/- Copyright (c) 2019 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen -/ import data.matrix.block import data.matrix.notation import linear_algebra.matrix.finite_dimensional import linear_algebra.std_basis import ring_theory.algebra_tower import algebra.module.algebra /-! # Linear maps and matrices This file defines the maps to send matrices to a linear map, and to send linear maps between modules with a finite bases to matrices. This defines a linear equivalence between linear maps between finite-dimensional vector spaces and matrices indexed by the respective bases. ## Main definitions In the list below, and in all this file, `R` is a commutative ring (semiring is sometimes enough), `M` and its variations are `R`-modules, `ι`, `κ`, `n` and `m` are finite types used for indexing. * `linear_map.to_matrix`: given bases `v₁ : ι → M₁` and `v₂ : κ → M₂`, the `R`-linear equivalence from `M₁ →ₗ[R] M₂` to `matrix κ ι R` * `matrix.to_lin`: the inverse of `linear_map.to_matrix` * `linear_map.to_matrix'`: the `R`-linear equivalence from `(m → R) →ₗ[R] (n → R)` to `matrix m n R` (with the standard basis on `m → R` and `n → R`) * `matrix.to_lin'`: the inverse of `linear_map.to_matrix'` * `alg_equiv_matrix`: given a basis indexed by `n`, the `R`-algebra equivalence between `R`-endomorphisms of `M` and `matrix n n R` ## Issues This file was originally written without attention to non-commutative rings, and so mostly only works in the commutative setting. This should be fixed. In particular, `matrix.mul_vec` gives us a linear equivalence `matrix m n R ≃ₗ[R] (n → R) →ₗ[Rᵐᵒᵖ] (m → R)` while `matrix.vec_mul` gives us a linear equivalence `matrix m n R ≃ₗ[Rᵐᵒᵖ] (m → R) →ₗ[R] (n → R)`. At present, the first equivalence is developed in detail but only for commutative rings (and we omit the distinction between `Rᵐᵒᵖ` and `R`), while the second equivalence is developed only in brief, but for not-necessarily-commutative rings. Naming is slightly inconsistent between the two developments. In the original (commutative) development `linear` is abbreviated to `lin`, although this is not consistent with the rest of mathlib. In the new (non-commutative) development `linear` is not abbreviated, and declarations use `_right` to indicate they use the right action of matrices on vectors (via `matrix.vec_mul`). When the two developments are made uniform, the names should be made uniform, too, by choosing between `linear` and `lin` consistently, and (presumably) adding `_left` where necessary. ## Tags linear_map, matrix, linear_equiv, diagonal, det, trace -/ noncomputable theory open linear_map matrix set submodule open_locale big_operators open_locale matrix universes u v w instance {n m} [fintype m] [decidable_eq m] [fintype n] [decidable_eq n] (R) [fintype R] : fintype (matrix m n R) := by unfold matrix; apply_instance section to_matrix_right variables {R : Type*} [semiring R] variables {l m n : Type*} /-- `matrix.vec_mul M` is a linear map. -/ @[simps] def matrix.vec_mul_linear [fintype m] (M : matrix m n R) : (m → R) →ₗ[R] (n → R) := { to_fun := λ x, M.vec_mul x, map_add' := λ v w, funext (λ i, add_dot_product _ _ _), map_smul' := λ c v, funext (λ i, smul_dot_product _ _ _) } variables [fintype m] [decidable_eq m] @[simp] lemma matrix.vec_mul_std_basis (M : matrix m n R) (i j) : M.vec_mul (std_basis R (λ _, R) i 1) j = M i j := begin have : (∑ i', (if i = i' then 1 else 0) * M i' j) = M i j, { simp_rw [boole_mul, finset.sum_ite_eq, finset.mem_univ, if_true] }, convert this, ext, split_ifs with h; simp only [std_basis_apply], { rw [h, function.update_same] }, { rw [function.update_noteq (ne.symm h), pi.zero_apply] } end /-- Linear maps `(m → R) →ₗ[R] (n → R)` are linearly equivalent over `Rᵐᵒᵖ` to `matrix m n R`, by having matrices act by right multiplication. -/ def linear_map.to_matrix_right' : ((m → R) →ₗ[R] (n → R)) ≃ₗ[Rᵐᵒᵖ] matrix m n R := { to_fun := λ f i j, f (std_basis R (λ _, R) i 1) j, inv_fun := matrix.vec_mul_linear, right_inv := λ M, by { ext i j, simp only [matrix.vec_mul_std_basis, matrix.vec_mul_linear_apply] }, left_inv := λ f, begin apply (pi.basis_fun R m).ext, intro j, ext i, simp only [pi.basis_fun_apply, matrix.vec_mul_std_basis, matrix.vec_mul_linear_apply] end, map_add' := λ f g, by { ext i j, simp only [pi.add_apply, linear_map.add_apply] }, map_smul' := λ c f, by { ext i j, simp only [pi.smul_apply, linear_map.smul_apply, ring_hom.id_apply] } } /-- A `matrix m n R` is linearly equivalent over `Rᵐᵒᵖ` to a linear map `(m → R) →ₗ[R] (n → R)`, by having matrices act by right multiplication. -/ abbreviation matrix.to_linear_map_right' : matrix m n R ≃ₗ[Rᵐᵒᵖ] ((m → R) →ₗ[R] (n → R)) := linear_map.to_matrix_right'.symm @[simp] lemma matrix.to_linear_map_right'_apply (M : matrix m n R) (v : m → R) : matrix.to_linear_map_right' M v = M.vec_mul v := rfl @[simp] lemma matrix.to_linear_map_right'_mul [fintype l] [decidable_eq l] (M : matrix l m R) (N : matrix m n R) : matrix.to_linear_map_right' (M ⬝ N) = (matrix.to_linear_map_right' N).comp (matrix.to_linear_map_right' M) := linear_map.ext $ λ x, (vec_mul_vec_mul _ M N).symm lemma matrix.to_linear_map_right'_mul_apply [fintype l] [decidable_eq l] (M : matrix l m R) (N : matrix m n R) (x) : matrix.to_linear_map_right' (M ⬝ N) x = (matrix.to_linear_map_right' N (matrix.to_linear_map_right' M x)) := (vec_mul_vec_mul _ M N).symm @[simp] lemma matrix.to_linear_map_right'_one : matrix.to_linear_map_right' (1 : matrix m m R) = id := by { ext, simp [linear_map.one_apply, std_basis_apply] } /-- If `M` and `M'` are each other's inverse matrices, they provide an equivalence between `n → A` and `m → A` corresponding to `M.vec_mul` and `M'.vec_mul`. -/ @[simps] def matrix.to_linear_equiv_right'_of_inv [fintype n] [decidable_eq n] {M : matrix m n R} {M' : matrix n m R} (hMM' : M ⬝ M' = 1) (hM'M : M' ⬝ M = 1) : (n → R) ≃ₗ[R] (m → R) := { to_fun := M'.to_linear_map_right', inv_fun := M.to_linear_map_right', left_inv := λ x, by rw [← matrix.to_linear_map_right'_mul_apply, hM'M, matrix.to_linear_map_right'_one, id_apply], right_inv := λ x, by rw [← matrix.to_linear_map_right'_mul_apply, hMM', matrix.to_linear_map_right'_one, id_apply], ..linear_map.to_matrix_right'.symm M' } end to_matrix_right /-! From this point on, we only work with commutative rings, and fail to distinguish between `Rᵐᵒᵖ` and `R`. This should eventually be remedied. -/ section to_matrix' variables {R : Type*} [comm_semiring R] variables {l m n : Type*} /-- `matrix.mul_vec M` is a linear map. -/ @[simps] def matrix.mul_vec_lin [fintype n] (M : matrix m n R) : (n → R) →ₗ[R] (m → R) := { to_fun := M.mul_vec, map_add' := λ v w, funext (λ i, dot_product_add _ _ _), map_smul' := λ c v, funext (λ i, dot_product_smul _ _ _) } variables [fintype n] [decidable_eq n] lemma matrix.mul_vec_std_basis (M : matrix m n R) (i j) : M.mul_vec (std_basis R (λ _, R) j 1) i = M i j := (congr_fun (matrix.mul_vec_single _ _ (1 : R)) i).trans $ mul_one _ @[simp] lemma matrix.mul_vec_std_basis_apply (M : matrix m n R) (j) : M.mul_vec (std_basis R (λ _, R) j 1) = Mᵀ j := funext $ λ i, matrix.mul_vec_std_basis M i j /-- Linear maps `(n → R) →ₗ[R] (m → R)` are linearly equivalent to `matrix m n R`. -/ def linear_map.to_matrix' : ((n → R) →ₗ[R] (m → R)) ≃ₗ[R] matrix m n R := { to_fun := λ f, of (λ i j, f (std_basis R (λ _, R) j 1) i), inv_fun := matrix.mul_vec_lin, right_inv := λ M, by { ext i j, simp only [matrix.mul_vec_std_basis, matrix.mul_vec_lin_apply, of_apply] }, left_inv := λ f, begin apply (pi.basis_fun R n).ext, intro j, ext i, simp only [pi.basis_fun_apply, matrix.mul_vec_std_basis, matrix.mul_vec_lin_apply, of_apply] end, map_add' := λ f g, by { ext i j, simp only [pi.add_apply, linear_map.add_apply, of_apply] }, map_smul' := λ c f, by { ext i j, simp only [pi.smul_apply, linear_map.smul_apply, ring_hom.id_apply, of_apply] } } /-- A `matrix m n R` is linearly equivalent to a linear map `(n → R) →ₗ[R] (m → R)`. -/ def matrix.to_lin' : matrix m n R ≃ₗ[R] ((n → R) →ₗ[R] (m → R)) := linear_map.to_matrix'.symm @[simp] lemma linear_map.to_matrix'_symm : (linear_map.to_matrix'.symm : matrix m n R ≃ₗ[R] _) = matrix.to_lin' := rfl @[simp] lemma matrix.to_lin'_symm : (matrix.to_lin'.symm : ((n → R) →ₗ[R] (m → R)) ≃ₗ[R] _) = linear_map.to_matrix' := rfl @[simp] lemma linear_map.to_matrix'_to_lin' (M : matrix m n R) : linear_map.to_matrix' (matrix.to_lin' M) = M := linear_map.to_matrix'.apply_symm_apply M @[simp] lemma matrix.to_lin'_to_matrix' (f : (n → R) →ₗ[R] (m → R)) : matrix.to_lin' (linear_map.to_matrix' f) = f := matrix.to_lin'.apply_symm_apply f @[simp] lemma linear_map.to_matrix'_apply (f : (n → R) →ₗ[R] (m → R)) (i j) : linear_map.to_matrix' f i j = f (λ j', if j' = j then 1 else 0) i := begin simp only [linear_map.to_matrix', linear_equiv.coe_mk, of_apply], congr, ext j', split_ifs with h, { rw [h, std_basis_same] }, apply std_basis_ne _ _ _ _ h end @[simp] lemma matrix.to_lin'_apply (M : matrix m n R) (v : n → R) : matrix.to_lin' M v = M.mul_vec v := rfl @[simp] lemma matrix.to_lin'_one : matrix.to_lin' (1 : matrix n n R) = id := by { ext, simp [linear_map.one_apply, std_basis_apply] } @[simp] lemma linear_map.to_matrix'_id : (linear_map.to_matrix' (linear_map.id : (n → R) →ₗ[R] (n → R))) = 1 := by { ext, rw [matrix.one_apply, linear_map.to_matrix'_apply, id_apply] } @[simp] lemma matrix.to_lin'_mul [fintype m] [decidable_eq m] (M : matrix l m R) (N : matrix m n R) : matrix.to_lin' (M ⬝ N) = (matrix.to_lin' M).comp (matrix.to_lin' N) := linear_map.ext $ λ x, (mul_vec_mul_vec _ _ _).symm /-- Shortcut lemma for `matrix.to_lin'_mul` and `linear_map.comp_apply` -/ lemma matrix.to_lin'_mul_apply [fintype m] [decidable_eq m] (M : matrix l m R) (N : matrix m n R) (x) : matrix.to_lin' (M ⬝ N) x = (matrix.to_lin' M (matrix.to_lin' N x)) := by rw [matrix.to_lin'_mul, linear_map.comp_apply] lemma linear_map.to_matrix'_comp [fintype l] [decidable_eq l] (f : (n → R) →ₗ[R] (m → R)) (g : (l → R) →ₗ[R] (n → R)) : (f.comp g).to_matrix' = f.to_matrix' ⬝ g.to_matrix' := suffices (f.comp g) = (f.to_matrix' ⬝ g.to_matrix').to_lin', by rw [this, linear_map.to_matrix'_to_lin'], by rw [matrix.to_lin'_mul, matrix.to_lin'_to_matrix', matrix.to_lin'_to_matrix'] lemma linear_map.to_matrix'_mul [fintype m] [decidable_eq m] (f g : (m → R) →ₗ[R] (m → R)) : (f * g).to_matrix' = f.to_matrix' ⬝ g.to_matrix' := linear_map.to_matrix'_comp f g @[simp] lemma linear_map.to_matrix'_algebra_map (x : R) : linear_map.to_matrix' (algebra_map R (module.End R (n → R)) x) = scalar n x := by simp [module.algebra_map_End_eq_smul_id] lemma matrix.ker_to_lin'_eq_bot_iff {M : matrix n n R} : M.to_lin'.ker = ⊥ ↔ ∀ v, M.mul_vec v = 0 → v = 0 := by simp only [submodule.eq_bot_iff, linear_map.mem_ker, matrix.to_lin'_apply] lemma matrix.range_to_lin' (M : matrix m n R) : M.to_lin'.range = span R (range Mᵀ) := by simp_rw [range_eq_map, ←supr_range_std_basis, map_supr, range_eq_map, ←ideal.span_singleton_one, ideal.span, submodule.map_span, image_image, image_singleton, matrix.to_lin'_apply, M.mul_vec_std_basis_apply, supr_span, range_eq_Union] /-- If `M` and `M'` are each other's inverse matrices, they provide an equivalence between `m → A` and `n → A` corresponding to `M.mul_vec` and `M'.mul_vec`. -/ @[simps] def matrix.to_lin'_of_inv [fintype m] [decidable_eq m] {M : matrix m n R} {M' : matrix n m R} (hMM' : M ⬝ M' = 1) (hM'M : M' ⬝ M = 1) : (m → R) ≃ₗ[R] (n → R) := { to_fun := matrix.to_lin' M', inv_fun := M.to_lin', left_inv := λ x, by rw [← matrix.to_lin'_mul_apply, hMM', matrix.to_lin'_one, id_apply], right_inv := λ x, by rw [← matrix.to_lin'_mul_apply, hM'M, matrix.to_lin'_one, id_apply], .. matrix.to_lin' M' } /-- Linear maps `(n → R) →ₗ[R] (n → R)` are algebra equivalent to `matrix n n R`. -/ def linear_map.to_matrix_alg_equiv' : ((n → R) →ₗ[R] (n → R)) ≃ₐ[R] matrix n n R := alg_equiv.of_linear_equiv linear_map.to_matrix' linear_map.to_matrix'_mul linear_map.to_matrix'_algebra_map /-- A `matrix n n R` is algebra equivalent to a linear map `(n → R) →ₗ[R] (n → R)`. -/ def matrix.to_lin_alg_equiv' : matrix n n R ≃ₐ[R] ((n → R) →ₗ[R] (n → R)) := linear_map.to_matrix_alg_equiv'.symm @[simp] lemma linear_map.to_matrix_alg_equiv'_symm : (linear_map.to_matrix_alg_equiv'.symm : matrix n n R ≃ₐ[R] _) = matrix.to_lin_alg_equiv' := rfl @[simp] lemma matrix.to_lin_alg_equiv'_symm : (matrix.to_lin_alg_equiv'.symm : ((n → R) →ₗ[R] (n → R)) ≃ₐ[R] _) = linear_map.to_matrix_alg_equiv' := rfl @[simp] lemma linear_map.to_matrix_alg_equiv'_to_lin_alg_equiv' (M : matrix n n R) : linear_map.to_matrix_alg_equiv' (matrix.to_lin_alg_equiv' M) = M := linear_map.to_matrix_alg_equiv'.apply_symm_apply M @[simp] lemma matrix.to_lin_alg_equiv'_to_matrix_alg_equiv' (f : (n → R) →ₗ[R] (n → R)) : matrix.to_lin_alg_equiv' (linear_map.to_matrix_alg_equiv' f) = f := matrix.to_lin_alg_equiv'.apply_symm_apply f @[simp] lemma linear_map.to_matrix_alg_equiv'_apply (f : (n → R) →ₗ[R] (n → R)) (i j) : linear_map.to_matrix_alg_equiv' f i j = f (λ j', if j' = j then 1 else 0) i := by simp [linear_map.to_matrix_alg_equiv'] @[simp] lemma matrix.to_lin_alg_equiv'_apply (M : matrix n n R) (v : n → R) : matrix.to_lin_alg_equiv' M v = M.mul_vec v := rfl @[simp] lemma matrix.to_lin_alg_equiv'_one : matrix.to_lin_alg_equiv' (1 : matrix n n R) = id := matrix.to_lin'_one @[simp] lemma linear_map.to_matrix_alg_equiv'_id : (linear_map.to_matrix_alg_equiv' (linear_map.id : (n → R) →ₗ[R] (n → R))) = 1 := linear_map.to_matrix'_id @[simp] lemma matrix.to_lin_alg_equiv'_mul (M N : matrix n n R) : matrix.to_lin_alg_equiv' (M ⬝ N) = (matrix.to_lin_alg_equiv' M).comp (matrix.to_lin_alg_equiv' N) := matrix.to_lin'_mul _ _ lemma linear_map.to_matrix_alg_equiv'_comp (f g : (n → R) →ₗ[R] (n → R)) : (f.comp g).to_matrix_alg_equiv' = f.to_matrix_alg_equiv' ⬝ g.to_matrix_alg_equiv' := linear_map.to_matrix'_comp _ _ lemma linear_map.to_matrix_alg_equiv'_mul (f g : (n → R) →ₗ[R] (n → R)) : (f * g).to_matrix_alg_equiv' = f.to_matrix_alg_equiv' ⬝ g.to_matrix_alg_equiv' := linear_map.to_matrix_alg_equiv'_comp f g lemma matrix.rank_vec_mul_vec {K m n : Type u} [field K] [fintype n] [decidable_eq n] (w : m → K) (v : n → K) : rank (vec_mul_vec w v).to_lin' ≤ 1 := begin rw [vec_mul_vec_eq, matrix.to_lin'_mul], refine le_trans (rank_comp_le1 _ _) _, refine (rank_le_domain _).trans_eq _, rw [dim_fun', fintype.card_unit, nat.cast_one] end end to_matrix' section to_matrix variables {R : Type*} [comm_semiring R] variables {l m n : Type*} [fintype n] [fintype m] [decidable_eq n] variables {M₁ M₂ : Type*} [add_comm_monoid M₁] [add_comm_monoid M₂] [module R M₁] [module R M₂] variables (v₁ : basis n R M₁) (v₂ : basis m R M₂) /-- Given bases of two modules `M₁` and `M₂` over a commutative ring `R`, we get a linear equivalence between linear maps `M₁ →ₗ M₂` and matrices over `R` indexed by the bases. -/ def linear_map.to_matrix : (M₁ →ₗ[R] M₂) ≃ₗ[R] matrix m n R := linear_equiv.trans (linear_equiv.arrow_congr v₁.equiv_fun v₂.equiv_fun) linear_map.to_matrix' /-- `linear_map.to_matrix'` is a particular case of `linear_map.to_matrix`, for the standard basis `pi.basis_fun R n`. -/ lemma linear_map.to_matrix_eq_to_matrix' : linear_map.to_matrix (pi.basis_fun R n) (pi.basis_fun R n) = linear_map.to_matrix' := rfl /-- Given bases of two modules `M₁` and `M₂` over a commutative ring `R`, we get a linear equivalence between matrices over `R` indexed by the bases and linear maps `M₁ →ₗ M₂`. -/ def matrix.to_lin : matrix m n R ≃ₗ[R] (M₁ →ₗ[R] M₂) := (linear_map.to_matrix v₁ v₂).symm /-- `matrix.to_lin'` is a particular case of `matrix.to_lin`, for the standard basis `pi.basis_fun R n`. -/ lemma matrix.to_lin_eq_to_lin' : matrix.to_lin (pi.basis_fun R n) (pi.basis_fun R m) = matrix.to_lin' := rfl @[simp] lemma linear_map.to_matrix_symm : (linear_map.to_matrix v₁ v₂).symm = matrix.to_lin v₁ v₂ := rfl @[simp] lemma matrix.to_lin_symm : (matrix.to_lin v₁ v₂).symm = linear_map.to_matrix v₁ v₂ := rfl @[simp] lemma matrix.to_lin_to_matrix (f : M₁ →ₗ[R] M₂) : matrix.to_lin v₁ v₂ (linear_map.to_matrix v₁ v₂ f) = f := by rw [← matrix.to_lin_symm, linear_equiv.apply_symm_apply] @[simp] lemma linear_map.to_matrix_to_lin (M : matrix m n R) : linear_map.to_matrix v₁ v₂ (matrix.to_lin v₁ v₂ M) = M := by rw [← matrix.to_lin_symm, linear_equiv.symm_apply_apply] lemma linear_map.to_matrix_apply (f : M₁ →ₗ[R] M₂) (i : m) (j : n) : linear_map.to_matrix v₁ v₂ f i j = v₂.repr (f (v₁ j)) i := begin rw [linear_map.to_matrix, linear_equiv.trans_apply, linear_map.to_matrix'_apply, linear_equiv.arrow_congr_apply, basis.equiv_fun_symm_apply, finset.sum_eq_single j, if_pos rfl, one_smul, basis.equiv_fun_apply], { intros j' _ hj', rw [if_neg hj', zero_smul] }, { intro hj, have := finset.mem_univ j, contradiction } end lemma linear_map.to_matrix_transpose_apply (f : M₁ →ₗ[R] M₂) (j : n) : (linear_map.to_matrix v₁ v₂ f)ᵀ j = v₂.repr (f (v₁ j)) := funext $ λ i, f.to_matrix_apply _ _ i j lemma linear_map.to_matrix_apply' (f : M₁ →ₗ[R] M₂) (i : m) (j : n) : linear_map.to_matrix v₁ v₂ f i j = v₂.repr (f (v₁ j)) i := linear_map.to_matrix_apply v₁ v₂ f i j lemma linear_map.to_matrix_transpose_apply' (f : M₁ →ₗ[R] M₂) (j : n) : (linear_map.to_matrix v₁ v₂ f)ᵀ j = v₂.repr (f (v₁ j)) := linear_map.to_matrix_transpose_apply v₁ v₂ f j lemma matrix.to_lin_apply (M : matrix m n R) (v : M₁) : matrix.to_lin v₁ v₂ M v = ∑ j, M.mul_vec (v₁.repr v) j • v₂ j := show v₂.equiv_fun.symm (matrix.to_lin' M (v₁.repr v)) = _, by rw [matrix.to_lin'_apply, v₂.equiv_fun_symm_apply] @[simp] lemma matrix.to_lin_self (M : matrix m n R) (i : n) : matrix.to_lin v₁ v₂ M (v₁ i) = ∑ j, M j i • v₂ j := begin rw [matrix.to_lin_apply, finset.sum_congr rfl (λ j hj, _)], rw [basis.repr_self, matrix.mul_vec, dot_product, finset.sum_eq_single i, finsupp.single_eq_same, mul_one], { intros i' _ i'_ne, rw [finsupp.single_eq_of_ne i'_ne.symm, mul_zero] }, { intros, have := finset.mem_univ i, contradiction }, end /-- This will be a special case of `linear_map.to_matrix_id_eq_basis_to_matrix`. -/ lemma linear_map.to_matrix_id : linear_map.to_matrix v₁ v₁ id = 1 := begin ext i j, simp [linear_map.to_matrix_apply, matrix.one_apply, finsupp.single, eq_comm] end lemma linear_map.to_matrix_one : linear_map.to_matrix v₁ v₁ 1 = 1 := linear_map.to_matrix_id v₁ @[simp] lemma matrix.to_lin_one : matrix.to_lin v₁ v₁ 1 = id := by rw [← linear_map.to_matrix_id v₁, matrix.to_lin_to_matrix] theorem linear_map.to_matrix_reindex_range [decidable_eq M₁] [decidable_eq M₂] (f : M₁ →ₗ[R] M₂) (k : m) (i : n) : linear_map.to_matrix v₁.reindex_range v₂.reindex_range f ⟨v₂ k, mem_range_self k⟩ ⟨v₁ i, mem_range_self i⟩ = linear_map.to_matrix v₁ v₂ f k i := by simp_rw [linear_map.to_matrix_apply, basis.reindex_range_self, basis.reindex_range_repr] variables {M₃ : Type*} [add_comm_monoid M₃] [module R M₃] (v₃ : basis l R M₃) lemma linear_map.to_matrix_comp [fintype l] [decidable_eq m] (f : M₂ →ₗ[R] M₃) (g : M₁ →ₗ[R] M₂) : linear_map.to_matrix v₁ v₃ (f.comp g) = linear_map.to_matrix v₂ v₃ f ⬝ linear_map.to_matrix v₁ v₂ g := by simp_rw [linear_map.to_matrix, linear_equiv.trans_apply, linear_equiv.arrow_congr_comp _ v₂.equiv_fun, linear_map.to_matrix'_comp] lemma linear_map.to_matrix_mul (f g : M₁ →ₗ[R] M₁) : linear_map.to_matrix v₁ v₁ (f * g) = linear_map.to_matrix v₁ v₁ f ⬝ linear_map.to_matrix v₁ v₁ g := by { rw [show (@has_mul.mul (M₁ →ₗ[R] M₁) _) = linear_map.comp, from rfl, linear_map.to_matrix_comp v₁ v₁ v₁ f g] } @[simp] lemma linear_map.to_matrix_algebra_map (x : R) : linear_map.to_matrix v₁ v₁ (algebra_map R (module.End R M₁) x) = scalar n x := by simp [module.algebra_map_End_eq_smul_id, linear_map.to_matrix_id] lemma linear_map.to_matrix_mul_vec_repr (f : M₁ →ₗ[R] M₂) (x : M₁) : (linear_map.to_matrix v₁ v₂ f).mul_vec (v₁.repr x) = v₂.repr (f x) := by { ext i, rw [← matrix.to_lin'_apply, linear_map.to_matrix, linear_equiv.trans_apply, matrix.to_lin'_to_matrix', linear_equiv.arrow_congr_apply, v₂.equiv_fun_apply], congr, exact v₁.equiv_fun.symm_apply_apply x } lemma matrix.to_lin_mul [fintype l] [decidable_eq m] (A : matrix l m R) (B : matrix m n R) : matrix.to_lin v₁ v₃ (A ⬝ B) = (matrix.to_lin v₂ v₃ A).comp (matrix.to_lin v₁ v₂ B) := begin apply (linear_map.to_matrix v₁ v₃).injective, haveI : decidable_eq l := λ _ _, classical.prop_decidable _, rw linear_map.to_matrix_comp v₁ v₂ v₃, repeat { rw linear_map.to_matrix_to_lin }, end /-- Shortcut lemma for `matrix.to_lin_mul` and `linear_map.comp_apply`. -/ lemma matrix.to_lin_mul_apply [fintype l] [decidable_eq m] (A : matrix l m R) (B : matrix m n R) (x) : matrix.to_lin v₁ v₃ (A ⬝ B) x = (matrix.to_lin v₂ v₃ A) (matrix.to_lin v₁ v₂ B x) := by rw [matrix.to_lin_mul v₁ v₂, linear_map.comp_apply] /-- If `M` and `M` are each other's inverse matrices, `matrix.to_lin M` and `matrix.to_lin M'` form a linear equivalence. -/ @[simps] def matrix.to_lin_of_inv [decidable_eq m] {M : matrix m n R} {M' : matrix n m R} (hMM' : M ⬝ M' = 1) (hM'M : M' ⬝ M = 1) : M₁ ≃ₗ[R] M₂ := { to_fun := matrix.to_lin v₁ v₂ M, inv_fun := matrix.to_lin v₂ v₁ M', left_inv := λ x, by rw [← matrix.to_lin_mul_apply, hM'M, matrix.to_lin_one, id_apply], right_inv := λ x, by rw [← matrix.to_lin_mul_apply, hMM', matrix.to_lin_one, id_apply], .. matrix.to_lin v₁ v₂ M } /-- Given a basis of a module `M₁` over a commutative ring `R`, we get an algebra equivalence between linear maps `M₁ →ₗ M₁` and square matrices over `R` indexed by the basis. -/ def linear_map.to_matrix_alg_equiv : (M₁ →ₗ[R] M₁) ≃ₐ[R] matrix n n R := alg_equiv.of_linear_equiv (linear_map.to_matrix v₁ v₁) (linear_map.to_matrix_mul v₁) (linear_map.to_matrix_algebra_map v₁) /-- Given a basis of a module `M₁` over a commutative ring `R`, we get an algebra equivalence between square matrices over `R` indexed by the basis and linear maps `M₁ →ₗ M₁`. -/ def matrix.to_lin_alg_equiv : matrix n n R ≃ₐ[R] (M₁ →ₗ[R] M₁) := (linear_map.to_matrix_alg_equiv v₁).symm @[simp] lemma linear_map.to_matrix_alg_equiv_symm : (linear_map.to_matrix_alg_equiv v₁).symm = matrix.to_lin_alg_equiv v₁ := rfl @[simp] lemma matrix.to_lin_alg_equiv_symm : (matrix.to_lin_alg_equiv v₁).symm = linear_map.to_matrix_alg_equiv v₁ := rfl @[simp] lemma matrix.to_lin_alg_equiv_to_matrix_alg_equiv (f : M₁ →ₗ[R] M₁) : matrix.to_lin_alg_equiv v₁ (linear_map.to_matrix_alg_equiv v₁ f) = f := by rw [← matrix.to_lin_alg_equiv_symm, alg_equiv.apply_symm_apply] @[simp] lemma linear_map.to_matrix_alg_equiv_to_lin_alg_equiv (M : matrix n n R) : linear_map.to_matrix_alg_equiv v₁ (matrix.to_lin_alg_equiv v₁ M) = M := by rw [← matrix.to_lin_alg_equiv_symm, alg_equiv.symm_apply_apply] lemma linear_map.to_matrix_alg_equiv_apply (f : M₁ →ₗ[R] M₁) (i j : n) : linear_map.to_matrix_alg_equiv v₁ f i j = v₁.repr (f (v₁ j)) i := by simp [linear_map.to_matrix_alg_equiv, linear_map.to_matrix_apply] lemma linear_map.to_matrix_alg_equiv_transpose_apply (f : M₁ →ₗ[R] M₁) (j : n) : (linear_map.to_matrix_alg_equiv v₁ f)ᵀ j = v₁.repr (f (v₁ j)) := funext $ λ i, f.to_matrix_apply _ _ i j lemma linear_map.to_matrix_alg_equiv_apply' (f : M₁ →ₗ[R] M₁) (i j : n) : linear_map.to_matrix_alg_equiv v₁ f i j = v₁.repr (f (v₁ j)) i := linear_map.to_matrix_alg_equiv_apply v₁ f i j lemma linear_map.to_matrix_alg_equiv_transpose_apply' (f : M₁ →ₗ[R] M₁) (j : n) : (linear_map.to_matrix_alg_equiv v₁ f)ᵀ j = v₁.repr (f (v₁ j)) := linear_map.to_matrix_alg_equiv_transpose_apply v₁ f j lemma matrix.to_lin_alg_equiv_apply (M : matrix n n R) (v : M₁) : matrix.to_lin_alg_equiv v₁ M v = ∑ j, M.mul_vec (v₁.repr v) j • v₁ j := show v₁.equiv_fun.symm (matrix.to_lin_alg_equiv' M (v₁.repr v)) = _, by rw [matrix.to_lin_alg_equiv'_apply, v₁.equiv_fun_symm_apply] @[simp] lemma matrix.to_lin_alg_equiv_self (M : matrix n n R) (i : n) : matrix.to_lin_alg_equiv v₁ M (v₁ i) = ∑ j, M j i • v₁ j := matrix.to_lin_self _ _ _ _ lemma linear_map.to_matrix_alg_equiv_id : linear_map.to_matrix_alg_equiv v₁ id = 1 := by simp_rw [linear_map.to_matrix_alg_equiv, alg_equiv.of_linear_equiv_apply, linear_map.to_matrix_id] @[simp] lemma matrix.to_lin_alg_equiv_one : matrix.to_lin_alg_equiv v₁ 1 = id := by rw [← linear_map.to_matrix_alg_equiv_id v₁, matrix.to_lin_alg_equiv_to_matrix_alg_equiv] theorem linear_map.to_matrix_alg_equiv_reindex_range [decidable_eq M₁] (f : M₁ →ₗ[R] M₁) (k i : n) : linear_map.to_matrix_alg_equiv v₁.reindex_range f ⟨v₁ k, mem_range_self k⟩ ⟨v₁ i, mem_range_self i⟩ = linear_map.to_matrix_alg_equiv v₁ f k i := by simp_rw [linear_map.to_matrix_alg_equiv_apply, basis.reindex_range_self, basis.reindex_range_repr] lemma linear_map.to_matrix_alg_equiv_comp (f g : M₁ →ₗ[R] M₁) : linear_map.to_matrix_alg_equiv v₁ (f.comp g) = linear_map.to_matrix_alg_equiv v₁ f ⬝ linear_map.to_matrix_alg_equiv v₁ g := by simp [linear_map.to_matrix_alg_equiv, linear_map.to_matrix_comp v₁ v₁ v₁ f g] lemma linear_map.to_matrix_alg_equiv_mul (f g : M₁ →ₗ[R] M₁) : linear_map.to_matrix_alg_equiv v₁ (f * g) = linear_map.to_matrix_alg_equiv v₁ f ⬝ linear_map.to_matrix_alg_equiv v₁ g := by { rw [show (@has_mul.mul (M₁ →ₗ[R] M₁) _) = linear_map.comp, from rfl, linear_map.to_matrix_alg_equiv_comp v₁ f g] } lemma matrix.to_lin_alg_equiv_mul (A B : matrix n n R) : matrix.to_lin_alg_equiv v₁ (A ⬝ B) = (matrix.to_lin_alg_equiv v₁ A).comp (matrix.to_lin_alg_equiv v₁ B) := by convert matrix.to_lin_mul v₁ v₁ v₁ A B @[simp] lemma matrix.to_lin_fin_two_prod_apply (a b c d : R) (x : R × R) : matrix.to_lin (basis.fin_two_prod R) (basis.fin_two_prod R) !![a, b; c, d] x = (a * x.fst + b * x.snd, c * x.fst + d * x.snd) := by simp [matrix.to_lin_apply, matrix.mul_vec, matrix.dot_product] lemma matrix.to_lin_fin_two_prod (a b c d : R) : matrix.to_lin (basis.fin_two_prod R) (basis.fin_two_prod R) !![a, b; c, d] = (a • linear_map.fst R R R + b • linear_map.snd R R R).prod (c • linear_map.fst R R R + d • linear_map.snd R R R) := linear_map.ext $ matrix.to_lin_fin_two_prod_apply _ _ _ _ end to_matrix namespace algebra section lmul variables {R S T : Type*} [comm_ring R] [comm_ring S] [comm_ring T] variables [algebra R S] [algebra S T] [algebra R T] [is_scalar_tower R S T] variables {m n : Type*} [fintype m] [decidable_eq m] [decidable_eq n] variables (b : basis m R S) (c : basis n S T) open algebra lemma to_matrix_lmul' (x : S) (i j) : linear_map.to_matrix b b (lmul R S x) i j = b.repr (x * b j) i := by simp only [linear_map.to_matrix_apply', coe_lmul_eq_mul, linear_map.mul_apply'] @[simp] lemma to_matrix_lsmul (x : R) (i j) : linear_map.to_matrix b b (algebra.lsmul R S x) i j = if i = j then x else 0 := by { rw [linear_map.to_matrix_apply', algebra.lsmul_coe, linear_equiv.map_smul, finsupp.smul_apply, b.repr_self_apply, smul_eq_mul, mul_boole], congr' 1; simp only [eq_comm] } /-- `left_mul_matrix b x` is the matrix corresponding to the linear map `λ y, x * y`. `left_mul_matrix_eq_repr_mul` gives a formula for the entries of `left_mul_matrix`. This definition is useful for doing (more) explicit computations with `linear_map.mul_left`, such as the trace form or norm map for algebras. -/ noncomputable def left_mul_matrix : S →ₐ[R] matrix m m R := { to_fun := λ x, linear_map.to_matrix b b (algebra.lmul R S x), map_zero' := by rw [alg_hom.map_zero, linear_equiv.map_zero], map_one' := by rw [alg_hom.map_one, linear_map.to_matrix_one], map_add' := λ x y, by rw [alg_hom.map_add, linear_equiv.map_add], map_mul' := λ x y, by rw [alg_hom.map_mul, linear_map.to_matrix_mul, matrix.mul_eq_mul], commutes' := λ r, by { ext, rw [lmul_algebra_map, to_matrix_lsmul, algebra_map_matrix_apply, id.map_eq_self] } } lemma left_mul_matrix_apply (x : S) : left_mul_matrix b x = linear_map.to_matrix b b (lmul R S x) := rfl lemma left_mul_matrix_eq_repr_mul (x : S) (i j) : left_mul_matrix b x i j = b.repr (x * b j) i := -- This is defeq to just `to_matrix_lmul' b x i j`, -- but the unfolding goes a lot faster with this explicit `rw`. by rw [left_mul_matrix_apply, to_matrix_lmul' b x i j] lemma left_mul_matrix_mul_vec_repr (x y : S) : (left_mul_matrix b x).mul_vec (b.repr y) = b.repr (x * y) := (linear_map.mul_left R x).to_matrix_mul_vec_repr b b y @[simp] lemma to_matrix_lmul_eq (x : S) : linear_map.to_matrix b b (linear_map.mul_left R x) = left_mul_matrix b x := rfl lemma left_mul_matrix_injective : function.injective (left_mul_matrix b) := λ x x' h, calc x = algebra.lmul R S x 1 : (mul_one x).symm ... = algebra.lmul R S x' 1 : by rw (linear_map.to_matrix b b).injective h ... = x' : mul_one x' variable [fintype n] lemma smul_left_mul_matrix (x) (ik jk) : left_mul_matrix (b.smul c) x ik jk = left_mul_matrix b (left_mul_matrix c x ik.2 jk.2) ik.1 jk.1 := by simp only [left_mul_matrix_apply, linear_map.to_matrix_apply, mul_comm, basis.smul_apply, basis.smul_repr, finsupp.smul_apply, id.smul_eq_mul, linear_equiv.map_smul, mul_smul_comm, coe_lmul_eq_mul, linear_map.mul_apply'] lemma smul_left_mul_matrix_algebra_map (x : S) : left_mul_matrix (b.smul c) (algebra_map _ _ x) = block_diagonal (λ k, left_mul_matrix b x) := begin ext ⟨i, k⟩ ⟨j, k'⟩, rw [smul_left_mul_matrix, alg_hom.commutes, block_diagonal_apply, algebra_map_matrix_apply], split_ifs with h; simp [h], end lemma smul_left_mul_matrix_algebra_map_eq (x : S) (i j k) : left_mul_matrix (b.smul c) (algebra_map _ _ x) (i, k) (j, k) = left_mul_matrix b x i j := by rw [smul_left_mul_matrix_algebra_map, block_diagonal_apply_eq] lemma smul_left_mul_matrix_algebra_map_ne (x : S) (i j) {k k'} (h : k ≠ k') : left_mul_matrix (b.smul c) (algebra_map _ _ x) (i, k) (j, k') = 0 := by rw [smul_left_mul_matrix_algebra_map, block_diagonal_apply_ne _ _ _ h] end lmul end algebra namespace linear_map section finite_dimensional open_locale classical variables {K : Type*} [field K] variables {V : Type*} [add_comm_group V] [module K V] [finite_dimensional K V] variables {W : Type*} [add_comm_group W] [module K W] [finite_dimensional K W] instance finite_dimensional : finite_dimensional K (V →ₗ[K] W) := linear_equiv.finite_dimensional (linear_map.to_matrix (basis.of_vector_space K V) (basis.of_vector_space K W)).symm section variables {A : Type*} [ring A] [algebra K A] [module A V] [is_scalar_tower K A V] [module A W] [is_scalar_tower K A W] /-- Linear maps over a `k`-algebra are finite dimensional (over `k`) if both the source and target are, since they form a subspace of all `k`-linear maps. -/ instance finite_dimensional' : finite_dimensional K (V →ₗ[A] W) := finite_dimensional.of_injective (restrict_scalars_linear_map K A V W) (restrict_scalars_injective _) end /-- The dimension of the space of linear transformations is the product of the dimensions of the domain and codomain. -/ @[simp] lemma finrank_linear_map : finite_dimensional.finrank K (V →ₗ[K] W) = (finite_dimensional.finrank K V) * (finite_dimensional.finrank K W) := begin let hbV := basis.of_vector_space K V, let hbW := basis.of_vector_space K W, rw [linear_equiv.finrank_eq (linear_map.to_matrix hbV hbW), matrix.finrank_matrix, finite_dimensional.finrank_eq_card_basis hbV, finite_dimensional.finrank_eq_card_basis hbW, mul_comm], end end finite_dimensional end linear_map section variables {R : Type v} [comm_ring R] {n : Type*} [decidable_eq n] variables {M M₁ M₂ : Type*} [add_comm_group M] [module R M] variables [add_comm_group M₁] [module R M₁] [add_comm_group M₂] [module R M₂] /-- The natural equivalence between linear endomorphisms of finite free modules and square matrices is compatible with the algebra structures. -/ def alg_equiv_matrix' [fintype n] : module.End R (n → R) ≃ₐ[R] matrix n n R := { map_mul' := linear_map.to_matrix'_comp, map_add' := linear_map.to_matrix'.map_add, commutes' := λ r, by { change (r • (linear_map.id : module.End R _)).to_matrix' = r • 1, rw ←linear_map.to_matrix'_id, refl, apply_instance }, ..linear_map.to_matrix' } /-- A linear equivalence of two modules induces an equivalence of algebras of their endomorphisms. -/ def linear_equiv.alg_conj (e : M₁ ≃ₗ[R] M₂) : module.End R M₁ ≃ₐ[R] module.End R M₂ := { map_mul' := λ f g, by apply e.arrow_congr_comp, map_add' := e.conj.map_add, commutes' := λ r, by { change e.conj (r • linear_map.id) = r • linear_map.id, rw [linear_equiv.map_smul, linear_equiv.conj_id], }, ..e.conj } /-- A basis of a module induces an equivalence of algebras from the endomorphisms of the module to square matrices. -/ def alg_equiv_matrix [fintype n] (h : basis n R M) : module.End R M ≃ₐ[R] matrix n n R := h.equiv_fun.alg_conj.trans alg_equiv_matrix' end