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Record W4322625119 · doi:10.1090/pspum/105/18

Cyclic homology and group actions

2023· other· en· W4322625119 on OpenAlexfundno aff
Raphaël Ponge

Bibliographic record

VenueProceedings of symposia in pure mathematics · 2023
Typeother
Languageen
FieldChemistry
TopicAxial and Atropisomeric Chirality Synthesis
Canadian institutionsnot available
FundersNational Research FoundationMcGill UniversityUniversity of California Berkeley
KeywordsHomology (biology)Group (periodic table)Group actionMathematicsBiologyChemistryGeneticsAmino acid

Abstract

fetched live from OpenAlex

In this paper we present the construction of explicit quasi-isomorphisms that compute the cyclic homology and periodic cyclic homology of crossed-product algebras associated with (discrete) group actions.In the first part we deal with algebraic crossed-products associated with group actions on unital algebras over any ring k Ą Q.In the second part, we extend the results to actions on locally convex algebras.We then deal with crossed-products associated with group actions on manifolds and smooth varieties.For the finite order components, the results are expressed in terms of what we call "mixed equivariant cohomology".This "mixed" theory mediates between group homology and de Rham cohomology.It is naturally related to equivariant cohomology, and so we obtain explicit constructions of cyclic cycles out of equivariant characteristic classes.For the infinite order components, we simplify and correct the misidentification of [20].An important new homological tool is the notion of "triangular S-module".This is a natural generalization of the cylindrical complexes of Getzler-Jones.It combines the mixed complexes of Burghelea-Kassel and parachain complexes of Getzler-Jones with the S-modules of Kassel-Jones.There are spectral sequences naturally associated with triangular S-modules.In particular, this allows us to recover spectral sequences of Feigin-Tsygan and Getzler-Jones and leads us to a new spectral sequence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.587
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.240
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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