2020
DOI: 10.1016/j.jfa.2020.108560
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A quantitative stability estimate for the fractional Faber-Krahn inequality

Abstract: We prove a quantitative version of the Faber-Krahn inequality for the first eigenvalue of the fractional Dirichlet-Laplacian of order s. This is done by using the so-called Caffarelli-Silvestre extension and adapting to the nonlocal setting a trick by Hansen and Nadirashvili. The relevant stability estimate comes with an explicit constant, which is stable as the fractional order of differentiability goes to 1.2010 Mathematics Subject Classification. 47A75, 49Q20, 35R11.

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Cited by 14 publications
(17 citation statements)
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“…Now we prove a technical result similar to [6,Lemma 4.2]. It states that if we are not going too far in the vertical direction, then the level sets of the extension of the characteristic function of a set E are comparable to E itself.…”
Section: Estimates On the Level Sets Of The Extensionmentioning
confidence: 55%
See 3 more Smart Citations
“…Now we prove a technical result similar to [6,Lemma 4.2]. It states that if we are not going too far in the vertical direction, then the level sets of the extension of the characteristic function of a set E are comparable to E itself.…”
Section: Estimates On the Level Sets Of The Extensionmentioning
confidence: 55%
“…This section contains some technical results that are the core of the proof of the Main Theorem. Our strategy follows the ideas in [6]: we first estimate D γ s (E) from below with a quantity involving the asymmetry of the superlevel sets of U E (•, z) and then, in a suitable range of values for the function U E and for the vertical variable z, we show that the asymmetry of the superlevel sets is estimated from below by A γ (E).…”
Section: Estimates On the Level Sets Of The Extensionmentioning
confidence: 99%
See 2 more Smart Citations
“…The optimal shape problems for the first eigenvalue of the fractional Laplacian with homogeneous external datum was addressed in [3,13,56,11], showing that the ball is the optimizer.…”
Section: Introductionmentioning
confidence: 99%