2023
DOI: 10.48550/arxiv.2301.09150
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Linear syzygies of curves in weighted projective space

Abstract: We develop analogues of Green's N p -conditions for subvarieties of weighted projective space, and we prove that such N p -conditions are satisfied for high degree embeddings of curves in weighted projective space. A key technical result links positivity with low degree (virtual) syzygies in wide generality, including cases where normal generation fails.

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Cited by 1 publication
(4 citation statements)
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“…In the classical setting, Corollary 1.8 implies that 𝑀 ⩾𝑟 (𝑟) has a linear resolution, as 𝑤 𝑖 = 𝑖 = 𝑤 𝑖 for all 𝑖. Thus, the conditions in this corollary can be seen as providing a nonstandard graded analogue of a linear resolution; in fact, this notion of a "Koszul linear" complex arises in [7] in relation to 𝑁 𝑝 -conditions on weighted projective space, and it contrasts with the notion of strong linearity from [5, Definition 1.2].…”
Section: Introductionmentioning
confidence: 98%
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“…In the classical setting, Corollary 1.8 implies that 𝑀 ⩾𝑟 (𝑟) has a linear resolution, as 𝑤 𝑖 = 𝑖 = 𝑤 𝑖 for all 𝑖. Thus, the conditions in this corollary can be seen as providing a nonstandard graded analogue of a linear resolution; in fact, this notion of a "Koszul linear" complex arises in [7] in relation to 𝑁 𝑝 -conditions on weighted projective space, and it contrasts with the notion of strong linearity from [5, Definition 1.2].…”
Section: Introductionmentioning
confidence: 98%
“…In fact, a main theme from recent work on syzygies with nonstandard gradings, for example, [3, 5, 7, 9-11, 14, 18, 20, 23], is that notions from the standard graded case can have several distinct nonstandard graded analogues, each of which is useful for different purposes. For instance, several analogs of linear resolutions in the nonstandard ℤ-graded setting play a key role in [7]. Our goal in this paper is to demonstrate how an alternate analogue of regularity -Koszul regularity -can provide sharper information in some contexts.…”
Section: Introductionmentioning
confidence: 99%
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