2015
DOI: 10.1007/s11118-015-9494-1
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Scale-invariant Boundary Harnack Principle on Inner Uniform Domains in Fractal-type Spaces

Abstract: We prove a scale-invariant boundary Harnack principle for inner uniform domains in metric measure Dirichlet spaces. We assume that the Dirichlet form is symmetric, strongly local, regular, and that the volume doubling property and two-sided sub-Gaussian heat kernel bounds are satisfied. We make no assumptions on the pseudo-metric induced by the Dirichlet form, hence the underlying space can be a fractal space.2010 Mathematics Subject Classification: 31C25, 60J60, 60J45.

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Cited by 22 publications
(24 citation statements)
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“…These are proved [24,Section 6]. Similarly, we can show that the Markovian transition functions P t map the space C 0 of continuous functions vanishing at infinity into itself, by repeating the proof given in [25,Proposition 3.2] under the present weaker assumptions and by applying the results of [24,Section 6].…”
Section: Harnack Inequalitiessupporting
confidence: 54%
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“…These are proved [24,Section 6]. Similarly, we can show that the Markovian transition functions P t map the space C 0 of continuous functions vanishing at infinity into itself, by repeating the proof given in [25,Proposition 3.2] under the present weaker assumptions and by applying the results of [24,Section 6].…”
Section: Harnack Inequalitiessupporting
confidence: 54%
“…Proof The strong Feller property is proved in [25,Proposition 3.2] under the stronger assumption that (X, d) is complete and geodesic, VD holds, and weak heat kernel estimates HKE( ) hold. However, the same proof goes through under the present weaker assumptions.…”
Section: Harnack Inequalitiesmentioning
confidence: 99%
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“…The boundary Harnack inequality was first proved independently by A. Ancona ([5]), B. Dahlberg ([17]) and J.-M. Wu ([35]) for Lipschitz domains, and then extended by numerous authors to a wider class of domains and elliptic operators. We refer to [1][2][3][4]31] for further discussion and references.…”
Section: Introductionmentioning
confidence: 99%