Pith. sign in

REVIEW 1 cited by

Multiplicative Chow-K\"unneth decomposition and homology splitting of configuration spaces

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2401.06455 v2 pith:Y6VT5Y5M submitted 2024-01-12 math.AG math.AT

classification math.AGmath.AT
keywords cohomologyconfigurationhyperellipticspacescurvesdecompositiondetailedforgetful
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
abstract

We construct a splitting of the cohomology of configuration spaces of points on a smooth proper variety with a multiplicative Chow--K\"unneth decomposition. Applied to hyperelliptic curves, this shows that the hyperelliptic Torelli group acts trivially on the rational cohomology of ordered configuration spaces of points. Moreover, if $H_{g,n}$ denotes the moduli space of $n$-pointed hyperelliptic curves, the Leray spectral sequence for the forgetful map $H_{g,n} \to H_g$ degenerates immediately, in sharp contrast to the forgetful map from $M_{g,n}$ to $M_g$. This allows for new detailed calculations of the cohomology of $M_{2,n}$ for $n \leq 5$, and the stable cohomology of $H_{g,n}$ for $n \leq 5$. We also give a detailed study of the cohomology of symplectic local systems on $M_2$.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research

    cs.CL 2025-05 conditional novelty 7.0 of 10

    SPOT shows that state-of-the-art AI models detect fewer than one in five known errors in full scientific papers, with precision below 7%.

Pith tools