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) measures the degree to which the tensor product M⊗RN fails to be exact
Takes two R-modules M and N as input and produces a new R-module TornR(M,N) for each non-negative integer n
Tor0R(M,N) is isomorphic to the tensor product M⊗RN
Higher Tor functors TornR(M,N) for n>0 measure the deviation from exactness
Tor is a obtained by taking a left derived functor of the tensor product functor −⊗RN
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 (M in this case)
Tor is an additive functor covariant in both arguments and preserves direct sums
TornR(M1⊕M2,N)≅TornR(M1,N)⊕TornR(M2,N)
TornR(M,N1⊕N2)≅TornR(M,N1)⊕TornR(M,N2)
Flatness and Vanishing of Tor
An R-module M is flat if the functor M⊗R− is exact
Equivalently, M is flat if TornR(M,N)=0 for all n>0 and all R-modules N
Examples of flat modules include free modules, projective modules, and localizations of flat modules
If either M or N is a flat R-module, then TornR(M,N)=0 for all n>0
In this case, the tensor product M⊗RN is exact, and there is no need for higher Tor functors
Tor can be used to detect flatness: an R-module M is flat if and only if Tor1R(M,N)=0 for all R-modules N
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), take a projective resolution P∙→M of M and tensor it with N to get a chain complex P∙⊗RN
The homology of this chain complex at the n-th position is TornR(M,N)
Alternatively, Tor can be computed using flat resolutions of the second argument
Take a flat resolution F∙→N of N and tensor it with M to get a chain complex M⊗RF∙
The homology of this chain complex at the n-th position is TornR(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 x∈M is a torsion element if rx=0 for some nonzero r∈R
The set of torsion elements in M forms a submodule called the torsion submodule Tor(M)
Tor1R(R/I,M) is isomorphic to the I-torsion submodule of M
Tor appears in the long exact sequence of Tor associated with a short exact sequence of modules
Given a short exact sequence 0→A→B→C→0 and an R-module M, there is a long exact sequence of Tor functors:
⋯→Torn+1R(C,M)→TornR(A,M)→TornR(B,M)→TornR(C,M)→⋯
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)≅Torn−1R(M,ΩN), where ΩN is the first syzygy of N
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) for all n≥0
This symmetry property simplifies computations and proofs involving Tor functors