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Vanishing viscosity selects the Hopf--Lax solution for bounded data

Example

Let u0(x)=sin⁡x on R, a bounded uniformly continuous datum, and let H(p)=p2/2. For ε>0 and t>0 define uε(x,t)=−2εlog⁡ ⁣[(4πεt)−1/2∫Rexp⁡ ⁣(−sin⁡y+(x−y)2/(2t)2ε) dy], and set uε(x,0)=sin⁡x. Then uε is a bounded classical solution for t>0 of utε+12∣uxε∣2=εuxxε, and it attains u0 uniformly as t↓0. The Hopf--Lax function Qtu0(x):=inf⁡y∈R{sin⁡y+(x−y)22t},Q0u0=u0, is a bounded uniformly continuous viscosity solution of ut+12∣ux∣2=0 with initial trace u0, and for every T<∞ one has sup⁡x∈R, 0≤t≤T∣uε(x,t)−Qtu0(x)∣≤max⁡{εlog⁡(1+T), 2εlog⁡(8πε+2)}. Both terms on the right tend to zero as ε↓0. Thus the viscous solutions converge uniformly on every finite time strip. The estimate permits an O(ε∣log⁡ε∣) error and does not assert a uniform O(ε) rate.

Verification

Given: The datum u0(x)=sin⁡x, the Hamiltonian H(p)=p2/2 with Legendre transform L(v)=v2/2, all displayed integrals interpreted as absolutely convergent improper integrals of continuous functions, the heat kernel Γ(z,s)=(4πs)−1/2e−z2/(4s) (The heat kernel on Rn and its causal extension), the viscous equations and the Hopf--Lax function Qtu0 (The Hopf--Lax operator and the Hopf--Lax formula).

[F1] sin⁡′=cos⁡, ∣cos⁡∣≤1, ∣sin⁡x−sin⁡y∣≤∣x−y∣, and sin⁡ is bounded (The derivatives of sine and cosine are cosine and minus sine, Sine and cosine are 1-Lipschitz on R, Parity and the Pythagorean identity for sine and cosine).

[F2] The Gaussian integral and change of variable for improper integrals are The Gaussian integral ∫−∞∞e−x2 dx=π and Change of variable in an improper integral. The logarithm derivative is 1/x for x>0 (The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t), and the kernel is the explicit function of The heat kernel on Rn and its causal extension; the exponential derivative, chain and algebra rules are The exponential function is smooth and (exp⁡)′=exp⁡, The chain rule, in one line from Carathéodory: if g is differentiable at c and f is differentiable at g(c), then f∘g is differentiable at c with (f∘g)′(c)=f′(g(c)) g′(c) and Sums, scalar multiples, products and quotients: (f+g)′(c)=f′(c)+g′(c), (αf)′(c)=αf′(c), (fg)′(c)=f′(c)g(c)+f(c)g′(c), and (f/g)′(c)=(f′(c)g(c)−f(c)g′(c))/g(c)2 when g(c)≠0. On a compact (x,t)-neighbourhood with t>0, every required kernel derivative is bounded by a fixed polynomial-times-Gaussian function of y, integrable by comparison with a Gaussian. On each compact y-interval its difference quotients converge uniformly; the mean value theorem bounds their tails by that same integrable majorant. Splitting into this interval and its tail justifies differentiation under the improper integral without a Lebesgue change-of-variable theorem or a choice assumption (The mean value theorem, as the case g(x)=x of Cauchy's: for f continuous on [a,b] with a<b and differentiable on (a,b) there is c∈(a,b) with f(b)−f(a)=f′(c)(b−a)).

[F3] The quadratic conjugate is L(v)=v2/2 by completing the square in The Legendre transform of a finite-valued convex Hamiltonian. For the bounded uniformly continuous datum sin⁡, the infimum is attained (Finiteness, superlinearity of the Lagrangian and localisation of Hopf--Lax near-minimisers) and The Hopf--Lax formula solves the Hamilton--Jacobi Cauchy problem supplies the viscosity solution, finite-strip bounded uniform continuity, initial trace and uniqueness. At a differentiable minimizer the derivative is zero by Fermat's theorem: an interior differentiable local extremum has zero gradient. The semigroup is The Hopf--Lax operators form a semigroup (dynamic programming).

Proof technique: Cole--Hopf representation, an approximate-identity bound, and the variational reduction of the limit.

1.1F1F2algebra

The Cole--Hopf family solves the viscous equation. Write Wε(x,t):=∫RΓ(x−y,εt)e−sin⁡y/(2ε) dy. The substitution z=2εtr and ∫e−r2dr=π show ∫Γ(z,εt)dz=1, and the same substitution with the Gaussian tail shows that Γ(⋅,εt) is an approximate identity as t↓0. Differentiating the kernel gives ∂tΓ(⋅,εt)=ε∂xxΓ(⋅,εt), so by [F2] Wtε=εWxxε, Wε>0, and uε=−2εlog⁡Wε satisfies utε=εuxxε−∣uxε∣2/2, that is utε+∣uxε∣2/2=εuxxε, on t>0. The approximate identity applied to the bounded uniformly continuous function e−sin⁡(⋅)/(2ε) gives Wε→e−sin⁡x/(2ε) uniformly as t↓0, hence uε(x,t)→sin⁡x uniformly; and −1≤uε≤1 because e−1/(2ε)≤e−sin⁡y/(2ε)≤e1/(2ε) and the kernel has unit mass.

1.2F1F2F3algebra

Uniform comparison with Hopf--Lax. Fix x, t>0, put g(y)=sin⁡y+(x−y)2/(2t) and m=min⁡g=Qtu0(x), and take one minimiser y∗. Then −1≤m≤1, g′(y∗)=0, and g′′(y)≤A:=1+1/t. Applying the mean value theorem [F2] to g′ shows that the derivative of g(y∗+r)−m−Ar2/2 is nonpositive for r>0 and nonnegative for r<0; a second application gives g(y∗+r)≤m+Ar2/2. The full Gaussian integral therefore gives Wε(x,t)≥e−m/(2ε)/1+t, hence uε−m≤εlog⁡(1+t). Conversely, g−m≥0 everywhere, and g−m≥(x−y)2/(2t)−2. If ∣y−x∣≥8t, the latter is at least (x−y)2/(4t). Splitting the integral at this radius and using [F2] bounds its normalized ratio by em/(2ε)Wε(x,t)≤(4πεt)−1/2(28t+∫Re−(x−y)2/(8εt) dy)=8πε+2. Thus uε−m≥−2εlog⁡(8/(πε)+2). These two bounds hold for every x and t>0; at t=0 the functions agree. Taking their maximum for 0≤t≤T gives the stated absolute error bound. Its right-hand side tends to zero: writing s=1/ε≥1, the integral formula for the logarithm in [F2] gives log⁡s=∫1sdr/r≤∫1sdr/r=2(s−1), hence (log⁡s)/s→0.

2.1step 1.1step 1.2F1F3∎

The limit is the viscosity solution. By [F3] the function Qtu0 is a viscosity solution of ut+∣ux∣2/2=0; independently, since u0 is 1-Lipschitz with ∣u0∣≤1, the bounds u0(x)−t/2≤Qtu0(x)≤u0(x) hold (competitor y=x and the Lipschitz bound for sin⁡), so Qtu0 has the initial trace u0 and is bounded and uniformly continuous. The uniform estimate of step 1.2, whose right-hand side tends to zero, then gives locally uniform convergence of the viscous family to this viscosity solution without invoking a general vanishing-viscosity theorem and without a momentum-Lipschitz hypothesis.

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