Alphabeta Math
TheoremStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedprecheck passjudge pass (gpt-6.1-sol)
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

The viscous scalar Cauchy problem with smooth data has a global classical solution

Statement

Assume Countable Choice (CC) for the heat-kernel and L1 interfaces below. Let n≥1, ε>0, let f ⁣:R→Rn be C2 with f(0)=0, and let u0∈Cc∞(Rn). For every T>0 there is a mild solution u of ut+div⁡xf(u)=εΔuon Rn×(0,T),u(x,0)=u0(x), with u∈C([0,T];Cb(Rn))∩C([0,T];L1(Rn))∩C1,2(Rn×(0,T)). The solution is global in the sense that these solutions are compatible on finite time intervals; for every t∈[0,T], sup⁡x∈Rnu(t,x)≤sup⁡xu0(x),inf⁡x∈Rnu(t,x)≥inf⁡xu0(x). In particular it is bounded and remains in the initial range. No uniqueness beyond the constructed mild solution is asserted.

Facts & Assumptions

Given: Countable Choice, n≥1, ε>0, f∈C2(R;Rn) with f(0)=0, u0∈Cc∞(Rn), and T>0.

[F1]

The heat evolution Ht is the convolution with the heat kernel Γ: Htg=Γ(⋅,t)∗g is defined for g∈Lp with ∥Htg∥p≤∥g∥p, and Γ(⋅,t) has unit mass, is strictly positive, is C∞ with ∂tΓ=ΔΓ, and satisfies the Gaussian derivative bounds ∣DαΓ(x,t)∣≤Cn,αt−(∣α∣+n)/2e−∣x∣2/(8t) (The heat evolution Ht of initial data, Normalisation, parabolic scaling, heat equation and derivative bounds for the heat kernel).

[F2]

For every multi-index α and 1≤p≤q≤∞ there is Cα,p,q with ∥DαHtg∥q≤Cα,p,qt−∣α∣/2−n2(1/p−1/q)∥g∥p for all g∈Lp and t>0; moreover the spatial and time derivatives pass through heat convolution for positive time, and Young's inequality bounds convolutions (Spatial derivative estimates for the heat flow, Lp to Lq smoothing estimate for the heat flow, Spatial and time derivatives pass through heat convolution for positive time, Young's convolution inequality under Countable Choice).

[F3]

Htu0 is bounded and uniformly continuous with ∥Htu0∥∞≤∥u0∥∞, and C([0,τ];Cb(Rn)) with the supremum norm is complete: a uniformly Cauchy sequence of bounded functions converges pointwise in R, its Cauchy bound then gives uniform convergence and boundedness of the limit; uniform limits preserve spatial continuity. Applying the same argument to continuous paths with values in this complete Cb space gives a uniform limit continuous in time (the triangle inequality with one approximating path proves continuity). Thus this path space is complete, the uniform limit of continuous functions is continuous, and the Banach fixed point theorem applies to a contraction of a nonempty complete metric space (The heat Cauchy problem for bounded uniformly continuous data, The uniform limit of continuous real-valued functions on a metric space is continuous, Closed subspaces of complete metric spaces are complete; the converse under countable choice, A contraction of a nonempty complete metric space into itself has exactly one fixed point, the limit of the iterates from any starting point).

[F6]

Write BUC(Rn) for the bounded uniformly continuous functions. The Gaussian kernels form an L1 approximate identity, so Hεtg→g in L1 for g∈L1 by the approximate-identity theorem. For g∈BUC, define ωg(ρ):=sup⁡∣z∣≤ρ∥g(⋅−z)−g∥∞, which tends to zero with ρ. Unit mass and the Gaussian tail give ∥Hεtg−g∥∞≤ωg(ρ)+2∥g∥∞∫∣z∣>ρΓ(z,εt) dz, so Hεtg→g uniformly as t↓0. The Gaussian convolution identity Γt∗Γs=Γt+s follows by completing the square in its integrand and using Gaussian unit mass. The contraction and this identity give strong continuity of t↦Hεtg in both L1 and BUC on [0,τ] (Normalisation, parabolic scaling, heat equation and derivative bounds for the heat kernel, Every L1 approximate identity converges to the identity in Lp for 1≤p<∞). The product-space rearrangements use Fubini's theorem for L^1 functions on a sigma-finite product, kernel time integrations use The second fundamental theorem: if G is differentiable on [a,b] with G′=f and f is integrable, then ∫abf=G(b)−G(a), and the flux Lipschitz bound uses 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).

Proof

technique · direct
1.1F1F2F6

Setup and kernel estimates. Put M0:=∥u0∥∞, R:=2M0+1 and L:=sup⁡∣s∣≤R∣f′(s)∣<∞. Since f(0)=0 and f is C1, the mean value theorem gives ∣f(s)∣≤L∣s∣ for ∣s∣≤R. By [F2] there are constants C1,C2 with ∥∇Hσg∥p≤C1σ−1/2∥g∥p for p∈{1,∞}. The Gaussian first moment gives ∥Hσg−g∥∞≤C2σ1/2∥∇g∥∞ for g∈C1∩L∞ with ∇g bounded. Also, ∥∇Γσ(⋅+h)−∇Γσ∥1≤min⁡{2C1σ−1/2,C2∣h∣σ−1} and ∥Γσ(⋅+h)−Γσ∥1≤min⁡{2,C2∣h∣σ−1/2} for every h∈Rn and σ>0. For the scaled kernel, ∥∂σ∇Γεσ∥1≤Cεσ−3/2, so for Δ>0 and σ>0, ∥∇Γε(σ+Δ)−∇Γεσ∥1≤Cεmin⁡{σ−1/2,Δσ−3/2}.

2.1F1F3F6step 1.1

A local mild solution for bounded uniformly continuous L1 data. Fix a starting datum g∈BUC(Rn)∩L1(Rn) with ∥g∥∞≤M0. Choose τ0∈(0,T] with q:=2C1Lτ0/ε≤12 and let Xτ0:=C([0,τ0];Cb(Rn)) with the supremum norm (Closed subspaces of complete metric spaces are complete; the converse under countable choice). For v∈Xτ0 with ∥v∥Xτ0≤R define (Tgv)(t):=Hεtg−∫0t∇Hε(t−s)∗f(v(s)) ds. By [F6], t↦Hεtg is continuous in the supremum norm at t=0; by [F1] the Duhamel term is continuous in Xτ0, since its integrand is norm continuous for s<t and has the integrable majorant C1(ε(t−s))−1/2∥f(v(s))∥∞. The bounds ∥Hεtg∥∞≤M0 and ∥f(v(s))∥∞≤LR give ∥Tgv∥Xτ0≤M0+qR≤R,∥Tgu−Tgv∥Xτ0≤q∥u−v∥Xτ0. Thus Tg is a contraction of the closed radius-R ball; the Banach fixed point theorem gives a unique fixed point u∈Xτ0 satisfying u(t)=Hεtg−∫0t∇Hε(t−s)∗f(u(s))ds. The original datum u0∈Cc∞ satisfies these assumptions.

2.2F1F2step 1.1

Hölder regularity on strips. Fix 0<δ<τ0 and let t,t′∈[δ,τ0]. Since f(u) is bounded with ∥f(u)∥∞≤LR, the mild identity and the kernel bounds of step 1.1 give, for every α∈(0,1), ∥u(t,⋅+h)−u(t,⋅)∥∞≤Cδ∣h∣α,∥u(t,⋅)−u(t′,⋅)∥∞≤Cδ∣t−t′∣1/2. For the spatial estimate, ∥∇Hεtg∥∞≤Cε,δ∥g∥∞ on the strip. The Duhamel term is bounded by LR∫0tmin⁡{Cεσ−1/2,Cε∣h∣σ−1} dσ, with t≤τ0; splitting at σ=∣h∣2 gives at most Cε(∣h∣+∣h∣log⁡+(τ0/∣h∣2))≤Cε,τ0,α∣h∣α for 0<∣h∣≤1, where log⁡+(r):=max⁡{log⁡r,0}. Larger ∣h∣ are covered by boundedness of u. For the temporal estimate assume t=t′+Δ with Δ>0. The initial heat term is Lipschitz in t on [δ,τ0] by the positive-time estimate for ∂tHεtg=εΔHεtg. On the common Duhamel interval, with σ=t′−s, the kernel difference is a time difference and satisfies ∥∇Γε(σ+Δ)−∇Γεσ∥1≤Cεmin⁡{σ−1/2,Δσ−3/2}. Splitting its integral at σ=Δ gives ∫0t′∥∇Γε(σ+Δ)−∇Γεσ∥1 dσ≤CεΔ. The remaining time slab has norm at most LR∫t′tC1(ε(t−s))−1/2ds≤2C1LRΔ/ε. Thus both estimates hold with Cδ depending only on δ,τ0,ε,n,∥g∥∞,LR, and u is continuous in (t,x) for t>0.

3.1F2F5F6step 2.1

L1 continuity and identification of the limits. For the arbitrary starting datum g∈BUC∩L1 of step 2.1, take Picard iterates u(0):=g, u(k+1):=Tgu(k). By [F6], u(0)∈C([0,τ0];L1). If u(k)∈C([0,τ0];L1), the integral defining u(k+1) is defined by norm limits of Riemann sums on truncated intervals s≤t−η. Completeness supplies these limits, and the bound on the omitted interval is at most 2C1L∥u(k)∥CtL1η/ε, which tends to zero. Its integrand has integrable majorant C1(εs)−1/2L∥u(k)∥CtL1, so u(k+1) is L1-continuous and ∥u(k+1)∥CtL1≤∥g∥1+q∥u(k)∥CtL1≤2∥g∥1. Successive differences obey ∥u(k+1)−u(k)∥CtL1≤q∥u(k)−u(k−1)∥CtL1, so the iterates converge in the complete space C([0,τ0];L1) (Riesz-Fischer completeness of Lp for 1≤p≤∞) to some w. They also converge uniformly on [0,τ0]×Rn to the fixed point u of step 2.1. On every bounded ball Bm, this uniform convergence implies convergence to u in C([0,τ0];L1(Bm)), while the global L1 convergence gives convergence to w in the same local space. Uniqueness of the local L1 limit yields u=w a.e. on every Bm, hence a.e. on Rn; thus u∈C([0,τ0];L1) and ∥u(t)∥1≤2∥g∥1.

3.2F1F2step 2.1

The equation in distributions. Testing the mild identity and using Fubini (the bound (t−s)−1/2 is integrable on each finite time triangle) gives ∫Π(uφt+f(u)⋅∇φ)+∫gφ(⋅,0)=−ε∫ΠuΔφ. Indeed the initial heat term pairs as −∫gφ(⋅,0) against φt+εΔφ, and the divergence Duhamel term pairs as −∫f(u)⋅∇φ against the same expression, by integrating ∂tHε(t−s)=εΔHε(t−s) in t. Thus ut+div⁡f(u)=εΔu distributionally, with datum g.

3.3F1F2F4step 1.1step 2.2

Hölder continuity and boundedness of the spatial gradient. Fix 0<δ0<δ<τ0 and use the mild identity restarted at δ0: u(t)=Hε(t−δ0)u(δ0)−div⁡W(t),W(t):=∫δ0tHε(t−s)f(u(s)) ds. By step 2.2, f(u) is spatially Cα and temporally Cα/2 on each positive strip (the C1/2 bound implies the weaker Cα/2 bound). Componentwise, differentiation of the divergence heat potential gives ∂ku(t,x)=∂kHε(t−δ0)u(δ0,x)−∑i∫0t−δ0∫RnDkiΓεσ(z)(fi(u(t−σ,x−z))−fi(u(t,x))) dz dσ, where the frozen value is subtracted using ∫DkiΓεσ=0. Gaussian scaling gives ∥D2Γεσ∥1≤Cεσ−1, ∥∇D2Γεσ∥1≤Cεσ−3/2, and ∥∂σD2Γεσ∥1≤Cεσ−2. With the parabolic Cα,α/2 modulus of f(u), a spatial increment h is bounded after splitting at σ=∣h∣2 by C∫0∣h∣2σ−1+α/2 dσ+C∣h∣∫∣h∣2τ0−δ0σ−3/2+α/2 dσ≤C∣h∣α, and a time increment Δ=∣t−t′∣ is bounded after splitting at σ=Δ by C∫0Δσ−1+α/2 dσ+CΔ∫Δτ0−δ0σ−2+α/2 dσ≤CΔα/2. If either split point exceeds the finite integration horizon, the same bounds follow by increasing C. The heat initial term is smooth with bounded derivatives on t≥δ. Thus for each 0<α<1, [∇u]Cxα(Rn×[δ,τ0))+[∇u]Ctα/2(Rn×[δ,τ0))≤Cδ0,δ. These are seminorm bounds; in particular they establish continuity of ∇u before any absolute bound is used. The absolute gradient bound follows from boundedness of u. If ∇u(t,x)≠0, put e=∇u(t,x)/∣∇u(t,x)∣. Along the unit segment x+se, 0≤s≤1, the fundamental theorem of calculus and the spatial seminorm Mδ:=[∇u]Cxα give ∣∇u(t,x)∣≤∣u(t,x+e)−u(t,x)∣+∫01∣∇u(t,x+se)−∇u(t,x)∣ ds≤2R+Mδ1+α. Thus ∇u is bounded on the positive-time strip. Since f′′ is bounded on [−R,R], f′(u) has the same parabolic Hölder regularity as u there; hence h:=−f′(u)⋅∇u is bounded and belongs to Cα,α/2(Rn×[δ,τ0)).

4.1F1F4F5step 2.1step 3.3

Heat-potential cancellation and C1,2. Fix 0<δ<τ0, use the bounds of step 3.3 on a slightly larger positive strip, and restart the heat equation at δ. Then u(t)=Hε(t−δ)u(δ)+w(t),w(t,x):=∫δtHε(t−s)h(s)(x) ds. For σ>0, ∫RnDijΓεσ(z) dz=0, so cancellation gives Dijw(t,x)=∫0t−δ∫RnDijΓεσ(z)(h(t−σ,x−z)−h(t,x)) dz dσ. The parabolic Hölder bound from step 3.3 yields ∣h(t−σ,x−z)−h(t,x)∣≤C(∣z∣α+σα/2). Gaussian scaling therefore gives ∫Rn∣D2Γεσ(z)∣(∣z∣α+σα/2) dz≤Cε,n,ασ−1+α/2, which is integrable at σ=0. Truncating the heat-potential integral at σ=η>0, differentiating, and letting η↓0 with this integrable dominator shows that Dijw exists and is continuous; the heat-kernel identity also gives wt−εΔw=h in distributions. Since h and Δw are continuous, this identity gives a continuous classical time derivative. The first term Hε(t−δ)u(δ) is smooth for t>δ, so u∈C1,2(Rn×(δ,τ0)) and satisfies ut=εΔu−f′(u)⋅∇u, hence ut+div⁡xf(u)=εΔu pointwise. Since δ>0 is arbitrary, u∈C1,2(Rn×(0,τ0)).

5.1F3F4step 2.1step 4.1

The range bound by a barrier. Let a<b in [0,τ0) and put Ma:=sup⁡xu(a,x). Write B:=f′(u(t,x)), which is bounded on [a,b]×Rn by L. For δ1>0 and λ>0 set Φ(t,x):=δ1eλ(t−a)(1+∣x∣2); then, using steps 4.1 and [F4], (∂t−εΔ+B⋅∇)Φ=δ1eλ(t−a)(λ(1+∣x∣2)−2εn+2B⋅x)>0 for λ large enough, because ∣B∣≤L and −εΔ(1+∣x∣2)=−2εn. The function z:=u−Ma−Φ is negative at t=a and, by step 2.1, ∣u∣≤R while Φ≥δ1(1+∣x∣2), so z is negative on the lateral boundary of every sufficiently large ball intersected with [a,b]; if z had a positive maximum in the closed cylinder, then at that point zt≥0, Dz=0, Δz≤0 (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value, Heine-Borel in Rn: with the Euclidean metric a subset of Rn is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line), contradicting (∂t−εΔ+B⋅∇)z<0 there. Letting δ1↓0 gives u≤Ma on [a,b]; applying the same argument to −u, whose flux is f~(s)=−f(−s) and whose range bound is the same, gives u≥ma:=inf⁡xu(a,x). In particular, with a=0, sup⁡xu(t,x)≤sup⁡xu0 and inf⁡xu(t,x)≥inf⁡xu0 on [0,τ0), the range of u is contained in I0:=[inf⁡u0,sup⁡u0].

6.1F3F6step 2.1step 2.2step 3.1step 4.1step 5.1∎

Global continuation and conclusion. For every t1>0, the positive-strip spatial modulus of step 2.2 makes u(t1,⋅) bounded and uniformly continuous, step 3.1 gives u(t1)∈L1, and step 5.1 places its values in I0. Thus g:=u(t1) is an admissible BUC∩L1 starting datum for the local fixed-point and Picard iteration of steps 2.1 and 3.1. The strong heat continuity required for this restart is [F6]: Gaussian approximate-identity convergence gives Hεtg→g in the supremum norm for BUC data and in L1 for L1 data. With the same global constants R,L, the local solution on [t1,t1+τ0) agrees with u at t1; local uniqueness in step 2.1 makes the pieces agree on overlaps, and ∥u(t)∥∞≤max⁡{∣inf⁡u0∣,∣sup⁡u0∣}≤R throughout. Iterating finitely many times covers [0,T], and the same local uniqueness shows that two solutions obtained with different terminal times T,T′ agree on their common interval. The range bounds of step 5.1 hold on all of [0,T]; L1 continuity holds by step 3.1 and C1,2 regularity on Rn×(0,T) by step 4.1. This is the asserted global mild solution.

Depends on

Used by

Dependency tree · two levels

151 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources