2015
DOI: 10.1515/crelle-2014-0114
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Characteristic classes of symmetric products of complex quasi-projective varieties

Abstract: Abstract. We prove generating series formulae for suitable twisted characteristic classes of symmetric products of a singular complex quasi-projective variety. More concretely, we study homology Hirzebruch classes for motivic coefficients, as well as for complexes of mixed Hodge modules. As a special case, we obtain a generating series formula for the (intersection) homology Hirzebruch classes of symmetric products. In some cases, the latter yields a similar formula for twisted homology L-classes generalizing … Show more

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Cited by 15 publications
(29 citation statements)
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“…In this paper, we obtain refined generating series formulae for equivariant characteristic classes of external and symmetric products of singular complex quasi-projective varieties, generalizing our previous results for symmetric products from [13].…”
Section: Introductionsupporting
confidence: 58%
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“…In this paper, we obtain refined generating series formulae for equivariant characteristic classes of external and symmetric products of singular complex quasi-projective varieties, generalizing our previous results for symmetric products from [13].…”
Section: Introductionsupporting
confidence: 58%
“…Let now Z be a quasi-projective variety, and denote by Z (n) := Z n /Σ n its n-th symmetric product (i.e., the quotient of Z n by the natural permutation action of the symmetric group Σ n on n elements), with π n : Z n → Z (n) the natural projection map. The standard approach for computing invariants of the symmetric products Z (n) is to collect the respective invariants of all symmetric products in a generating series, and then compute the latter solely in terms of invariants of Z, e.g., see [13] and the references therein. In this paper, we obtain generalizations of results of [13], formulated in terms of equivariant characteristic classes of external products and resp., symmetric products of varieties.…”
Section: ) Hmentioning
confidence: 99%
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