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Local regularity and compactness for the p-harmonic map heat flows

  • Masashi Misawa EMAIL logo
Veröffentlicht/Copyright: 21. Februar 2017

Abstract

We study a geometric analysis and local regularity for the evolution of p-harmonic maps, called p-harmonic map heat flows. Our main result is to establish a criterion for a uniform local regularity estimate for regular p-harmonic map heat flows, devising some new monotonicity-type formulas of a local scaled energy. The regularity criterion obtained is almost optimal, comparing with that of the corresponding stationary case. As application we show a compactness of regular p-harmonic map heat flows with energy bound.


Communicated by Frank Duzaar


Award Identifier / Grant number: 15K04962

Funding statement: The work of Masashi Misawa was partially supported by the Grant-in-Aid for Scientific Research (C) No. 15K04962 from Japan Society for the Promotion of Science.

A Appendix

Here we demonstrate the proof of Lemma 8, based on Moser’s iteration method as usual. Such an estimate has originally been done for the evolutionary p-Laplacian system with controllable growth lower-order terms, due to DiBenedetto, developing the intrinsic scaling transformation to the evolutionary p-Laplace operator (refer to [10, 8]). However, the emphasis here is to make localization by use of the cut-off function 𝒞.

Proof of Lemma 8.

We use the same notation as in Lemma 8. The Bochner-type formula holds in

Q0:=Q(L2-p(r0)2,r0)(t0,x0)

in the distribution sense

(A.1)t(12|Du|2)-Dα(Aαβ|Du|p-2Dβ(12|Du|2))+C2|Du|p-2|D2u|2C3|Du|p+2

with

Aαβ=Aαβ(Du):=δαβ+(p-2)DαuDβu|Du|2.

Here the positive constants C2 and C3 depend only on m,p, and m,p and 𝒩, respectively. By use of a scaling transformation intrinsic to the evolutionary p-Laplace operator

(A.2)t=t0+L2-p(r0)2s,x=x0+r0y,

we now rewrite (A.1) for the scaled solution v in Q(1,1)(0)

v(s,y)=u(t0+L2-p(r0)2s,x0+r0y)Lr0

satisfying in Q(1,1)(0)

(A.3)sv-div(|Dv|p-2Dv)=-Lr0|Dv|p-2A(Lr0v)(Dv,Dv).

Formally make differentiation of equation (A.3) on spatial variable and multiply the resulting equation by the spatial gradient yielding

s(12|Dv|2)-Dα(Aαβ|Dv|p-2Dβ(12|Dv|2))+|Dv|p-2|D2v|2+(p-2)|Dv|p-4|D12|Dv|2|2
=-Lr0D(|Dv|p-2A(Lr0v)(Dv,Dv))Dv.

Here by (3.1) and Cauchy’s inequality we estimate the right-hand side as

Lr0|D(|Dv|p-2A(Lr0v)(Dv,Dv))Dv|CLr0(|Dv|p|D2v|+Lr0|Dv|p+2)
CLr01LDuL(Q0)|Dv|p-1|D2v|+L2(r0)21L2DuL(Q0)2|Dv|p
C(|Dv|p-1|D2v|+|Dv|p)
δ|Dv|p-2|D2v|2+C(δ-1)|Dv|p,

leading to the scaled Bochner formula for the scaled solution v in Q(1,1)(0)

(A.4)s(12|Dv|2)-Dα(Aαβ|Dv|p-2Dβ(12|Dv|2))+C|Dv|p-2|D2v|2C|Dv|p.

Finally, we make Moser’s iteration estimate by (A.4) and scaling back to have (3.2). Now, taking care of localization by the cut off function 𝒞, we proceed to the estimations.

Let B(ρ)=B(ρ,0) be a ball in m with center of origin and radius ρ1. Also let r<ρ1. Let η be a smooth real-valued function on m such that 0η1, the support of η is contained in B(ρ) and η=1 on B(r). Let σ=σ(t) be a smooth real-valued function on such that 0σ1, σ=1 on [-r2,) and σ=0 on (-,-ρ2]. Also we denote by the original notation the scaled function under (A.2)

𝒞(s,y)=((t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|)+,(s,y)Q(1,1)(0),

and also write as w=(s,y)Q(1,1)(0) and dw=dyds.

Let α be a nonnegative number and use the test function |Dv|αη2σ𝒞q in the weak form of (A.4). After a routine computation we have the so-called reverse Poincaré inequality

(A.5)sup-r2<τ<0B(ρ)|Dv(τ)|α+2η2σ𝒞q𝑑y+(-ρ2, 0)×B(ρ)|D|Dv|α+p2|2η2σ𝒞q𝑑w
C(α+p)3(-ρ2,0)×B(ρ)(|Dv|α+2η2tσ+|Dv|α+p|Dη|2σ)𝒞q𝑑w.

Applying the Sobolev embedding W01,2(B(ρ))L2mm-2(B(ρ)), we have

(B(ρ)(|Dv|α+p2η𝒞q2)2mm-2𝑑y)m-22mC(B(ρ)|D(|Dv|α+p2η𝒞q2)|2𝑑y)12,

which is combined with (A.5) and yields

sup-r2<τ<0B(r)|Dv(τ)|α+2𝒞q𝑑y+-r20(B(r)|Dv|m(α+p)m-2𝒞mqm-2𝑑y)m-2m𝑑t
(A.6)C(α+p)3(ρ-r)2(-ρ2, 0)×B(ρ)(|Dv|α+2+|Dv|α+p)𝒞q𝑑w.

By Hölder’s inequality and (A.6) we compute as

Q(r2,r)|Dv|α+p+2(α+2)m𝒞q(m+2)m𝑑w-r20(B(r)|Dv|α+2𝒞q𝑑y)2m(B(r)|Dv|m(α+p)m-2𝒞qmm-2𝑑y)m-2m𝑑t
(sup-r2<τ<0B(r)|Dv(τ)|α+2𝒞q𝑑y)2m-r20(B(r)|Dv|m(α+p)m-2𝒞qmm-2𝑑y)m-2m𝑑t
(C(α+p)3(ρ-r)2Q(ρ2,ρ)|Dv|α+p𝒞q𝑑w+C(α+p)3|Q(ρ2,ρ)|(ρ-r)2)m+2m,

where we use a simple inequality valid for α0

|Dv|α+2=(χ{|Dv|1}+χ{|Dv|<1})|Dv|α+2
χ{|Dv|1}|Dv|α+p+χ{|Dv|<1}
|Dv|α+p+1

and also estimate the derivative of 𝒞 as

|D𝒞(s,y)|=|D((t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|)+|
=|-x0+r0y|x0+r1y|r0|χ{|x0+r0y|<t0;L2-p(r0)2s+Rλ0}(s,y)
((t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|)+r0(t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|
((t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|)+
=𝒞(s,y),
|s𝒞(s,y)|=|s((t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|)+|
=|1λ0(t0+L2-p(r0)2s+Rλ0)1λ0-1L2-p(r0)2|χ{|x0+r0y|<t0+L2-p(r0)2s+Rλ0}(s,y)
1λ0χ{|x0+r0y|<t0+L2-p(r0)2s+Rλ0}(s,y)((ρ0)λ0)1λ0-1(ρ0)λ0
ρ0ρ0/2(ρ0)λ0(ρ0)λ0((t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|)+
=2𝒞(s,y),

because by the range Q(1,1)(0) of (s,y), and condition (3.1) of r0

-1s0,|y|1,ρ0=(t0+Rλ0)1λ0-|x0|4,r0ρ02,L2-p(r0)2(ρ0)λ0

and so we have the estimations

r0ρ021

and

(t0+L2-p(r0)2s+Rλ0)1λ0-|x0+r0y|(t0+Rλ0-(ρ0)λ0)1λ0-(|x0|+r0)(t0+Rλ0)1λ0+|x0|2-|x0|-r0ρ0-ρ02=ρ02.

We arrange some terms in an appropriate way to have

1|Q(r2,r)|Q(r2,r)|Dv|α+p+2(α+2)m𝒞q(m+2)m𝑑w
(A.7)C(α+p)3(1+2m)|Q(ρ2,ρ)|1+2m(ρ-r)2(1+2m)(1|Q(ρ2,ρ)|Q(ρ2,ρ)|Dv|α+p𝒞q𝑑w+1)1+2m.

Here let {ρk} be a sequence of radii, defined as

(A.8)ρk=2-1(1+2-k),1ρk12,Qk=Q((ρk)2,ρk)(0),

and let {αk} and {qk} be sequences of exponents

(A.9)θ=1+2m,q>1,αk=2θk-2,qk=qθk,0=α0<αk,q<qk,αk+2(αk+2)m=αkθ+4m=αk+1.

We choose r=ρk+1, ρ=ρk and α=αk, q=qk in (A.7) and make routine computation to have

(1|Qk+1|Qk+1|Dv|αk+1+p𝒞qk+1𝑑w)1θk+1Ckθk+1(αk+p)3θk(1|Qk|Qk|Dv|αk+p𝒞qk𝑑w+1)1θk,

which is computed by sequences (A.8) and (A.9) as

(1|Qk+1|Qk+1|Dv|αk+1+p𝒞qk+1𝑑w)1θk+1Ckθk(1|Qk|Qk|Dv|αk+p𝒞qk𝑑w+1)1θk,
(A.10)(1|Qk+1|Qk+1|Dv|αk+1+p𝒞qk+1𝑑w+1)1θk+1Ckθk(1|Qk|Qk|Dv|αk+p𝒞qk𝑑w+1)1θk.

An iterative application of (A.10) yields

supQ((ρ02)2,ρ02)|Dv|2𝒞q0(1|Qk+1|Qk+1|Dv|αk+1+p𝒞q0(αk+1+p)2𝑑w)1θk+1
(1|Qk+1|Qk+1|Dv|αk+1+p𝒞qk+1𝑑w+1)1θk+1
(A.11)Ci=1kiθi(1|Q0|Q0|Dv|α0+p𝒞q0𝑑w+1)1θ0,

with the relation of exponents

0𝒞(s,y)1,(s,y)Q(1,1)(0),
qk+1=q0θk+1<q0αk+1+p2θk+1<αk+1+p2=θk+1+p-22

and the computation

αk+1+pθk+1=2+p-2θk+12,qk+1αk+1+p=q02+p-2θk+1<q02.

Finally, scaling back in (A.11) yields the desired estimate (3.2). ∎

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Received: 2016-12-20
Accepted: 2017-01-17
Published Online: 2017-02-21
Published in Print: 2018-07-01

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