2014
DOI: 10.1112/blms/bdu089
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Lyubeznik numbers for nonsingular projective varieties

Abstract: Abstract. In this paper, we determine completely the Lyubeznik numbers λ i,j (A) of the local ring A at the vertex of the affine cone over a nonsingular projective variety V , where V is defined over a field of characteristic zero, in terms of the dimensions of the algebraic de Rham cohomology spaces of V . In particular, we prove that these numbers are intrinsic numerical invariants of V , even though a priori their definition depends on an embedding into projective space. This provides supporting evidence fo… Show more

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Cited by 19 publications
(11 citation statements)
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“…Switala [16] in a recent paper about Lyubeznik numbers recovers independently our Theorem 4.8(1) for the vertex of the cone over a nonsingular projective variety. His argument is similar to ours, but uses cohomology instead of homology.…”
Section: All Other Values Of H J Dr (H I I (A)) Are Zero As Are All O...supporting
confidence: 62%
“…Switala [16] in a recent paper about Lyubeznik numbers recovers independently our Theorem 4.8(1) for the vertex of the cone over a nonsingular projective variety. His argument is similar to ours, but uses cohomology instead of homology.…”
Section: All Other Values Of H J Dr (H I I (A)) Are Zero As Are All O...supporting
confidence: 62%
“…The answer has been proven to be affirmative if k has prime characteristic [Zha11], or if X is smooth [Swi15]. Additionally, the highest Lyubeznik number is always independent of the choice of embedding [Zha07], as is λ 0,1 (A) (cf.…”
Section: Introductionmentioning
confidence: 99%
“…Although our principal motivation for seeking such a theorem is to better understand the topology of a ring's spectrum, cohomological dimension is itself an influential research topic. It has connections with, for instance, the number of equations defining a variety [BS98, ILL + 07], depth [PS73,Lyu06b,Var13,DT15], and the vanishing of singular and algebraic de Rham cohomology [GLS98,Lyu07,Swi15]. The new SVT may be a useful tool for extending results previously known only in equal characteristic to the mixed characteristic setting.…”
Section: Introductionmentioning
confidence: 99%