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PropositionStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-07
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  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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Homology of the derived tensor product is tor

Statement

For a right R-module N, a left R-module M, and n0, with supplied projective resolutions, Hn(N[0]RLM[0])TornR(N,M) naturally in both modules.

Facts & Assumptions

Given: For a right R-module N, a left R-module M, and n0, with supplied projective resolutions, Hn(N[0]RLM[0])TornR(N,M) naturally in both modules.

[F1]

The derived tensor is represented using either projective replacement with the two-replacement balancing zigzag (Derived tensor product in the bounded above setting).

[F2]

Balanced Tor is resolution tensor homology, with maps induced by comparison maps (The balanced Tor bifunctor).

Proof

1.1

Represent the derived tensor by NRPM with the projective resolution reindexed by PMi=(PM)i. Its degree n cohomology is exactly Hn(NR(PM)), including n=0 and zero modules.

F1
2.1

This homology is the definition of balanced Tor on the left-resolution side. The common two-resolution tensor complex gives the same balance on the other side, and comparison maps on resolutions induce exactly the maps used in that definition. Thus the identification is natural and compatible with either supplied resolution.

F2step 1.1

Depends on

Used by

Dependency tree · two levels

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Sources