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7.1 Definition and properties of Tor functor

3 min readaugust 7, 2024

The measures how tensor products deviate from exactness. It takes two and produces a new module for each non-negative integer, with Tor₀ being the tensor product itself. Higher Tor functors capture the non-exactness.

Tor is derived from the tensor product functor using . It's additive, preserves direct sums, and vanishes for flat modules. Tor helps detect flatness and appears in long exact sequences, making it a powerful tool in homological algebra.

Definition and Properties

Tor as a Derived Functor

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  • Tor functor TornR(M,N)\operatorname{Tor}_n^R(M,N) measures the degree to which the tensor product MRNM \otimes_R N fails to be exact
    • Takes two R-modules MM and NN as input and produces a new R-module TornR(M,N)\operatorname{Tor}_n^R(M,N) for each non-negative integer nn
    • Tor0R(M,N)\operatorname{Tor}_0^R(M,N) is isomorphic to the tensor product MRNM \otimes_R N
    • Higher Tor functors TornR(M,N)\operatorname{Tor}_n^R(M,N) for n>0n > 0 measure the deviation from exactness
  • Tor is a obtained by taking a left derived functor of the tensor product functor RN- \otimes_R N
    • Derived functors are a way to extend a functor that is not exact to a sequence of functors that preserve exactness
    • Left derived functors are computed using projective resolutions of the first argument (MM in this case)
  • Tor is an additive functor covariant in both arguments and preserves direct sums
    • TornR(M1M2,N)TornR(M1,N)TornR(M2,N)\operatorname{Tor}_n^R(M_1 \oplus M_2, N) \cong \operatorname{Tor}_n^R(M_1, N) \oplus \operatorname{Tor}_n^R(M_2, N)
    • TornR(M,N1N2)TornR(M,N1)TornR(M,N2)\operatorname{Tor}_n^R(M, N_1 \oplus N_2) \cong \operatorname{Tor}_n^R(M, N_1) \oplus \operatorname{Tor}_n^R(M, N_2)

Flatness and Vanishing of Tor

  • An R-module MM is flat if the functor MRM \otimes_R - is exact
    • Equivalently, MM is flat if TornR(M,N)=0\operatorname{Tor}_n^R(M,N) = 0 for all n>0n > 0 and all R-modules NN
    • Examples of flat modules include free modules, projective modules, and localizations of flat modules
  • If either MM or NN is a flat R-module, then TornR(M,N)=0\operatorname{Tor}_n^R(M,N) = 0 for all n>0n > 0
    • In this case, the tensor product MRNM \otimes_R N is exact, and there is no need for higher Tor functors
  • Tor can be used to detect flatness: an R-module MM is flat if and only if Tor1R(M,N)=0\operatorname{Tor}_1^R(M,N) = 0 for all R-modules NN
    • This provides a practical way to check flatness using a single Tor functor instead of all higher Tor functors

Computation and Applications

Computing Tor using Resolutions

  • Tor functors can be computed using projective resolutions or flat resolutions
    • To compute TornR(M,N)\operatorname{Tor}_n^R(M,N), take a projective resolution PMP_\bullet \to M of MM and tensor it with NN to get a chain complex PRNP_\bullet \otimes_R N
    • The homology of this chain complex at the nn-th position is TornR(M,N)\operatorname{Tor}_n^R(M,N)
  • Alternatively, Tor can be computed using flat resolutions of the second argument
    • Take a flat resolution FNF_\bullet \to N of NN and tensor it with MM to get a chain complex MRFM \otimes_R F_\bullet
    • The homology of this chain complex at the nn-th position is TornR(M,N)\operatorname{Tor}_n^R(M,N)
  • The choice of resolution (projective or flat) depends on the properties of the modules involved and the convenience of computation

Applications and Properties of Tor

  • Tor is related to the concept of torsion in module theory
    • An element xMx \in M is a torsion element if rx=0rx = 0 for some nonzero rRr \in R
    • The set of torsion elements in MM forms a submodule called the torsion submodule Tor(M)\operatorname{Tor}(M)
    • Tor1R(R/I,M)\operatorname{Tor}_1^R(R/I, M) is isomorphic to the II-torsion submodule of MM
  • Tor appears in the long exact sequence of Tor associated with a short exact sequence of modules
    • Given a short exact sequence 0ABC00 \to A \to B \to C \to 0 and an R-module MM, there is a long exact sequence of Tor functors: Torn+1R(C,M)TornR(A,M)TornR(B,M)TornR(C,M)\cdots \to \operatorname{Tor}_{n+1}^R(C,M) \to \operatorname{Tor}_n^R(A,M) \to \operatorname{Tor}_n^R(B,M) \to \operatorname{Tor}_n^R(C,M) \to \cdots
    • This long exact sequence can be used to compute Tor functors and study the relationships between modules
  • Tor satisfies the dimension shifting property: TornR(M,N)Torn1R(M,ΩN)\operatorname{Tor}_n^R(M,N) \cong \operatorname{Tor}_{n-1}^R(M,\Omega N), where ΩN\Omega N is the first syzygy of NN
    • This property allows for the computation of higher Tor functors using lower ones and syzygies
  • Tor is balanced, meaning that TornR(M,N)TornR(N,M)\operatorname{Tor}_n^R(M,N) \cong \operatorname{Tor}_n^R(N,M) for all n0n \geq 0
    • This symmetry property simplifies computations and proofs involving Tor functors
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© 2024 Fiveable Inc. All rights reserved.
AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.

© 2024 Fiveable Inc. All rights reserved.
AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.
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