Tensor product of modules over commutative semirings. #
This file constructs the tensor product of modules over commutative semirings. Given a semiring
R and modules over it M and N, the standard construction of the tensor product is
tensor_product R M N. It is also a module over R.
It comes with a canonical bilinear map M → N → tensor_product R M N.
Given any bilinear map M → N → P, there is a unique linear map tensor_product R M N → P whose
composition with the canonical bilinear map M → N → tensor_product R M N is the given bilinear
map M → N → P.
We start by proving basic lemmas about bilinear maps.
Notations #
This file uses the localized notation M ⊗ N and M ⊗[R] N for tensor_product R M N, as well
as m ⊗ₜ n and m ⊗ₜ[R] n for tensor_product.tmul R m n.
Tags #
bilinear, tensor, tensor product
- of_zero_left : ∀ {R : Type u_1} [_inst_1 : comm_semiring R] {M : Type u_4} {N : Type u_5} [_inst_4 : add_comm_monoid M] [_inst_5 : add_comm_monoid N] [_inst_9 : module R M] [_inst_10 : module R N] (n : N), tensor_product.eqv R M N (free_add_monoid.of (0, n)) 0
- of_zero_right : ∀ {R : Type u_1} [_inst_1 : comm_semiring R] {M : Type u_4} {N : Type u_5} [_inst_4 : add_comm_monoid M] [_inst_5 : add_comm_monoid N] [_inst_9 : module R M] [_inst_10 : module R N] (m : M), tensor_product.eqv R M N (free_add_monoid.of (m, 0)) 0
- of_add_left : ∀ {R : Type u_1} [_inst_1 : comm_semiring R] {M : Type u_4} {N : Type u_5} [_inst_4 : add_comm_monoid M] [_inst_5 : add_comm_monoid N] [_inst_9 : module R M] [_inst_10 : module R N] (m₁ m₂ : M) (n : N), tensor_product.eqv R M N (free_add_monoid.of (m₁, n) + free_add_monoid.of (m₂, n)) (free_add_monoid.of (m₁ + m₂, n))
- of_add_right : ∀ {R : Type u_1} [_inst_1 : comm_semiring R] {M : Type u_4} {N : Type u_5} [_inst_4 : add_comm_monoid M] [_inst_5 : add_comm_monoid N] [_inst_9 : module R M] [_inst_10 : module R N] (m : M) (n₁ n₂ : N), tensor_product.eqv R M N (free_add_monoid.of (m, n₁) + free_add_monoid.of (m, n₂)) (free_add_monoid.of (m, n₁ + n₂))
- of_smul : ∀ {R : Type u_1} [_inst_1 : comm_semiring R] {M : Type u_4} {N : Type u_5} [_inst_4 : add_comm_monoid M] [_inst_5 : add_comm_monoid N] [_inst_9 : module R M] [_inst_10 : module R N] (r : R) (m : M) (n : N), tensor_product.eqv R M N (free_add_monoid.of (r • m, n)) (free_add_monoid.of (m, r • n))
- add_comm : ∀ {R : Type u_1} [_inst_1 : comm_semiring R] {M : Type u_4} {N : Type u_5} [_inst_4 : add_comm_monoid M] [_inst_5 : add_comm_monoid N] [_inst_9 : module R M] [_inst_10 : module R N] (x y : free_add_monoid (M × N)), tensor_product.eqv R M N (x + y) (y + x)
The relation on free_add_monoid (M × N) that generates a congruence whose quotient is
the tensor product.
The tensor product of two modules M and N over the same commutative semiring R.
The localized notations are M ⊗ N and M ⊗[R] N, accessed by open_locale tensor_product.
Equations
- tensor_product R M N = (add_con_gen (tensor_product.eqv R M N)).quotient
Instances for tensor_product
- tensor_product.add_zero_class
- tensor_product.add_comm_semigroup
- tensor_product.inhabited
- tensor_product.left_has_smul
- tensor_product.has_smul
- tensor_product.add_comm_monoid
- tensor_product.left_distrib_mul_action
- tensor_product.distrib_mul_action
- tensor_product.left_module
- tensor_product.module
- tensor_product.is_central_scalar
- tensor_product.is_scalar_tower_left
- tensor_product.is_scalar_tower_right
- tensor_product.is_scalar_tower
- tensor_product.has_neg
- tensor_product.add_comm_group
- module.finite.base_change
- module.finite.tensor_product
- algebra.tensor_product.tensor_product.has_one
- algebra.tensor_product.tensor_product.add_monoid_with_one
- algebra.tensor_product.tensor_product.semiring
- algebra.tensor_product.left_algebra
- algebra.tensor_product.tensor_product.algebra
- algebra.tensor_product.tensor_product.is_scalar_tower
- algebra.tensor_product.tensor_product.ring
- algebra.tensor_product.tensor_product.comm_ring
- module.free.tensor
- tensor_product.lie_module.lie_ring_module
- tensor_product.lie_module.lie_module
- lie_algebra.extend_scalars.tensor_product.has_bracket
- lie_algebra.extend_scalars.tensor_product.lie_ring
- lie_algebra.extend_scalars.lie_algebra
- kaehler_differential.module_3
- kaehler_differential.is_scalar_tower
- algebra.formally_unramified.base_change
- algebra.formally_smooth.base_change
- algebra.formally_etale.base_change
Equations
- tensor_product.add_zero_class M N = {zero := add_monoid.zero (add_con_gen (tensor_product.eqv R M N)).add_monoid, add := add_monoid.add (add_con_gen (tensor_product.eqv R M N)).add_monoid, zero_add := _, add_zero := _}
Equations
- tensor_product.add_comm_semigroup M N = {add := add_monoid.add (add_con_gen (tensor_product.eqv R M N)).add_monoid, add_assoc := _, add_comm := _}
Equations
- tensor_product.inhabited M N = {default := 0}
The canonical function M → N → M ⊗ N. The localized notations are m ⊗ₜ n and m ⊗ₜ[R] n,
accessed by open_locale tensor_product.
Equations
- m ⊗ₜ[R] n = ⇑((add_con_gen (tensor_product.eqv R M N)).mk') (free_add_monoid.of (m, n))
A typeclass for has_smul structures which can be moved across a tensor product.
This typeclass is generated automatically from a is_scalar_tower instance, but exists so that
we can also add an instance for add_comm_group.int_module, allowing z • to be moved even if
R does not support negation.
Note that module R' (M ⊗[R] N) is available even without this typeclass on R'; it's only
needed if tensor_product.smul_tmul, tensor_product.smul_tmul', or tensor_product.tmul_smul is
used.
Instances of this typeclass
Instances of other typeclasses for tensor_product.compatible_smul
- tensor_product.compatible_smul.has_sizeof_inst
Note that this provides the default compatible_smul R R M N instance through
mul_action.is_scalar_tower.left.
Equations
smul can be moved from one side of the product to the other .
Auxiliary function to defining scalar multiplication on tensor product.
Equations
- tensor_product.smul.aux r = ⇑free_add_monoid.lift (λ (p : M × N), (r • p.fst) ⊗ₜ[R] p.snd)
Given two modules over a commutative semiring R, if one of the factors carries a
(distributive) action of a second type of scalars R', which commutes with the action of R, then
the tensor product (over R) carries an action of R'.
This instance defines this R' action in the case that it is the left module which has the R'
action. Two natural ways in which this situation arises are:
- Extension of scalars
- A tensor product of a group representation with a module not carrying an action
Note that in the special case that R = R', since R is commutative, we just get the usual scalar
action on a tensor product of two modules. This special case is important enough that, for
performance reasons, we define it explicitly below.
Equations
- tensor_product.left_has_smul = {smul := λ (r : R'), ⇑((add_con_gen (tensor_product.eqv R M N)).lift (tensor_product.smul.aux r) _)}
Equations
- tensor_product.add_comm_monoid = {add := add_comm_semigroup.add (tensor_product.add_comm_semigroup M N), add_assoc := _, zero := add_zero_class.zero (tensor_product.add_zero_class M N), zero_add := _, add_zero := _, nsmul := λ (n : ℕ) (v : tensor_product R M N), n • v, nsmul_zero' := _, nsmul_succ' := _, add_comm := _}
Equations
- tensor_product.left_distrib_mul_action = have this : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ[R] n, from tensor_product.left_distrib_mul_action._proof_3, {to_mul_action := {to_has_smul := {smul := has_smul.smul tensor_product.left_has_smul}, one_smul := _, mul_smul := _}, smul_add := _, smul_zero := _}
Equations
- tensor_product.left_module = {to_distrib_mul_action := {to_mul_action := {to_has_smul := {smul := has_smul.smul tensor_product.left_has_smul}, one_smul := _, mul_smul := _}, smul_add := _, smul_zero := _}, add_smul := _, zero_smul := _}
Equations
is_scalar_tower R'₂ R' M implies is_scalar_tower R'₂ R' (M ⊗[R] N)
is_scalar_tower R'₂ R' N implies is_scalar_tower R'₂ R' (M ⊗[R] N)
A short-cut instance for the common case, where the requirements for the compatible_smul
instances are sufficient.
The canonical bilinear map M → N → M ⊗[R] N.
Equations
- tensor_product.mk R M N = linear_map.mk₂ R (λ (_x : M) (_y : N), _x ⊗ₜ[R] _y) tensor_product.add_tmul _ tensor_product.tmul_add _
The simple (aka pure) elements span the tensor product.
Auxiliary function to constructing a linear map M ⊗ N → P given a bilinear map M → N → P
with the property that its composition with the canonical bilinear map M → N → M ⊗ N is
the given bilinear map M → N → P.
Equations
- tensor_product.lift_aux f = (add_con_gen (tensor_product.eqv R M N)).lift (⇑free_add_monoid.lift (λ (p : M × N), ⇑(⇑f p.fst) p.snd)) _
Constructing a linear map M ⊗ N → P given a bilinear map M → N → P with the property that
its composition with the canonical bilinear map M → N → M ⊗ N is
the given bilinear map M → N → P.
Equations
- tensor_product.lift f = {to_fun := (tensor_product.lift_aux f).to_fun, map_add' := _, map_smul' := _}
This used to be an @[ext] lemma, but it fails very slowly when the ext tactic tries to apply
it in some cases, notably when one wants to show equality of two linear maps. The @[ext]
attribute is now added locally where it is needed. Using this as the @[ext] lemma instead of
tensor_product.ext' allows ext to apply lemmas specific to M →ₗ _ and N →ₗ _.
Linearly constructing a linear map M ⊗ N → P given a bilinear map M → N → P
with the property that its composition with the canonical bilinear map M → N → M ⊗ N is
the given bilinear map M → N → P.
Equations
- tensor_product.uncurry R M N P = (tensor_product.lift ((linear_map.lflip R (M →ₗ[R] N →ₗ[R] P) N P).comp linear_map.id.flip)).flip
A linear equivalence constructing a linear map M ⊗ N → P given a bilinear map M → N → P
with the property that its composition with the canonical bilinear map M → N → M ⊗ N is
the given bilinear map M → N → P.
Equations
- tensor_product.lift.equiv R M N P = {to_fun := (tensor_product.uncurry R M N P).to_fun, map_add' := _, map_smul' := _, inv_fun := λ (f : tensor_product R M N →ₗ[R] P), (tensor_product.mk R M N).compr₂ f, left_inv := _, right_inv := _}
Given a linear map M ⊗ N → P, compose it with the canonical bilinear map M → N → M ⊗ N to
form a bilinear map M → N → P.
Equations
- tensor_product.lcurry R M N P = ↑((tensor_product.lift.equiv R M N P).symm)
Given a linear map M ⊗ N → P, compose it with the canonical bilinear map M → N → M ⊗ N to
form a bilinear map M → N → P.
Equations
- tensor_product.curry f = ⇑(tensor_product.lcurry R M N P) f
The base ring is a left identity for the tensor product of modules, up to linear equivalence.
Equations
- tensor_product.lid R M = linear_equiv.of_linear (tensor_product.lift (linear_map.lsmul R M)) (⇑(tensor_product.mk R R M) 1) _ _
The tensor product of modules is commutative, up to linear equivalence.
Equations
- tensor_product.comm R M N = linear_equiv.of_linear (tensor_product.lift (tensor_product.mk R N M).flip) (tensor_product.lift (tensor_product.mk R M N).flip) _ _
The base ring is a right identity for the tensor product of modules, up to linear equivalence.
Equations
- tensor_product.rid R M = (tensor_product.comm R M R).trans (tensor_product.lid R M)
The associator for tensor product of R-modules, as a linear equivalence.
Equations
- tensor_product.assoc R M N P = linear_equiv.of_linear (tensor_product.lift (tensor_product.lift ((tensor_product.lcurry R N P (tensor_product R M (tensor_product R N P))).comp (tensor_product.mk R M (tensor_product R N P))))) (tensor_product.lift ((tensor_product.uncurry R N P (tensor_product R (tensor_product R M N) P)).comp (tensor_product.curry (tensor_product.mk R (tensor_product R M N) P)))) _ _
The tensor product of a pair of linear maps between modules.
Equations
- tensor_product.map f g = tensor_product.lift (((tensor_product.mk R P Q).compl₂ g).comp f)
Given submodules p ⊆ P and q ⊆ Q, this is the natural map: p ⊗ q → P ⊗ Q.
Equations
The tensor product of a pair of linear maps between modules, bilinear in both maps.
The canonical linear map from P ⊗[R] (M →ₗ[R] Q) to (M →ₗ[R] P ⊗[R] Q)
Equations
- tensor_product.ltensor_hom_to_hom_ltensor R M P Q = tensor_product.lift ((linear_map.llcomp R M Q (tensor_product R P Q)).comp (tensor_product.mk R P Q))
The canonical linear map from (M →ₗ[R] P) ⊗[R] Q to (M →ₗ[R] P ⊗[R] Q)
Equations
- tensor_product.rtensor_hom_to_hom_rtensor R M P Q = tensor_product.lift ((linear_map.llcomp R M P (tensor_product R P Q)).comp (tensor_product.mk R P Q).flip).flip
The linear map from (M →ₗ P) ⊗ (N →ₗ Q) to (M ⊗ N →ₗ P ⊗ Q) sending f ⊗ₜ g to
the tensor_product.map f g, the tensor product of the two maps.
Equations
- tensor_product.hom_tensor_hom_map R M N P Q = tensor_product.lift (tensor_product.map_bilinear R M N P Q)
If M and P are linearly equivalent and N and Q are linearly equivalent
then M ⊗ N and P ⊗ Q are linearly equivalent.
Equations
- tensor_product.congr f g = linear_equiv.of_linear (tensor_product.map ↑f ↑g) (tensor_product.map ↑(f.symm) ↑(g.symm)) _ _
A tensor product analogue of mul_left_comm.
Equations
- tensor_product.left_comm R M N P = let e₁ : tensor_product R M (tensor_product R N P) ≃ₗ[R] tensor_product R (tensor_product R M N) P := (tensor_product.assoc R M N P).symm, e₂ : tensor_product R (tensor_product R M N) P ≃ₗ[R] tensor_product R (tensor_product R N M) P := tensor_product.congr (tensor_product.comm R M N) 1, e₃ : tensor_product R (tensor_product R N M) P ≃ₗ[R] tensor_product R N (tensor_product R M P) := tensor_product.assoc R N M P in e₁.trans (e₂.trans e₃)
This special case is worth defining explicitly since it is useful for defining multiplication on tensor products of modules carrying multiplications (e.g., associative rings, Lie rings, ...).
E.g., suppose M = P and N = Q and that M and N carry bilinear multiplications:
M ⊗ M → M and N ⊗ N → N. Using map, we can define (M ⊗ M) ⊗ (N ⊗ N) → M ⊗ N which, when
combined with this definition, yields a bilinear multiplication on M ⊗ N:
(M ⊗ N) ⊗ (M ⊗ N) → M ⊗ N. In particular we could use this to define the multiplication in
the tensor_product.semiring instance (currently defined "by hand" using tensor_product.mul).
See also mul_mul_mul_comm.
Equations
- tensor_product.tensor_tensor_tensor_comm R M N P Q = let e₁ : tensor_product R (tensor_product R M N) (tensor_product R P Q) ≃ₗ[R] tensor_product R M (tensor_product R N (tensor_product R P Q)) := tensor_product.assoc R M N (tensor_product R P Q), e₂ : tensor_product R M (tensor_product R N (tensor_product R P Q)) ≃ₗ[R] tensor_product R M (tensor_product R P (tensor_product R N Q)) := tensor_product.congr 1 (tensor_product.left_comm R N P Q), e₃ : tensor_product R M (tensor_product R P (tensor_product R N Q)) ≃ₗ[R] tensor_product R (tensor_product R M P) (tensor_product R N Q) := (tensor_product.assoc R M P (tensor_product R N Q)).symm in e₁.trans (e₂.trans e₃)
This special case is useful for describing the interplay between dual_tensor_hom_equiv and
composition of linear maps.
E.g., composition of linear maps gives a map (M → N) ⊗ (N → P) → (M → P), and applying
dual_tensor_hom_equiv.symm to the three hom-modules gives a map
(M.dual ⊗ N) ⊗ (N.dual ⊗ P) → (M.dual ⊗ P), which agrees with the application of contract_right
on N ⊗ N.dual after the suitable rebracketting.
Equations
- tensor_product.tensor_tensor_tensor_assoc R M N P Q = (tensor_product.assoc R (tensor_product R M N) P Q).symm.trans (tensor_product.congr (tensor_product.assoc R M N P) 1)
ltensor M f : M ⊗ N →ₗ M ⊗ P is the natural linear map induced by f : N →ₗ P.
Equations
rtensor f M : N₁ ⊗ M →ₗ N₂ ⊗ M is the natural linear map induced by f : N₁ →ₗ N₂.
Equations
ltensor_hom M is the natural linear map that sends a linear map f : N →ₗ P to M ⊗ f.
Equations
- linear_map.ltensor_hom M = {to_fun := linear_map.ltensor M _inst_11, map_add' := _, map_smul' := _}
rtensor_hom M is the natural linear map that sends a linear map f : N →ₗ P to M ⊗ f.
Equations
- linear_map.rtensor_hom M = {to_fun := λ (f : N →ₗ[R] P), linear_map.rtensor M f, map_add' := _, map_smul' := _}
Auxiliary function to defining negation multiplication on tensor product.
Equations
- tensor_product.neg.aux R = ⇑free_add_monoid.lift (λ (p : M × N), (-p.fst) ⊗ₜ[R] p.snd)
Equations
- tensor_product.has_neg = {neg := ⇑((add_con_gen (tensor_product.eqv R M N)).lift (tensor_product.neg.aux R) tensor_product.has_neg._proof_1)}
Equations
- tensor_product.add_comm_group = {add := add_comm_monoid.add tensor_product.add_comm_monoid, add_assoc := _, zero := add_comm_monoid.zero tensor_product.add_comm_monoid, zero_add := _, add_zero := _, nsmul := add_comm_monoid.nsmul tensor_product.add_comm_monoid, nsmul_zero' := _, nsmul_succ' := _, neg := has_neg.neg tensor_product.has_neg, sub := λ (_x _x_1 : tensor_product R M N), add_zero_class.add _x (-_x_1), sub_eq_add_neg := _, zsmul := λ (n : ℤ) (v : tensor_product R M N), n • v, zsmul_zero' := _, zsmul_succ' := _, zsmul_neg' := _, add_left_neg := _, add_comm := _}
While the tensor product will automatically inherit a ℤ-module structure from
add_comm_group.int_module, that structure won't be compatible with lemmas like tmul_smul unless
we use a ℤ-module instance provided by tensor_product.left_module.
When R is a ring we get the required tensor_product.compatible_smul instance through
is_scalar_tower, but when it is only a semiring we need to build it from scratch.
The instance diamond in compatible_smul doesn't matter because it's in Prop.