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linear_independent.lean
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linear_independent.lean
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/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Alexander Bentkamp, Anne Baanen
-/
import algebra.big_operators.fin
import linear_algebra.finsupp
import linear_algebra.prod
import set_theory.cardinal.basic
/-!
# Linear independence
> THIS FILE IS SYNCHRONIZED WITH MATHLIB4.
> Any changes to this file require a corresponding PR to mathlib4.
This file defines linear independence in a module or vector space.
It is inspired by Isabelle/HOL's linear algebra, and hence indirectly by HOL Light.
We define `linear_independent R v` as `ker (finsupp.total ι M R v) = ⊥`. Here `finsupp.total` is the
linear map sending a function `f : ι →₀ R` with finite support to the linear combination of vectors
from `v` with these coefficients. Then we prove that several other statements are equivalent to this
one, including injectivity of `finsupp.total ι M R v` and some versions with explicitly written
linear combinations.
## Main definitions
All definitions are given for families of vectors, i.e. `v : ι → M` where `M` is the module or
vector space and `ι : Type*` is an arbitrary indexing type.
* `linear_independent R v` states that the elements of the family `v` are linearly independent.
* `linear_independent.repr hv x` returns the linear combination representing `x : span R (range v)`
on the linearly independent vectors `v`, given `hv : linear_independent R v`
(using classical choice). `linear_independent.repr hv` is provided as a linear map.
## Main statements
We prove several specialized tests for linear independence of families of vectors and of sets of
vectors.
* `fintype.linear_independent_iff`: if `ι` is a finite type, then any function `f : ι → R` has
finite support, so we can reformulate the statement using `∑ i : ι, f i • v i` instead of a sum
over an auxiliary `s : finset ι`;
* `linear_independent_empty_type`: a family indexed by an empty type is linearly independent;
* `linear_independent_unique_iff`: if `ι` is a singleton, then `linear_independent K v` is
equivalent to `v default ≠ 0`;
* linear_independent_option`, `linear_independent_sum`, `linear_independent_fin_cons`,
`linear_independent_fin_succ`: type-specific tests for linear independence of families of vector
fields;
* `linear_independent_insert`, `linear_independent_union`, `linear_independent_pair`,
`linear_independent_singleton`: linear independence tests for set operations.
In many cases we additionally provide dot-style operations (e.g., `linear_independent.union`) to
make the linear independence tests usable as `hv.insert ha` etc.
We also prove that, when working over a division ring,
any family of vectors includes a linear independent subfamily spanning the same subspace.
## Implementation notes
We use families instead of sets because it allows us to say that two identical vectors are linearly
dependent.
If you want to use sets, use the family `(λ x, x : s → M)` given a set `s : set M`. The lemmas
`linear_independent.to_subtype_range` and `linear_independent.of_subtype_range` connect those two
worlds.
## Tags
linearly dependent, linear dependence, linearly independent, linear independence
-/
noncomputable theory
open function set submodule
open_locale classical big_operators cardinal
universes u
variables {ι : Type*} {ι' : Type*} {R : Type*} {K : Type*}
variables {M : Type*} {M' M'' : Type*} {V : Type u} {V' : Type*}
section module
variables {v : ι → M}
variables [semiring R] [add_comm_monoid M] [add_comm_monoid M'] [add_comm_monoid M'']
variables [module R M] [module R M'] [module R M'']
variables {a b : R} {x y : M}
variables (R) (v)
/-- `linear_independent R v` states the family of vectors `v` is linearly independent over `R`. -/
def linear_independent : Prop := (finsupp.total ι M R v).ker = ⊥
variables {R} {v}
theorem linear_independent_iff : linear_independent R v ↔
∀l, finsupp.total ι M R v l = 0 → l = 0 :=
by simp [linear_independent, linear_map.ker_eq_bot']
theorem linear_independent_iff' : linear_independent R v ↔
∀ s : finset ι, ∀ g : ι → R, ∑ i in s, g i • v i = 0 → ∀ i ∈ s, g i = 0 :=
linear_independent_iff.trans
⟨λ hf s g hg i his, have h : _ := hf (∑ i in s, finsupp.single i (g i)) $
by simpa only [linear_map.map_sum, finsupp.total_single] using hg, calc
g i = (finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (finsupp.single i (g i)) :
by rw [finsupp.lapply_apply, finsupp.single_eq_same]
... = ∑ j in s, (finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (finsupp.single j (g j)) :
eq.symm $ finset.sum_eq_single i
(λ j hjs hji, by rw [finsupp.lapply_apply, finsupp.single_eq_of_ne hji])
(λ hnis, hnis.elim his)
... = (∑ j in s, finsupp.single j (g j)) i : (finsupp.lapply i : (ι →₀ R) →ₗ[R] R).map_sum.symm
... = 0 : finsupp.ext_iff.1 h i,
λ hf l hl, finsupp.ext $ λ i, classical.by_contradiction $ λ hni, hni $ hf _ _ hl _ $
finsupp.mem_support_iff.2 hni⟩
theorem linear_independent_iff'' :
linear_independent R v ↔ ∀ (s : finset ι) (g : ι → R) (hg : ∀ i ∉ s, g i = 0),
∑ i in s, g i • v i = 0 → ∀ i, g i = 0 :=
linear_independent_iff'.trans ⟨λ H s g hg hv i, if his : i ∈ s then H s g hv i his else hg i his,
λ H s g hg i hi, by { convert H s (λ j, if j ∈ s then g j else 0) (λ j hj, if_neg hj)
(by simp_rw [ite_smul, zero_smul, finset.sum_extend_by_zero, hg]) i,
exact (if_pos hi).symm }⟩
theorem not_linear_independent_iff : ¬ linear_independent R v ↔
∃ s : finset ι, ∃ g : ι → R, (∑ i in s, g i • v i) = 0 ∧ (∃ i ∈ s, g i ≠ 0) :=
begin
rw linear_independent_iff',
simp only [exists_prop, not_forall],
end
theorem fintype.linear_independent_iff [fintype ι] :
linear_independent R v ↔ ∀ g : ι → R, ∑ i, g i • v i = 0 → ∀ i, g i = 0 :=
begin
refine ⟨λ H g, by simpa using linear_independent_iff'.1 H finset.univ g,
λ H, linear_independent_iff''.2 $ λ s g hg hs i, H _ _ _⟩,
rw ← hs,
refine (finset.sum_subset (finset.subset_univ _) (λ i _ hi, _)).symm,
rw [hg i hi, zero_smul]
end
/-- A finite family of vectors `v i` is linear independent iff the linear map that sends
`c : ι → R` to `∑ i, c i • v i` has the trivial kernel. -/
theorem fintype.linear_independent_iff' [fintype ι] :
linear_independent R v ↔
(linear_map.lsum R (λ i : ι, R) ℕ (λ i, linear_map.id.smul_right (v i))).ker = ⊥ :=
by simp [fintype.linear_independent_iff, linear_map.ker_eq_bot', funext_iff]; skip
lemma fintype.not_linear_independent_iff [fintype ι] :
¬linear_independent R v ↔ ∃ g : ι → R, (∑ i, g i • v i) = 0 ∧ (∃ i, g i ≠ 0) :=
by simpa using (not_iff_not.2 fintype.linear_independent_iff)
lemma linear_independent_empty_type [is_empty ι] : linear_independent R v :=
linear_independent_iff.mpr $ λ v hv, subsingleton.elim v 0
lemma linear_independent.ne_zero [nontrivial R]
(i : ι) (hv : linear_independent R v) : v i ≠ 0 :=
λ h, zero_ne_one' R $ eq.symm begin
suffices : (finsupp.single i 1 : ι →₀ R) i = 0, {simpa},
rw linear_independent_iff.1 hv (finsupp.single i 1),
{ simp },
{ simp [h] }
end
/-- A subfamily of a linearly independent family (i.e., a composition with an injective map) is a
linearly independent family. -/
lemma linear_independent.comp
(h : linear_independent R v) (f : ι' → ι) (hf : injective f) : linear_independent R (v ∘ f) :=
begin
rw [linear_independent_iff, finsupp.total_comp],
intros l hl,
have h_map_domain : ∀ x, (finsupp.map_domain f l) (f x) = 0,
by rw linear_independent_iff.1 h (finsupp.map_domain f l) hl; simp,
ext x,
convert h_map_domain x,
rw [finsupp.map_domain_apply hf]
end
lemma linear_independent.coe_range (i : linear_independent R v) :
linear_independent R (coe : range v → M) :=
by simpa using i.comp _ (range_splitting_injective v)
/-- If `v` is a linearly independent family of vectors and the kernel of a linear map `f` is
disjoint with the submodule spanned by the vectors of `v`, then `f ∘ v` is a linearly independent
family of vectors. See also `linear_independent.map'` for a special case assuming `ker f = ⊥`. -/
lemma linear_independent.map (hv : linear_independent R v) {f : M →ₗ[R] M'}
(hf_inj : disjoint (span R (range v)) f.ker) : linear_independent R (f ∘ v) :=
begin
rw [disjoint_iff_inf_le, ← set.image_univ, finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap,
map_le_iff_le_comap, comap_bot, finsupp.supported_univ, top_inf_eq] at hf_inj,
unfold linear_independent at hv ⊢,
rw [hv, le_bot_iff] at hf_inj,
haveI : inhabited M := ⟨0⟩,
rw [finsupp.total_comp, @finsupp.lmap_domain_total _ _ R _ _ _ _ _ _ _ _ _ _ f,
linear_map.ker_comp, hf_inj],
exact λ _, rfl,
end
/-- An injective linear map sends linearly independent families of vectors to linearly independent
families of vectors. See also `linear_independent.map` for a more general statement. -/
lemma linear_independent.map' (hv : linear_independent R v) (f : M →ₗ[R] M')
(hf_inj : f.ker = ⊥) : linear_independent R (f ∘ v) :=
hv.map $ by simp [hf_inj]
/-- If the image of a family of vectors under a linear map is linearly independent, then so is
the original family. -/
lemma linear_independent.of_comp (f : M →ₗ[R] M') (hfv : linear_independent R (f ∘ v)) :
linear_independent R v :=
linear_independent_iff'.2 $ λ s g hg i his,
have ∑ (i : ι) in s, g i • f (v i) = 0,
by simp_rw [← f.map_smul, ← f.map_sum, hg, f.map_zero],
linear_independent_iff'.1 hfv s g this i his
/-- If `f` is an injective linear map, then the family `f ∘ v` is linearly independent
if and only if the family `v` is linearly independent. -/
protected lemma linear_map.linear_independent_iff (f : M →ₗ[R] M') (hf_inj : f.ker = ⊥) :
linear_independent R (f ∘ v) ↔ linear_independent R v :=
⟨λ h, h.of_comp f, λ h, h.map $ by simp only [hf_inj, disjoint_bot_right]⟩
@[nontriviality]
lemma linear_independent_of_subsingleton [subsingleton R] : linear_independent R v :=
linear_independent_iff.2 (λ l hl, subsingleton.elim _ _)
theorem linear_independent_equiv (e : ι ≃ ι') {f : ι' → M} :
linear_independent R (f ∘ e) ↔ linear_independent R f :=
⟨λ h, function.comp.right_id f ▸ e.self_comp_symm ▸ h.comp _ e.symm.injective,
λ h, h.comp _ e.injective⟩
theorem linear_independent_equiv' (e : ι ≃ ι') {f : ι' → M} {g : ι → M} (h : f ∘ e = g) :
linear_independent R g ↔ linear_independent R f :=
h ▸ linear_independent_equiv e
theorem linear_independent_subtype_range {ι} {f : ι → M} (hf : injective f) :
linear_independent R (coe : range f → M) ↔ linear_independent R f :=
iff.symm $ linear_independent_equiv' (equiv.of_injective f hf) rfl
alias linear_independent_subtype_range ↔ linear_independent.of_subtype_range _
theorem linear_independent_image {ι} {s : set ι} {f : ι → M} (hf : set.inj_on f s) :
linear_independent R (λ x : s, f x) ↔ linear_independent R (λ x : f '' s, (x : M)) :=
linear_independent_equiv' (equiv.set.image_of_inj_on _ _ hf) rfl
lemma linear_independent_span (hs : linear_independent R v) :
@linear_independent ι R (span R (range v))
(λ i : ι, ⟨v i, subset_span (mem_range_self i)⟩) _ _ _ :=
linear_independent.of_comp (span R (range v)).subtype hs
/-- See `linear_independent.fin_cons` for a family of elements in a vector space. -/
lemma linear_independent.fin_cons' {m : ℕ} (x : M) (v : fin m → M)
(hli : linear_independent R v)
(x_ortho : (∀ (c : R) (y : submodule.span R (set.range v)), c • x + y = (0 : M) → c = 0)) :
linear_independent R (fin.cons x v : fin m.succ → M) :=
begin
rw fintype.linear_independent_iff at hli ⊢,
rintros g total_eq j,
simp_rw [fin.sum_univ_succ, fin.cons_zero, fin.cons_succ] at total_eq,
have : g 0 = 0,
{ refine x_ortho (g 0) ⟨∑ (i : fin m), g i.succ • v i, _⟩ total_eq,
exact sum_mem (λ i _, smul_mem _ _ (subset_span ⟨i, rfl⟩)) },
rw [this, zero_smul, zero_add] at total_eq,
exact fin.cases this (hli _ total_eq) j,
end
/-- A set of linearly independent vectors in a module `M` over a semiring `K` is also linearly
independent over a subring `R` of `K`.
The implementation uses minimal assumptions about the relationship between `R`, `K` and `M`.
The version where `K` is an `R`-algebra is `linear_independent.restrict_scalars_algebras`.
-/
lemma linear_independent.restrict_scalars [semiring K] [smul_with_zero R K] [module K M]
[is_scalar_tower R K M]
(hinj : function.injective (λ r : R, r • (1 : K))) (li : linear_independent K v) :
linear_independent R v :=
begin
refine linear_independent_iff'.mpr (λ s g hg i hi, hinj (eq.trans _ (zero_smul _ _).symm)),
refine (linear_independent_iff'.mp li : _) _ _ _ i hi,
simp_rw [smul_assoc, one_smul],
exact hg,
end
/-- Every finite subset of a linearly independent set is linearly independent. -/
lemma linear_independent_finset_map_embedding_subtype
(s : set M) (li : linear_independent R (coe : s → M)) (t : finset s) :
linear_independent R (coe : (finset.map (embedding.subtype s) t) → M) :=
begin
let f : t.map (embedding.subtype s) → s := λ x, ⟨x.1, begin
obtain ⟨x, h⟩ := x,
rw [finset.mem_map] at h,
obtain ⟨a, ha, rfl⟩ := h,
simp only [subtype.coe_prop, embedding.coe_subtype],
end⟩,
convert linear_independent.comp li f _,
rintros ⟨x, hx⟩ ⟨y, hy⟩,
rw [finset.mem_map] at hx hy,
obtain ⟨a, ha, rfl⟩ := hx,
obtain ⟨b, hb, rfl⟩ := hy,
simp only [imp_self, subtype.mk_eq_mk],
end
/--
If every finite set of linearly independent vectors has cardinality at most `n`,
then the same is true for arbitrary sets of linearly independent vectors.
-/
lemma linear_independent_bounded_of_finset_linear_independent_bounded {n : ℕ}
(H : ∀ s : finset M, linear_independent R (λ i : s, (i : M)) → s.card ≤ n) :
∀ s : set M, linear_independent R (coe : s → M) → #s ≤ n :=
begin
intros s li,
apply cardinal.card_le_of,
intro t,
rw ← finset.card_map (embedding.subtype s),
apply H,
apply linear_independent_finset_map_embedding_subtype _ li,
end
section subtype
/-! The following lemmas use the subtype defined by a set in `M` as the index set `ι`. -/
theorem linear_independent_comp_subtype {s : set ι} :
linear_independent R (v ∘ coe : s → M) ↔
∀ l ∈ (finsupp.supported R R s), (finsupp.total ι M R v) l = 0 → l = 0 :=
begin
simp only [linear_independent_iff, (∘), finsupp.mem_supported, finsupp.total_apply,
set.subset_def, finset.mem_coe],
split,
{ intros h l hl₁ hl₂,
have := h (l.subtype_domain s) ((finsupp.sum_subtype_domain_index hl₁).trans hl₂),
exact (finsupp.subtype_domain_eq_zero_iff hl₁).1 this },
{ intros h l hl,
refine finsupp.emb_domain_eq_zero.1 (h (l.emb_domain $ function.embedding.subtype s) _ _),
{ suffices : ∀ i hi, ¬l ⟨i, hi⟩ = 0 → i ∈ s, by simpa,
intros, assumption },
{ rwa [finsupp.emb_domain_eq_map_domain, finsupp.sum_map_domain_index],
exacts [λ _, zero_smul _ _, λ _ _ _, add_smul _ _ _] } }
end
lemma linear_dependent_comp_subtype' {s : set ι} :
¬ linear_independent R (v ∘ coe : s → M) ↔
∃ f : ι →₀ R, f ∈ finsupp.supported R R s ∧ finsupp.total ι M R v f = 0 ∧ f ≠ 0 :=
by simp [linear_independent_comp_subtype]
/-- A version of `linear_dependent_comp_subtype'` with `finsupp.total` unfolded. -/
lemma linear_dependent_comp_subtype {s : set ι} :
¬ linear_independent R (v ∘ coe : s → M) ↔
∃ f : ι →₀ R, f ∈ finsupp.supported R R s ∧ ∑ i in f.support, f i • v i = 0 ∧ f ≠ 0 :=
linear_dependent_comp_subtype'
theorem linear_independent_subtype {s : set M} :
linear_independent R (λ x, x : s → M) ↔
∀ l ∈ (finsupp.supported R R s), (finsupp.total M M R id) l = 0 → l = 0 :=
by apply @linear_independent_comp_subtype _ _ _ id
theorem linear_independent_comp_subtype_disjoint {s : set ι} :
linear_independent R (v ∘ coe : s → M) ↔
disjoint (finsupp.supported R R s) (finsupp.total ι M R v).ker :=
by rw [linear_independent_comp_subtype, linear_map.disjoint_ker]
theorem linear_independent_subtype_disjoint {s : set M} :
linear_independent R (λ x, x : s → M) ↔
disjoint (finsupp.supported R R s) (finsupp.total M M R id).ker :=
by apply @linear_independent_comp_subtype_disjoint _ _ _ id
theorem linear_independent_iff_total_on {s : set M} :
linear_independent R (λ x, x : s → M) ↔ (finsupp.total_on M M R id s).ker = ⊥ :=
by rw [finsupp.total_on, linear_map.ker, linear_map.comap_cod_restrict, submodule.map_bot,
comap_bot, linear_map.ker_comp, linear_independent_subtype_disjoint, disjoint_iff_inf_le,
← map_comap_subtype, map_le_iff_le_comap, comap_bot, ker_subtype, le_bot_iff]
lemma linear_independent.restrict_of_comp_subtype {s : set ι}
(hs : linear_independent R (v ∘ coe : s → M)) :
linear_independent R (s.restrict v) :=
hs
variables (R M)
lemma linear_independent_empty : linear_independent R (λ x, x : (∅ : set M) → M) :=
by simp [linear_independent_subtype_disjoint]
variables {R M}
lemma linear_independent.mono {t s : set M} (h : t ⊆ s) :
linear_independent R (λ x, x : s → M) → linear_independent R (λ x, x : t → M) :=
begin
simp only [linear_independent_subtype_disjoint],
exact (disjoint.mono_left (finsupp.supported_mono h))
end
lemma linear_independent_of_finite (s : set M)
(H : ∀ t ⊆ s, set.finite t → linear_independent R (λ x, x : t → M)) :
linear_independent R (λ x, x : s → M) :=
linear_independent_subtype.2 $
λ l hl, linear_independent_subtype.1 (H _ hl (finset.finite_to_set _)) l (subset.refl _)
lemma linear_independent_Union_of_directed {η : Type*}
{s : η → set M} (hs : directed (⊆) s)
(h : ∀ i, linear_independent R (λ x, x : s i → M)) :
linear_independent R (λ x, x : (⋃ i, s i) → M) :=
begin
by_cases hη : nonempty η,
{ resetI,
refine linear_independent_of_finite (⋃ i, s i) (λ t ht ft, _),
rcases finite_subset_Union ft ht with ⟨I, fi, hI⟩,
rcases hs.finset_le fi.to_finset with ⟨i, hi⟩,
exact (h i).mono (subset.trans hI $ Union₂_subset $
λ j hj, hi j (fi.mem_to_finset.2 hj)) },
{ refine (linear_independent_empty _ _).mono _,
rintro _ ⟨_, ⟨i, _⟩, _⟩, exact hη ⟨i⟩ }
end
lemma linear_independent_sUnion_of_directed {s : set (set M)}
(hs : directed_on (⊆) s)
(h : ∀ a ∈ s, linear_independent R (λ x, x : (a : set M) → M)) :
linear_independent R (λ x, x : (⋃₀ s) → M) :=
by rw sUnion_eq_Union; exact
linear_independent_Union_of_directed hs.directed_coe (by simpa using h)
lemma linear_independent_bUnion_of_directed {η} {s : set η} {t : η → set M}
(hs : directed_on (t ⁻¹'o (⊆)) s) (h : ∀a∈s, linear_independent R (λ x, x : t a → M)) :
linear_independent R (λ x, x : (⋃a∈s, t a) → M) :=
by rw bUnion_eq_Union; exact
linear_independent_Union_of_directed (directed_comp.2 $ hs.directed_coe) (by simpa using h)
end subtype
end module
/-! ### Properties which require `ring R` -/
section module
variables {v : ι → M}
variables [ring R] [add_comm_group M] [add_comm_group M'] [add_comm_group M'']
variables [module R M] [module R M'] [module R M'']
variables {a b : R} {x y : M}
theorem linear_independent_iff_injective_total : linear_independent R v ↔
function.injective (finsupp.total ι M R v) :=
linear_independent_iff.trans
(injective_iff_map_eq_zero (finsupp.total ι M R v).to_add_monoid_hom).symm
alias linear_independent_iff_injective_total ↔ linear_independent.injective_total _
lemma linear_independent.injective [nontrivial R] (hv : linear_independent R v) :
injective v :=
begin
intros i j hij,
let l : ι →₀ R := finsupp.single i (1 : R) - finsupp.single j 1,
have h_total : finsupp.total ι M R v l = 0,
{ simp_rw [linear_map.map_sub, finsupp.total_apply],
simp [hij] },
have h_single_eq : finsupp.single i (1 : R) = finsupp.single j 1,
{ rw linear_independent_iff at hv,
simp [eq_add_of_sub_eq' (hv l h_total)] },
simpa [finsupp.single_eq_single_iff] using h_single_eq
end
theorem linear_independent.to_subtype_range {ι} {f : ι → M} (hf : linear_independent R f) :
linear_independent R (coe : range f → M) :=
begin
nontriviality R,
exact (linear_independent_subtype_range hf.injective).2 hf
end
theorem linear_independent.to_subtype_range' {ι} {f : ι → M} (hf : linear_independent R f)
{t} (ht : range f = t) :
linear_independent R (coe : t → M) :=
ht ▸ hf.to_subtype_range
theorem linear_independent.image_of_comp {ι ι'} (s : set ι) (f : ι → ι') (g : ι' → M)
(hs : linear_independent R (λ x : s, g (f x))) :
linear_independent R (λ x : f '' s, g x) :=
begin
nontriviality R,
have : inj_on f s, from inj_on_iff_injective.2 hs.injective.of_comp,
exact (linear_independent_equiv' (equiv.set.image_of_inj_on f s this) rfl).1 hs
end
theorem linear_independent.image {ι} {s : set ι} {f : ι → M}
(hs : linear_independent R (λ x : s, f x)) : linear_independent R (λ x : f '' s, (x : M)) :=
by convert linear_independent.image_of_comp s f id hs
lemma linear_independent.group_smul
{G : Type*} [hG : group G] [distrib_mul_action G R] [distrib_mul_action G M]
[is_scalar_tower G R M] [smul_comm_class G R M] {v : ι → M} (hv : linear_independent R v)
(w : ι → G) : linear_independent R (w • v) :=
begin
rw linear_independent_iff'' at hv ⊢,
intros s g hgs hsum i,
refine (smul_eq_zero_iff_eq (w i)).1 _,
refine hv s (λ i, w i • g i) (λ i hi, _) _ i,
{ dsimp only,
exact (hgs i hi).symm ▸ smul_zero _ },
{ rw [← hsum, finset.sum_congr rfl _],
intros, erw [pi.smul_apply, smul_assoc, smul_comm] },
end
-- This lemma cannot be proved with `linear_independent.group_smul` since the action of
-- `Rˣ` on `R` is not commutative.
lemma linear_independent.units_smul {v : ι → M} (hv : linear_independent R v)
(w : ι → Rˣ) : linear_independent R (w • v) :=
begin
rw linear_independent_iff'' at hv ⊢,
intros s g hgs hsum i,
rw ← (w i).mul_left_eq_zero,
refine hv s (λ i, g i • w i) (λ i hi, _) _ i,
{ dsimp only,
exact (hgs i hi).symm ▸ zero_smul _ _ },
{ rw [← hsum, finset.sum_congr rfl _],
intros,
erw [pi.smul_apply, smul_assoc],
refl }
end
section maximal
universes v w
/--
A linearly independent family is maximal if there is no strictly larger linearly independent family.
-/
@[nolint unused_arguments]
def linear_independent.maximal {ι : Type w} {R : Type u} [semiring R]
{M : Type v} [add_comm_monoid M] [module R M] {v : ι → M} (i : linear_independent R v) : Prop :=
∀ (s : set M) (i' : linear_independent R (coe : s → M)) (h : range v ≤ s), range v = s
/--
An alternative characterization of a maximal linearly independent family,
quantifying over types (in the same universe as `M`) into which the indexing family injects.
-/
lemma linear_independent.maximal_iff {ι : Type w} {R : Type u} [ring R] [nontrivial R]
{M : Type v} [add_comm_group M] [module R M] {v : ι → M} (i : linear_independent R v) :
i.maximal ↔ ∀ (κ : Type v) (w : κ → M) (i' : linear_independent R w)
(j : ι → κ) (h : w ∘ j = v), surjective j :=
begin
fsplit,
{ rintros p κ w i' j rfl,
specialize p (range w) i'.coe_range (range_comp_subset_range _ _),
rw [range_comp, ←@image_univ _ _ w] at p,
exact range_iff_surjective.mp (image_injective.mpr i'.injective p), },
{ intros p w i' h,
specialize p w (coe : w → M) i'
(λ i, ⟨v i, range_subset_iff.mp h i⟩)
(by { ext, simp, }),
have q := congr_arg (λ s, (coe : w → M) '' s) p.range_eq,
dsimp at q,
rw [←image_univ, image_image] at q,
simpa using q, },
end
end maximal
/-- Linear independent families are injective, even if you multiply either side. -/
lemma linear_independent.eq_of_smul_apply_eq_smul_apply {M : Type*} [add_comm_group M] [module R M]
{v : ι → M} (li : linear_independent R v) (c d : R) (i j : ι)
(hc : c ≠ 0) (h : c • v i = d • v j) : i = j :=
begin
let l : ι →₀ R := finsupp.single i c - finsupp.single j d,
have h_total : finsupp.total ι M R v l = 0,
{ simp_rw [linear_map.map_sub, finsupp.total_apply],
simp [h] },
have h_single_eq : finsupp.single i c = finsupp.single j d,
{ rw linear_independent_iff at li,
simp [eq_add_of_sub_eq' (li l h_total)] },
rcases (finsupp.single_eq_single_iff _ _ _ _).mp h_single_eq with ⟨this, _⟩ | ⟨hc, _⟩,
{ exact this },
{ contradiction },
end
section subtype
/-! The following lemmas use the subtype defined by a set in `M` as the index set `ι`. -/
lemma linear_independent.disjoint_span_image (hv : linear_independent R v) {s t : set ι}
(hs : disjoint s t) :
disjoint (submodule.span R $ v '' s) (submodule.span R $ v '' t) :=
begin
simp only [disjoint_def, finsupp.mem_span_image_iff_total],
rintros _ ⟨l₁, hl₁, rfl⟩ ⟨l₂, hl₂, H⟩,
rw [hv.injective_total.eq_iff] at H, subst l₂,
have : l₁ = 0 :=
submodule.disjoint_def.mp (finsupp.disjoint_supported_supported hs) _ hl₁ hl₂,
simp [this]
end
lemma linear_independent.not_mem_span_image [nontrivial R] (hv : linear_independent R v) {s : set ι}
{x : ι} (h : x ∉ s) :
v x ∉ submodule.span R (v '' s) :=
begin
have h' : v x ∈ submodule.span R (v '' {x}),
{ rw set.image_singleton,
exact mem_span_singleton_self (v x), },
intro w,
apply linear_independent.ne_zero x hv,
refine disjoint_def.1 (hv.disjoint_span_image _) (v x) h' w,
simpa using h,
end
lemma linear_independent.total_ne_of_not_mem_support [nontrivial R] (hv : linear_independent R v)
{x : ι} (f : ι →₀ R) (h : x ∉ f.support) :
finsupp.total ι M R v f ≠ v x :=
begin
replace h : x ∉ (f.support : set ι) := h,
have p := hv.not_mem_span_image h,
intro w,
rw ←w at p,
rw finsupp.span_image_eq_map_total at p,
simp only [not_exists, not_and, mem_map] at p,
exact p f (f.mem_supported_support R) rfl,
end
lemma linear_independent_sum {v : ι ⊕ ι' → M} :
linear_independent R v ↔ linear_independent R (v ∘ sum.inl) ∧
linear_independent R (v ∘ sum.inr) ∧
disjoint (submodule.span R (range (v ∘ sum.inl))) (submodule.span R (range (v ∘ sum.inr))) :=
begin
rw [range_comp v, range_comp v],
refine ⟨λ h, ⟨h.comp _ sum.inl_injective, h.comp _ sum.inr_injective,
h.disjoint_span_image is_compl_range_inl_range_inr.1⟩, _⟩,
rintro ⟨hl, hr, hlr⟩,
rw [linear_independent_iff'] at *,
intros s g hg i hi,
have : ∑ i in s.preimage sum.inl (sum.inl_injective.inj_on _), (λ x, g x • v x) (sum.inl i) +
∑ i in s.preimage sum.inr (sum.inr_injective.inj_on _), (λ x, g x • v x) (sum.inr i) = 0,
{ rw [finset.sum_preimage', finset.sum_preimage', ← finset.sum_union, ← finset.filter_or],
{ simpa only [← mem_union, range_inl_union_range_inr, mem_univ, finset.filter_true] },
{ exact finset.disjoint_filter.2
(λ x _ hx, disjoint_left.1 is_compl_range_inl_range_inr.1 hx) } },
{ rw ← eq_neg_iff_add_eq_zero at this,
rw [disjoint_def'] at hlr,
have A := hlr _ (sum_mem $ λ i hi, _) _ (neg_mem $ sum_mem $ λ i hi, _) this,
{ cases i with i i,
{ exact hl _ _ A i (finset.mem_preimage.2 hi) },
{ rw [this, neg_eq_zero] at A,
exact hr _ _ A i (finset.mem_preimage.2 hi) } },
{ exact smul_mem _ _ (subset_span ⟨sum.inl i, mem_range_self _, rfl⟩) },
{ exact smul_mem _ _ (subset_span ⟨sum.inr i, mem_range_self _, rfl⟩) } }
end
lemma linear_independent.sum_type {v' : ι' → M} (hv : linear_independent R v)
(hv' : linear_independent R v')
(h : disjoint (submodule.span R (range v)) (submodule.span R (range v'))) :
linear_independent R (sum.elim v v') :=
linear_independent_sum.2 ⟨hv, hv', h⟩
lemma linear_independent.union {s t : set M}
(hs : linear_independent R (λ x, x : s → M)) (ht : linear_independent R (λ x, x : t → M))
(hst : disjoint (span R s) (span R t)) :
linear_independent R (λ x, x : (s ∪ t) → M) :=
(hs.sum_type ht $ by simpa).to_subtype_range' $ by simp
lemma linear_independent_Union_finite_subtype {ι : Type*} {f : ι → set M}
(hl : ∀i, linear_independent R (λ x, x : f i → M))
(hd : ∀i, ∀t:set ι, t.finite → i ∉ t → disjoint (span R (f i)) (⨆i∈t, span R (f i))) :
linear_independent R (λ x, x : (⋃i, f i) → M) :=
begin
rw [Union_eq_Union_finset f],
apply linear_independent_Union_of_directed,
{ apply directed_of_sup,
exact (λ t₁ t₂ ht, Union_mono $ λ i, Union_subset_Union_const $ λ h, ht h) },
assume t,
induction t using finset.induction_on with i s his ih,
{ refine (linear_independent_empty _ _).mono _,
simp },
{ rw [finset.set_bUnion_insert],
refine (hl _).union ih _,
rw span_Union₂,
exact hd i s s.finite_to_set his }
end
lemma linear_independent_Union_finite {η : Type*} {ιs : η → Type*}
{f : Π j : η, ιs j → M}
(hindep : ∀j, linear_independent R (f j))
(hd : ∀i, ∀t:set η, t.finite → i ∉ t →
disjoint (span R (range (f i))) (⨆i∈t, span R (range (f i)))) :
linear_independent R (λ ji : Σ j, ιs j, f ji.1 ji.2) :=
begin
nontriviality R,
apply linear_independent.of_subtype_range,
{ rintros ⟨x₁, x₂⟩ ⟨y₁, y₂⟩ hxy,
by_cases h_cases : x₁ = y₁,
subst h_cases,
{ apply sigma.eq,
rw linear_independent.injective (hindep _) hxy,
refl },
{ have h0 : f x₁ x₂ = 0,
{ apply disjoint_def.1 (hd x₁ {y₁} (finite_singleton y₁)
(λ h, h_cases (eq_of_mem_singleton h))) (f x₁ x₂) (subset_span (mem_range_self _)),
rw supr_singleton,
simp only at hxy,
rw hxy,
exact (subset_span (mem_range_self y₂)) },
exact false.elim ((hindep x₁).ne_zero _ h0) } },
rw range_sigma_eq_Union_range,
apply linear_independent_Union_finite_subtype (λ j, (hindep j).to_subtype_range) hd,
end
end subtype
section repr
variables (hv : linear_independent R v)
/-- Canonical isomorphism between linear combinations and the span of linearly independent vectors.
-/
@[simps {rhs_md := semireducible}]
def linear_independent.total_equiv (hv : linear_independent R v) :
(ι →₀ R) ≃ₗ[R] span R (range v) :=
begin
apply linear_equiv.of_bijective
(linear_map.cod_restrict (span R (range v)) (finsupp.total ι M R v) _),
split,
{ rw [← linear_map.ker_eq_bot, linear_map.ker_cod_restrict],
apply hv },
{ rw [← linear_map.range_eq_top, linear_map.range_eq_map, linear_map.map_cod_restrict,
← linear_map.range_le_iff_comap, range_subtype, submodule.map_top],
rw finsupp.range_total,
exact le_rfl },
{ intro l,
rw ← finsupp.range_total,
rw linear_map.mem_range,
apply mem_range_self l }
end
/-- Linear combination representing a vector in the span of linearly independent vectors.
Given a family of linearly independent vectors, we can represent any vector in their span as
a linear combination of these vectors. These are provided by this linear map.
It is simply one direction of `linear_independent.total_equiv`. -/
def linear_independent.repr (hv : linear_independent R v) :
span R (range v) →ₗ[R] ι →₀ R := hv.total_equiv.symm
@[simp] lemma linear_independent.total_repr (x) : finsupp.total ι M R v (hv.repr x) = x :=
subtype.ext_iff.1 (linear_equiv.apply_symm_apply hv.total_equiv x)
lemma linear_independent.total_comp_repr :
(finsupp.total ι M R v).comp hv.repr = submodule.subtype _ :=
linear_map.ext $ hv.total_repr
lemma linear_independent.repr_ker : hv.repr.ker = ⊥ :=
by rw [linear_independent.repr, linear_equiv.ker]
lemma linear_independent.repr_range : hv.repr.range = ⊤ :=
by rw [linear_independent.repr, linear_equiv.range]
lemma linear_independent.repr_eq
{l : ι →₀ R} {x} (eq : finsupp.total ι M R v l = ↑x) :
hv.repr x = l :=
begin
have : ↑((linear_independent.total_equiv hv : (ι →₀ R) →ₗ[R] span R (range v)) l)
= finsupp.total ι M R v l := rfl,
have : (linear_independent.total_equiv hv : (ι →₀ R) →ₗ[R] span R (range v)) l = x,
{ rw eq at this,
exact subtype.ext_iff.2 this },
rw ←linear_equiv.symm_apply_apply hv.total_equiv l,
rw ←this,
refl,
end
lemma linear_independent.repr_eq_single (i) (x) (hx : ↑x = v i) :
hv.repr x = finsupp.single i 1 :=
begin
apply hv.repr_eq,
simp [finsupp.total_single, hx]
end
lemma linear_independent.span_repr_eq [nontrivial R] (x) :
span.repr R (set.range v) x = (hv.repr x).equiv_map_domain (equiv.of_injective _ hv.injective) :=
begin
have p : (span.repr R (set.range v) x).equiv_map_domain (equiv.of_injective _ hv.injective).symm =
hv.repr x,
{ apply (linear_independent.total_equiv hv).injective,
ext,
simp only [linear_independent.total_equiv_apply_coe, equiv.self_comp_of_injective_symm,
linear_independent.total_repr, finsupp.total_equiv_map_domain, span.finsupp_total_repr], },
ext ⟨_, ⟨i, rfl⟩⟩,
simp [←p],
end
-- TODO: why is this so slow?
lemma linear_independent_iff_not_smul_mem_span :
linear_independent R v ↔ (∀ (i : ι) (a : R), a • (v i) ∈ span R (v '' (univ \ {i})) → a = 0) :=
⟨ λ hv i a ha, begin
rw [finsupp.span_image_eq_map_total, mem_map] at ha,
rcases ha with ⟨l, hl, e⟩,
rw sub_eq_zero.1 (linear_independent_iff.1 hv (l - finsupp.single i a) (by simp [e])) at hl,
by_contra hn,
exact (not_mem_of_mem_diff (hl $ by simp [hn])) (mem_singleton _),
end, λ H, linear_independent_iff.2 $ λ l hl, begin
ext i, simp only [finsupp.zero_apply],
by_contra hn,
refine hn (H i _ _),
refine (finsupp.mem_span_image_iff_total _).2 ⟨finsupp.single i (l i) - l, _, _⟩,
{ rw finsupp.mem_supported',
intros j hj,
have hij : j = i :=
not_not.1
(λ hij : j ≠ i, hj ((mem_diff _).2 ⟨mem_univ _, λ h, hij (eq_of_mem_singleton h)⟩)),
simp [hij] },
{ simp [hl] }
end⟩
/-- See also `complete_lattice.independent_iff_linear_independent_of_ne_zero`. -/
lemma linear_independent.independent_span_singleton (hv : linear_independent R v) :
complete_lattice.independent $ λ i, R ∙ v i :=
begin
refine complete_lattice.independent_def.mp (λ i, _),
rw disjoint_iff_inf_le,
intros m hm,
simp only [mem_inf, mem_span_singleton, supr_subtype', ← span_range_eq_supr] at hm,
obtain ⟨⟨r, rfl⟩, hm⟩ := hm,
suffices : r = 0, { simp [this], },
apply linear_independent_iff_not_smul_mem_span.mp hv i,
convert hm,
ext,
simp,
end
variable (R)
lemma exists_maximal_independent' (s : ι → M) :
∃ I : set ι, linear_independent R (λ x : I, s x) ∧
∀ J : set ι, I ⊆ J → linear_independent R (λ x : J, s x) → I = J :=
begin
let indep : set ι → Prop := λ I, linear_independent R (s ∘ coe : I → M),
let X := { I : set ι // indep I },
let r : X → X → Prop := λ I J, I.1 ⊆ J.1,
have key : ∀ c : set X, is_chain r c → indep (⋃ (I : X) (H : I ∈ c), I),
{ intros c hc,
dsimp [indep],
rw [linear_independent_comp_subtype],
intros f hsupport hsum,
rcases eq_empty_or_nonempty c with rfl | hn,
{ simpa using hsupport },
haveI : is_refl X r := ⟨λ _, set.subset.refl _⟩,
obtain ⟨I, I_mem, hI⟩ : ∃ I ∈ c, (f.support : set ι) ⊆ I :=
hc.directed_on.exists_mem_subset_of_finset_subset_bUnion hn hsupport,
exact linear_independent_comp_subtype.mp I.2 f hI hsum },
have trans : transitive r := λ I J K, set.subset.trans,
obtain ⟨⟨I, hli : indep I⟩, hmax : ∀ a, r ⟨I, hli⟩ a → r a ⟨I, hli⟩⟩ :=
@exists_maximal_of_chains_bounded _ r
(λ c hc, ⟨⟨⋃ I ∈ c, (I : set ι), key c hc⟩, λ I, set.subset_bUnion_of_mem⟩) trans,
exact ⟨I, hli, λ J hsub hli, set.subset.antisymm hsub (hmax ⟨J, hli⟩ hsub)⟩,
end
lemma exists_maximal_independent (s : ι → M) : ∃ I : set ι, linear_independent R (λ x : I, s x) ∧
∀ i ∉ I, ∃ a : R, a ≠ 0 ∧ a • s i ∈ span R (s '' I) :=
begin
classical,
rcases exists_maximal_independent' R s with ⟨I, hIlinind, hImaximal⟩,
use [I, hIlinind],
intros i hi,
specialize hImaximal (I ∪ {i}) (by simp),
set J := I ∪ {i} with hJ,
have memJ : ∀ {x}, x ∈ J ↔ x = i ∨ x ∈ I, by simp [hJ],
have hiJ : i ∈ J := by simp,
have h := mt hImaximal _, swap,
{ intro h2,
rw h2 at hi,
exact absurd hiJ hi },
obtain ⟨f, supp_f, sum_f, f_ne⟩ := linear_dependent_comp_subtype.mp h,
have hfi : f i ≠ 0,
{ contrapose hIlinind,
refine linear_dependent_comp_subtype.mpr ⟨f, _, sum_f, f_ne⟩,
simp only [finsupp.mem_supported, hJ] at ⊢ supp_f,
rintro x hx,
refine (memJ.mp (supp_f hx)).resolve_left _,
rintro rfl,
exact hIlinind (finsupp.mem_support_iff.mp hx) },
use [f i, hfi],
have hfi' : i ∈ f.support := finsupp.mem_support_iff.mpr hfi,
rw [← finset.insert_erase hfi', finset.sum_insert (finset.not_mem_erase _ _),
add_eq_zero_iff_eq_neg] at sum_f,
rw sum_f,
refine neg_mem (sum_mem (λ c hc, smul_mem _ _ (subset_span ⟨c, _, rfl⟩))),
exact (memJ.mp (supp_f (finset.erase_subset _ _ hc))).resolve_left (finset.ne_of_mem_erase hc),
end
end repr
lemma surjective_of_linear_independent_of_span [nontrivial R]
(hv : linear_independent R v) (f : ι' ↪ ι)
(hss : range v ⊆ span R (range (v ∘ f))) :
surjective f :=
begin
intros i,
let repr : (span R (range (v ∘ f)) : Type*) → ι' →₀ R := (hv.comp f f.injective).repr,
let l := (repr ⟨v i, hss (mem_range_self i)⟩).map_domain f,
have h_total_l : finsupp.total ι M R v l = v i,
{ dsimp only [l],
rw finsupp.total_map_domain,
rw (hv.comp f f.injective).total_repr,
{ refl } },
have h_total_eq : (finsupp.total ι M R v) l = (finsupp.total ι M R v) (finsupp.single i 1),
by rw [h_total_l, finsupp.total_single, one_smul],
have l_eq : l = _ := linear_map.ker_eq_bot.1 hv h_total_eq,
dsimp only [l] at l_eq,
rw ←finsupp.emb_domain_eq_map_domain at l_eq,
rcases finsupp.single_of_emb_domain_single (repr ⟨v i, _⟩) f i (1 : R) zero_ne_one.symm l_eq
with ⟨i', hi'⟩,
use i',
exact hi'.2
end
lemma eq_of_linear_independent_of_span_subtype [nontrivial R] {s t : set M}
(hs : linear_independent R (λ x, x : s → M)) (h : t ⊆ s) (hst : s ⊆ span R t) : s = t :=
begin
let f : t ↪ s := ⟨λ x, ⟨x.1, h x.2⟩, λ a b hab, subtype.coe_injective (subtype.mk.inj hab)⟩,
have h_surj : surjective f,
{ apply surjective_of_linear_independent_of_span hs f _,
convert hst; simp [f, comp], },
show s = t,
{ apply subset.antisymm _ h,
intros x hx,
rcases h_surj ⟨x, hx⟩ with ⟨y, hy⟩,
convert y.mem,
rw ← subtype.mk.inj hy,
refl }
end
open linear_map
lemma linear_independent.image_subtype {s : set M} {f : M →ₗ[R] M'}
(hs : linear_independent R (λ x, x : s → M))
(hf_inj : disjoint (span R s) f.ker) : linear_independent R (λ x, x : f '' s → M') :=
begin
rw [← @subtype.range_coe _ s] at hf_inj,
refine (hs.map hf_inj).to_subtype_range' _,
simp [set.range_comp f]
end
lemma linear_independent.inl_union_inr {s : set M} {t : set M'}
(hs : linear_independent R (λ x, x : s → M))
(ht : linear_independent R (λ x, x : t → M')) :
linear_independent R (λ x, x : inl R M M' '' s ∪ inr R M M' '' t → M × M') :=
begin
refine (hs.image_subtype _).union (ht.image_subtype _) _; [simp, simp, skip],
simp only [span_image],
simp [disjoint_iff, prod_inf_prod]
end
lemma linear_independent_inl_union_inr' {v : ι → M} {v' : ι' → M'}
(hv : linear_independent R v) (hv' : linear_independent R v') :
linear_independent R (sum.elim (inl R M M' ∘ v) (inr R M M' ∘ v')) :=
(hv.map' (inl R M M') ker_inl).sum_type (hv'.map' (inr R M M') ker_inr) $
begin
refine is_compl_range_inl_inr.disjoint.mono _ _;
simp only [span_le, range_coe, range_comp_subset_range],
end
/-- Dedekind's linear independence of characters -/
-- See, for example, Keith Conrad's note
-- <https://kconrad.math.uconn.edu/blurbs/galoistheory/linearchar.pdf>
theorem linear_independent_monoid_hom (G : Type*) [monoid G] (L : Type*) [comm_ring L]
[no_zero_divisors L] :
@linear_independent _ L (G → L) (λ f, f : (G →* L) → (G → L)) _ _ _ :=
by letI := classical.dec_eq (G →* L);
letI : mul_action L L := distrib_mul_action.to_mul_action;
-- We prove linear independence by showing that only the trivial linear combination vanishes.
exact linear_independent_iff'.2
-- To do this, we use `finset` induction,
(λ s, finset.induction_on s (λ g hg i, false.elim) $ λ a s has ih g hg,
-- Here
-- * `a` is a new character we will insert into the `finset` of characters `s`,
-- * `ih` is the fact that only the trivial linear combination of characters in `s` is zero
-- * `hg` is the fact that `g` are the coefficients of a linear combination summing to zero
-- and it remains to prove that `g` vanishes on `insert a s`.
-- We now make the key calculation:
-- For any character `i` in the original `finset`, we have `g i • i = g i • a` as functions on the
-- monoid `G`.
have h1 : ∀ i ∈ s, (g i • i : G → L) = g i • a, from λ i his, funext $ λ x : G,
-- We prove these expressions are equal by showing
-- the differences of their values on each monoid element `x` is zero
eq_of_sub_eq_zero $ ih (λ j, g j * j x - g j * a x)
(funext $ λ y : G, calc
-- After that, it's just a chase scene.
(∑ i in s, ((g i * i x - g i * a x) • i : G → L)) y
= ∑ i in s, (g i * i x - g i * a x) * i y : finset.sum_apply _ _ _
... = ∑ i in s, (g i * i x * i y - g i * a x * i y) : finset.sum_congr rfl
(λ _ _, sub_mul _ _ _)
... = ∑ i in s, g i * i x * i y - ∑ i in s, g i * a x * i y : finset.sum_sub_distrib
... = (g a * a x * a y + ∑ i in s, g i * i x * i y)
- (g a * a x * a y + ∑ i in s, g i * a x * i y) : by rw add_sub_add_left_eq_sub
... = ∑ i in insert a s, g i * i x * i y - ∑ i in insert a s, g i * a x * i y :
by rw [finset.sum_insert has, finset.sum_insert has]
... = ∑ i in insert a s, g i * i (x * y) - ∑ i in insert a s, a x * (g i * i y) :
congr (congr_arg has_sub.sub (finset.sum_congr rfl $ λ i _, by rw [i.map_mul, mul_assoc]))
(finset.sum_congr rfl $ λ _ _, by rw [mul_assoc, mul_left_comm])
... = (∑ i in insert a s, (g i • i : G → L)) (x * y)
- a x * (∑ i in insert a s, (g i • i : G → L)) y :
by rw [finset.sum_apply, finset.sum_apply, finset.mul_sum]; refl
... = 0 - a x * 0 : by rw hg; refl
... = 0 : by rw [mul_zero, sub_zero])
i
his,
-- On the other hand, since `a` is not already in `s`, for any character `i ∈ s`
-- there is some element of the monoid on which it differs from `a`.
have h2 : ∀ i : G →* L, i ∈ s → ∃ y, i y ≠ a y, from λ i his,
classical.by_contradiction $ λ h,
have hia : i = a, from monoid_hom.ext $ λ y, classical.by_contradiction $ λ hy, h ⟨y, hy⟩,
has $ hia ▸ his,
-- From these two facts we deduce that `g` actually vanishes on `s`,
have h3 : ∀ i ∈ s, g i = 0, from λ i his, let ⟨y, hy⟩ := h2 i his in