Latest

Algebraic and complex geometry

Log-canonical threefold abundance in numerical dimension one

OpenAI research collection · 2 manuscripts · Source checked 2026-10-19

OpenAI's result summary

Proves log abundance for projective log canonical threefold pairs over algebraically closed fields of characteristic p > 3 when the effective boundary is rational and the ℚ-Cartier adjoint is nef of numerical dimension one. The adjoint is semiample, without requiring the original variety to be terminal or ℚ-factorial.

Read the manuscripts

Short excerpts below come from OpenAI's abstracts. The full abstract and original PDF preserve the paper's precise scope.

MANUSCRIPT 01

Log abundance in numerical dimension one for threefolds in positive characteristic

We prove the numerical-dimension-one case of log abundance for threefolds over algebraically closed fields of characteristic p > 3. If (X,B) is a projective log canonical threefold pair with effective rational boundary, and K_X+B is ℚ-Cartier, nef, and of numerical dimension one, then K_X+B is semiample. Neither terminality nor…

Full source abstract

We prove the numerical-dimension-one case of log abundance for threefolds over algebraically closed fields of characteristic p > 3. If (X,B) is a projective log canonical threefold pair with effective rational boundary, and K_X+B is ℚ-Cartier, nef, and of numerical dimension one, then K_X+B is semiample. Neither terminality nor ℚ-factoriality of X is required.

This exact PDF is not listed in the imported formalization catalogue. Family scope notes may contain further information.

MANUSCRIPT 02

Abundance in numerical dimension one for terminal threefolds in positive characteristic

Let X be a projective ℚ-factorial terminal threefold over an algebraically closed field of characteristic p > 3. We prove the numerical-dimension-one case of abundance: if K_(X) is nef with \nu(K_X)=1, then K_(X) is semiample and \kappa(X,K_X)=1.

This exact PDF is not listed in the imported formalization catalogue. Family scope notes may contain further information.

One signal in the wider AGI picture

New mathematical reasoning could help AI tackle harder scientific and computational problems. How reliably these skills transfer beyond mathematics will determine how much they contribute to general intelligence.

Explore the AGI Clock ↗