit ball of Rn\mathbb R^n and set vj(x)=ϕ(x−3je1)v_j(x)=\phi(x-3je_1). Explain why this sequence is bounded in H¹ but has no strongly L²-convergent subsequence.

Take a moment to make a prediction or work it out on paper. Open a hint when you need one.

Give me a hint

Distinct supports are disjoint, so the squared norm of a difference is the sum of two identical squared norms.

Compare with the solution

Translations preserve both the function and gradient L² norms, giving a common H¹ bound. Centers are at least three apart, so the unit-ball supports of distinct terms are disjoint. Consequently ∥vj−vk∥22=2∥ϕ∥22>0\|v_j-v_k\|_2^2=2\|\phi\|_2^2>0 for every distinct j and k. No subsequence is Cauchy in L². This is spatial escape on an unbounded domain, not a contradiction of bounded-domain Rellich compactness.

Take it with you

  • Compact embedding promises a strong subsequence in a specified weaker target.
  • Translation control must be combined with spatial tightness.
  • Concentration, high frequencies, and escaping translations obstruct different overstrong compactness claims.

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