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orthogonal_projection_orthogonal_projection_of_le {U V : submodule 𝕜 E} [complete_space U] [complete_space V] (h : U ≤ V) (x : E) : orthogonal_projection U (orthogonal_projection V x) = orthogonal_projection U x
eq.symm $ by simpa only [sub_eq_zero, map_sub] using orthogonal_projection_mem_subspace_orthogonal_complement_eq_zero (submodule.orthogonal_le h (sub_orthogonal_projection_mem_orthogonal x))
lemma
orthogonal_projection_orthogonal_projection_of_le
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "orthogonal_projection", "orthogonal_projection_mem_subspace_orthogonal_complement_eq_zero", "sub_orthogonal_projection_mem_orthogonal", "submodule", "submodule.orthogonal_le" ]
If `U ≤ V`, then projecting on `V` and then on `U` is the same as projecting on `U`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_projection_tendsto_closure_supr [complete_space E] {ι : Type*} [semilattice_sup ι] (U : ι → submodule 𝕜 E) [∀ i, complete_space (U i)] (hU : monotone U) (x : E) : filter.tendsto (λ i, (orthogonal_projection (U i) x : E)) at_top (𝓝 (orthogonal_projection (⨆ i, U i).topological_closure x : E))
begin casesI is_empty_or_nonempty ι, { rw filter_eq_bot_of_is_empty (at_top : filter ι), exact tendsto_bot }, let y := (orthogonal_projection (⨆ i, U i).topological_closure x : E), have proj_x : ∀ i, orthogonal_projection (U i) x = orthogonal_projection (U i) y := λ i, (orthogonal_projection_orthogonal_...
lemma
orthogonal_projection_tendsto_closure_supr
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "cinfi_le", "complete_space", "filter", "filter.tendsto", "is_empty_or_nonempty", "le_supr", "metric.mem_closure_iff", "monotone", "normed_add_comm_group.tendsto_at_top", "orthogonal_projection", "orthogonal_projection_minimal", "orthogonal_projection_orthogonal_projection_of_le", "semilatti...
Given a monotone family `U` of complete submodules of `E` and a fixed `x : E`, the orthogonal projection of `x` on `U i` tends to the orthogonal projection of `x` on `(⨆ i, U i).topological_closure` along `at_top`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_projection_tendsto_self [complete_space E] {ι : Type*} [semilattice_sup ι] (U : ι → submodule 𝕜 E) [∀ t, complete_space (U t)] (hU : monotone U) (x : E) (hU' : ⊤ ≤ (⨆ t, U t).topological_closure) : filter.tendsto (λ t, (orthogonal_projection (U t) x : E)) at_top (𝓝 x)
begin rw ← eq_top_iff at hU', convert orthogonal_projection_tendsto_closure_supr U hU x, rw orthogonal_projection_eq_self_iff.mpr _, rw hU', trivial end
lemma
orthogonal_projection_tendsto_self
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "eq_top_iff", "filter.tendsto", "monotone", "orthogonal_projection", "orthogonal_projection_tendsto_closure_supr", "semilattice_sup", "submodule" ]
Given a monotone family `U` of complete submodules of `E` with dense span supremum, and a fixed `x : E`, the orthogonal projection of `x` on `U i` tends to `x` along `at_top`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
submodule.triorthogonal_eq_orthogonal [complete_space E] : Kᗮᗮᗮ = Kᗮ
begin rw Kᗮ.orthogonal_orthogonal_eq_closure, exact K.is_closed_orthogonal.submodule_topological_closure_eq, end
lemma
submodule.triorthogonal_eq_orthogonal
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space" ]
The orthogonal complement satisfies `Kᗮᗮᗮ = Kᗮ`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
submodule.topological_closure_eq_top_iff [complete_space E] : K.topological_closure = ⊤ ↔ Kᗮ = ⊥
begin rw ←submodule.orthogonal_orthogonal_eq_closure, split; intro h, { rw [←submodule.triorthogonal_eq_orthogonal, h, submodule.top_orthogonal_eq_bot] }, { rw [h, submodule.bot_orthogonal_eq_top] } end
lemma
submodule.topological_closure_eq_top_iff
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "submodule.bot_orthogonal_eq_top", "submodule.top_orthogonal_eq_bot" ]
The closure of `K` is the full space iff `Kᗮ` is trivial.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_of_sub_mem_orthogonal (hK : dense (K : set E)) (h : x - y ∈ Kᗮ) : x = y
begin rw [dense_iff_topological_closure_eq_top, topological_closure_eq_top_iff] at hK, rwa [hK, submodule.mem_bot, sub_eq_zero] at h, end
lemma
dense.eq_of_sub_mem_orthogonal
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "dense", "submodule.mem_bot" ]
If `S` is dense and `x - y ∈ Kᗮ`, then `x = y`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_zero_of_mem_orthogonal (hK : dense (K : set E)) (h : x ∈ Kᗮ) : x = 0
hK.eq_of_sub_mem_orthogonal (by rwa [sub_zero])
lemma
dense.eq_zero_of_mem_orthogonal
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "dense" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_of_inner_left (hK : dense (K : set E)) (h : ∀ v : K, ⟪x, v⟫ = ⟪y, v⟫) : x = y
hK.eq_of_sub_mem_orthogonal (submodule.sub_mem_orthogonal_of_inner_left h)
lemma
dense.eq_of_inner_left
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "dense", "submodule.sub_mem_orthogonal_of_inner_left" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_zero_of_inner_left (hK : dense (K : set E)) (h : ∀ v : K, ⟪x, v⟫ = 0) : x = 0
hK.eq_of_inner_left (λ v, by rw [inner_zero_left, h v])
lemma
dense.eq_zero_of_inner_left
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "dense", "inner_zero_left" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_of_inner_right (hK : dense (K : set E)) (h : ∀ v : K, ⟪(v : E), x⟫ = ⟪(v : E), y⟫) : x = y
hK.eq_of_sub_mem_orthogonal (submodule.sub_mem_orthogonal_of_inner_right h)
lemma
dense.eq_of_inner_right
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "dense", "submodule.sub_mem_orthogonal_of_inner_right" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_zero_of_inner_right (hK : dense (K : set E)) (h : ∀ v : K, ⟪(v : E), x⟫ = 0) : x = 0
hK.eq_of_inner_right (λ v, by rw [inner_zero_right, h v])
lemma
dense.eq_zero_of_inner_right
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "dense", "inner_zero_right" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
reflection_mem_subspace_orthogonal_precomplement_eq_neg [complete_space E] {v : E} (hv : v ∈ K) : reflection Kᗮ v = -v
reflection_mem_subspace_orthogonal_complement_eq_neg (K.le_orthogonal_orthogonal hv)
lemma
reflection_mem_subspace_orthogonal_precomplement_eq_neg
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "reflection", "reflection_mem_subspace_orthogonal_complement_eq_neg" ]
The reflection in `Kᗮ` of an element of `K` is its negation.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_projection_orthogonal_complement_singleton_eq_zero [complete_space E] (v : E) : orthogonal_projection (𝕜 ∙ v)ᗮ v = 0
orthogonal_projection_mem_subspace_orthogonal_precomplement_eq_zero (submodule.mem_span_singleton_self v)
lemma
orthogonal_projection_orthogonal_complement_singleton_eq_zero
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "orthogonal_projection", "orthogonal_projection_mem_subspace_orthogonal_precomplement_eq_zero", "submodule.mem_span_singleton_self" ]
The orthogonal projection onto `(𝕜 ∙ v)ᗮ` of `v` is zero.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
reflection_orthogonal_complement_singleton_eq_neg [complete_space E] (v : E) : reflection (𝕜 ∙ v)ᗮ v = -v
reflection_mem_subspace_orthogonal_precomplement_eq_neg (submodule.mem_span_singleton_self v)
lemma
reflection_orthogonal_complement_singleton_eq_neg
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "reflection", "reflection_mem_subspace_orthogonal_precomplement_eq_neg", "submodule.mem_span_singleton_self" ]
The reflection in `(𝕜 ∙ v)ᗮ` of `v` is `-v`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
reflection_sub [complete_space F] {v w : F} (h : ‖v‖ = ‖w‖) : reflection (ℝ ∙ (v - w))ᗮ v = w
begin set R : F ≃ₗᵢ[ℝ] F := reflection (ℝ ∙ (v - w))ᗮ, suffices : R v + R v = w + w, { apply smul_right_injective F (by norm_num : (2:ℝ) ≠ 0), simpa [two_smul] using this }, have h₁ : R (v - w) = -(v - w) := reflection_orthogonal_complement_singleton_eq_neg (v - w), have h₂ : R (v + w) = v + w, { apply ...
lemma
reflection_sub
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "congr_arg2", "real_inner_add_sub_eq_zero_iff", "reflection", "reflection_mem_subspace_eq_self", "reflection_orthogonal_complement_singleton_eq_neg", "smul_right_injective", "submodule.mem_orthogonal_singleton_iff_inner_left", "two_smul" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_sum_orthogonal_projection_self_orthogonal_complement [complete_space E] [complete_space K] (w : E) : w = (orthogonal_projection K w : E) + (orthogonal_projection Kᗮ w : E)
begin obtain ⟨y, hy, z, hz, hwyz⟩ := K.exists_sum_mem_mem_orthogonal w, convert hwyz, { exact eq_orthogonal_projection_of_mem_orthogonal' hy hz hwyz }, { rw add_comm at hwyz, refine eq_orthogonal_projection_of_mem_orthogonal' hz _ hwyz, simp [hy] } end
lemma
eq_sum_orthogonal_projection_self_orthogonal_complement
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "eq_orthogonal_projection_of_mem_orthogonal'", "orthogonal_projection" ]
In a complete space `E`, a vector splits as the sum of its orthogonal projections onto a complete submodule `K` and onto the orthogonal complement of `K`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
norm_sq_eq_add_norm_sq_projection (x : E) (S : submodule 𝕜 E) [complete_space E] [complete_space S] : ‖x‖^2 = ‖orthogonal_projection S x‖^2 + ‖orthogonal_projection Sᗮ x‖^2
begin let p1 := orthogonal_projection S, let p2 := orthogonal_projection Sᗮ, have x_decomp : x = p1 x + p2 x := eq_sum_orthogonal_projection_self_orthogonal_complement S x, have x_orth : ⟪ (p1 x : E), p2 x ⟫ = 0 := submodule.inner_right_of_mem_orthogonal (set_like.coe_mem (p1 x)) (set_like.coe_mem (p2 x...
lemma
norm_sq_eq_add_norm_sq_projection
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "eq_sum_orthogonal_projection_self_orthogonal_complement", "mul_eq_mul_left_iff", "norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero", "norm_eq_zero", "orthogonal_projection", "set_like.coe_mem", "submodule", "submodule.coe_eq_zero", "submodule.coe_norm", "submodule.inner_rig...
The Pythagorean theorem, for an orthogonal projection.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
id_eq_sum_orthogonal_projection_self_orthogonal_complement [complete_space E] [complete_space K] : continuous_linear_map.id 𝕜 E = K.subtypeL.comp (orthogonal_projection K) + Kᗮ.subtypeL.comp (orthogonal_projection Kᗮ)
by { ext w, exact eq_sum_orthogonal_projection_self_orthogonal_complement K w }
lemma
id_eq_sum_orthogonal_projection_self_orthogonal_complement
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "continuous_linear_map.id", "eq_sum_orthogonal_projection_self_orthogonal_complement", "orthogonal_projection" ]
In a complete space `E`, the projection maps onto a complete subspace `K` and its orthogonal complement sum to the identity.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
inner_orthogonal_projection_eq_of_mem_right [complete_space K] (u : K) (v : E) : ⟪orthogonal_projection K v, u⟫ = ⟪v, u⟫
calc ⟪orthogonal_projection K v, u⟫ = ⟪(orthogonal_projection K v : E), u⟫ : K.coe_inner _ _ ... = ⟪(orthogonal_projection K v : E), u⟫ + ⟪v - orthogonal_projection K v, u⟫ : by rw [orthogonal_projection_inner_eq_zero _ _ (submodule.coe_mem _), add_zero] ... = ⟪v, u⟫ : by rw [← inner_add_left, add_sub_c...
lemma
inner_orthogonal_projection_eq_of_mem_right
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "inner_add_left", "orthogonal_projection", "orthogonal_projection_inner_eq_zero", "submodule.coe_mem" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
inner_orthogonal_projection_eq_of_mem_left [complete_space K] (u : K) (v : E) : ⟪u, orthogonal_projection K v⟫ = ⟪(u : E), v⟫
by rw [← inner_conj_symm, ← inner_conj_symm (u : E), inner_orthogonal_projection_eq_of_mem_right]
lemma
inner_orthogonal_projection_eq_of_mem_left
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "inner_conj_symm", "inner_orthogonal_projection_eq_of_mem_right", "orthogonal_projection" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
inner_orthogonal_projection_left_eq_right [complete_space K] (u v : E) : ⟪↑(orthogonal_projection K u), v⟫ = ⟪u, orthogonal_projection K v⟫
by rw [← inner_orthogonal_projection_eq_of_mem_left, inner_orthogonal_projection_eq_of_mem_right]
lemma
inner_orthogonal_projection_left_eq_right
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "inner_orthogonal_projection_eq_of_mem_left", "inner_orthogonal_projection_eq_of_mem_right", "orthogonal_projection" ]
The orthogonal projection is self-adjoint.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_projection_is_symmetric [complete_space K] : (K.subtypeL ∘L orthogonal_projection K : E →ₗ[𝕜] E).is_symmetric
inner_orthogonal_projection_left_eq_right K
lemma
orthogonal_projection_is_symmetric
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "inner_orthogonal_projection_left_eq_right", "orthogonal_projection" ]
The orthogonal projection is symmetric.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
submodule.finrank_add_inf_finrank_orthogonal {K₁ K₂ : submodule 𝕜 E} [finite_dimensional 𝕜 K₂] (h : K₁ ≤ K₂) : finrank 𝕜 K₁ + finrank 𝕜 (K₁ᗮ ⊓ K₂ : submodule 𝕜 E) = finrank 𝕜 K₂
begin haveI := submodule.finite_dimensional_of_le h, haveI := proper_is_R_or_C 𝕜 K₁, have hd := submodule.finrank_sup_add_finrank_inf_eq K₁ (K₁ᗮ ⊓ K₂), rw [←inf_assoc, (submodule.orthogonal_disjoint K₁).eq_bot, bot_inf_eq, finrank_bot, submodule.sup_orthogonal_inf_of_complete_space h] at hd, rw add_zer...
lemma
submodule.finrank_add_inf_finrank_orthogonal
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "bot_inf_eq", "finite_dimensional", "finrank_bot", "submodule", "submodule.finite_dimensional_of_le", "submodule.finrank_sup_add_finrank_inf_eq", "submodule.orthogonal_disjoint", "submodule.sup_orthogonal_inf_of_complete_space" ]
Given a finite-dimensional subspace `K₂`, and a subspace `K₁` containined in it, the dimensions of `K₁` and the intersection of its orthogonal subspace with `K₂` add to that of `K₂`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
submodule.finrank_add_inf_finrank_orthogonal' {K₁ K₂ : submodule 𝕜 E} [finite_dimensional 𝕜 K₂] (h : K₁ ≤ K₂) {n : ℕ} (h_dim : finrank 𝕜 K₁ + n = finrank 𝕜 K₂) : finrank 𝕜 (K₁ᗮ ⊓ K₂ : submodule 𝕜 E) = n
by { rw ← add_right_inj (finrank 𝕜 K₁), simp [submodule.finrank_add_inf_finrank_orthogonal h, h_dim] }
lemma
submodule.finrank_add_inf_finrank_orthogonal'
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "finite_dimensional", "submodule", "submodule.finrank_add_inf_finrank_orthogonal" ]
Given a finite-dimensional subspace `K₂`, and a subspace `K₁` containined in it, the dimensions of `K₁` and the intersection of its orthogonal subspace with `K₂` add to that of `K₂`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
submodule.finrank_add_finrank_orthogonal [finite_dimensional 𝕜 E] (K : submodule 𝕜 E) : finrank 𝕜 K + finrank 𝕜 Kᗮ = finrank 𝕜 E
begin convert submodule.finrank_add_inf_finrank_orthogonal (le_top : K ≤ ⊤) using 1, { rw inf_top_eq }, { simp } end
lemma
submodule.finrank_add_finrank_orthogonal
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "finite_dimensional", "inf_top_eq", "le_top", "submodule", "submodule.finrank_add_inf_finrank_orthogonal" ]
Given a finite-dimensional space `E` and subspace `K`, the dimensions of `K` and `Kᗮ` add to that of `E`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
submodule.finrank_add_finrank_orthogonal' [finite_dimensional 𝕜 E] {K : submodule 𝕜 E} {n : ℕ} (h_dim : finrank 𝕜 K + n = finrank 𝕜 E) : finrank 𝕜 Kᗮ = n
by { rw ← add_right_inj (finrank 𝕜 K), simp [submodule.finrank_add_finrank_orthogonal, h_dim] }
lemma
submodule.finrank_add_finrank_orthogonal'
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "finite_dimensional", "submodule", "submodule.finrank_add_finrank_orthogonal" ]
Given a finite-dimensional space `E` and subspace `K`, the dimensions of `K` and `Kᗮ` add to that of `E`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
finrank_orthogonal_span_singleton {n : ℕ} [_i : fact (finrank 𝕜 E = n + 1)] {v : E} (hv : v ≠ 0) : finrank 𝕜 (𝕜 ∙ v)ᗮ = n
submodule.finrank_add_finrank_orthogonal' $ by simp [finrank_span_singleton hv, _i.elim, add_comm]
lemma
finrank_orthogonal_span_singleton
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "fact", "finrank_span_singleton", "submodule.finrank_add_finrank_orthogonal'" ]
In a finite-dimensional inner product space, the dimension of the orthogonal complement of the span of a nonzero vector is one less than the dimension of the space.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
linear_isometry_equiv.reflections_generate_dim_aux [finite_dimensional ℝ F] {n : ℕ} (φ : F ≃ₗᵢ[ℝ] F) (hn : finrank ℝ (ker (continuous_linear_map.id ℝ F - φ))ᗮ ≤ n) : ∃ l : list F, l.length ≤ n ∧ φ = (l.map (λ v, reflection (ℝ ∙ v)ᗮ)).prod
begin -- We prove this by strong induction on `n`, the dimension of the orthogonal complement of the -- fixed subspace of the endomorphism `φ` induction n with n IH generalizing φ, { -- Base case: `n = 0`, the fixed subspace is the whole space, so `φ = id` refine ⟨[], rfl.le, show φ = 1, from _⟩, have :...
lemma
linear_isometry_equiv.reflections_generate_dim_aux
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "continuous_linear_map.coe_sub", "continuous_linear_map.id", "continuous_linear_map.to_linear_map_eq_coe", "exists_ne", "finite_dimensional", "finrank_eq_zero", "le_zero_iff", "linear_isometry_equiv.inner_map_map", "linear_map.congr_fun", "linear_map.sub_apply", "linear_map.zero_apply", "list....
An element `φ` of the orthogonal group of `F` can be factored as a product of reflections, and specifically at most as many reflections as the dimension of the complement of the fixed subspace of `φ`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
linear_isometry_equiv.reflections_generate_dim [finite_dimensional ℝ F] (φ : F ≃ₗᵢ[ℝ] F) : ∃ l : list F, l.length ≤ finrank ℝ F ∧ φ = (l.map (λ v, reflection (ℝ ∙ v)ᗮ)).prod
let ⟨l, hl₁, hl₂⟩ := φ.reflections_generate_dim_aux le_rfl in ⟨l, hl₁.trans (submodule.finrank_le _), hl₂⟩
lemma
linear_isometry_equiv.reflections_generate_dim
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "finite_dimensional", "le_rfl", "reflection", "submodule.finrank_le" ]
The orthogonal group of `F` is generated by reflections; specifically each element `φ` of the orthogonal group is a product of at most as many reflections as the dimension of `F`. Special case of the **Cartan–Dieudonné theorem**.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
linear_isometry_equiv.reflections_generate [finite_dimensional ℝ F] : subgroup.closure (set.range (λ v : F, reflection (ℝ ∙ v)ᗮ)) = ⊤
begin rw subgroup.eq_top_iff', intros φ, rcases φ.reflections_generate_dim with ⟨l, _, rfl⟩, apply (subgroup.closure _).list_prod_mem, intros x hx, rcases list.mem_map.mp hx with ⟨a, _, hax⟩, exact subgroup.subset_closure ⟨a, hax⟩, end
lemma
linear_isometry_equiv.reflections_generate
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "finite_dimensional", "list_prod_mem", "reflection", "set.range", "subgroup.closure", "subgroup.eq_top_iff'", "subgroup.subset_closure" ]
The orthogonal group of `F` is generated by reflections.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family.is_internal_iff_of_is_complete [decidable_eq ι] {V : ι → submodule 𝕜 E} (hV : orthogonal_family 𝕜 (λ i, V i) (λ i, (V i).subtypeₗᵢ)) (hc : is_complete (↑(supr V) : set E)) : direct_sum.is_internal V ↔ (supr V)ᗮ = ⊥
begin haveI : complete_space ↥(supr V) := hc.complete_space_coe, simp only [direct_sum.is_internal_submodule_iff_independent_and_supr_eq_top, hV.independent, true_and, submodule.orthogonal_eq_bot_iff] end
lemma
orthogonal_family.is_internal_iff_of_is_complete
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "direct_sum.is_internal", "direct_sum.is_internal_submodule_iff_independent_and_supr_eq_top", "is_complete", "orthogonal_family", "submodule", "submodule.orthogonal_eq_bot_iff", "supr" ]
An orthogonal family of subspaces of `E` satisfies `direct_sum.is_internal` (that is, they provide an internal direct sum decomposition of `E`) if and only if their span has trivial orthogonal complement.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family.is_internal_iff [decidable_eq ι] [finite_dimensional 𝕜 E] {V : ι → submodule 𝕜 E} (hV : orthogonal_family 𝕜 (λ i, V i) (λ i, (V i).subtypeₗᵢ)) : direct_sum.is_internal V ↔ (supr V)ᗮ = ⊥
begin haveI h := finite_dimensional.proper_is_R_or_C 𝕜 ↥(supr V), exact hV.is_internal_iff_of_is_complete (complete_space_coe_iff_is_complete.mp infer_instance) end
lemma
orthogonal_family.is_internal_iff
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "direct_sum.is_internal", "finite_dimensional", "finite_dimensional.proper_is_R_or_C", "orthogonal_family", "submodule", "supr" ]
An orthogonal family of subspaces of `E` satisfies `direct_sum.is_internal` (that is, they provide an internal direct sum decomposition of `E`) if and only if their span has trivial orthogonal complement.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family.sum_projection_of_mem_supr [fintype ι] {V : ι → submodule 𝕜 E} [∀ i, complete_space ↥(V i)] (hV : orthogonal_family 𝕜 (λ i, V i) (λ i, (V i).subtypeₗᵢ)) (x : E) (hx : x ∈ supr V) : ∑ i, (orthogonal_projection (V i) x : E) = x
begin refine submodule.supr_induction _ hx (λ i x hx, _) _ (λ x y hx hy, _), { refine (finset.sum_eq_single_of_mem i (finset.mem_univ _) $ λ j _ hij, _).trans (orthogonal_projection_eq_self_iff.mpr hx), rw [orthogonal_projection_mem_subspace_orthogonal_complement_eq_zero, submodule.coe_zero], exact hV...
lemma
orthogonal_family.sum_projection_of_mem_supr
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "congr_arg2", "finset.mem_univ", "fintype", "orthogonal_family", "orthogonal_projection", "orthogonal_projection_mem_subspace_orthogonal_complement_eq_zero", "submodule", "submodule.coe_add", "submodule.coe_zero", "submodule.supr_induction", "supr" ]
If `x` lies within an orthogonal family `v`, it can be expressed as a sum of projections.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family.projection_direct_sum_coe_add_hom [decidable_eq ι] {V : ι → submodule 𝕜 E} (hV : orthogonal_family 𝕜 (λ i, V i) (λ i, (V i).subtypeₗᵢ)) (x : ⨁ i, V i) (i : ι) [complete_space ↥(V i)] : orthogonal_projection (V i) (direct_sum.coe_add_monoid_hom V x) = x i
begin induction x using direct_sum.induction_on with j x x y hx hy, { simp }, { simp_rw [direct_sum.coe_add_monoid_hom_of, direct_sum.of, dfinsupp.single_add_hom_apply], obtain rfl | hij := decidable.eq_or_ne i j, { rw [orthogonal_projection_mem_subspace_eq_self, dfinsupp.single_eq_same] }, { rw [orth...
lemma
orthogonal_family.projection_direct_sum_coe_add_hom
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "complete_space", "congr_arg2", "decidable.eq_or_ne", "dfinsupp.add_apply", "dfinsupp.single_eq_of_ne", "dfinsupp.single_eq_same", "direct_sum.coe_add_monoid_hom", "direct_sum.coe_add_monoid_hom_of", "direct_sum.induction_on", "direct_sum.of", "orthogonal_family", "orthogonal_projection", "o...
If a family of submodules is orthogonal, then the `orthogonal_projection` on a direct sum is just the coefficient of that direct sum.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family.decomposition [decidable_eq ι] [fintype ι] {V : ι → submodule 𝕜 E} [∀ i, complete_space ↥(V i)] (hV : orthogonal_family 𝕜 (λ i, V i) (λ i, (V i).subtypeₗᵢ)) (h : supr V = ⊤) : direct_sum.decomposition V
{ decompose' := λ x, dfinsupp.equiv_fun_on_fintype.symm $ λ i, orthogonal_projection (V i) x, left_inv := λ x, begin dsimp only, letI := λ i, classical.dec_eq (V i), rw [direct_sum.coe_add_monoid_hom, direct_sum.to_add_monoid, dfinsupp.lift_add_hom_apply, dfinsupp.sum_add_hom_apply, dfinsupp.sum_eq_...
def
orthogonal_family.decomposition
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "classical.dec_eq", "complete_space", "dfinsupp.equiv_fun_on_fintype_symm_coe", "dfinsupp.sum_add_hom_apply", "direct_sum.coe_add_monoid_hom", "direct_sum.decomposition", "direct_sum.to_add_monoid", "equiv.apply_symm_apply", "fintype", "orthogonal_family", "orthogonal_projection", "submodule",...
If a family of submodules is orthogonal and they span the whole space, then the orthogonal projection provides a means to decompose the space into its submodules. The projection function is `decompose V x i = orthogonal_projection (V i) x`. See note [reducible non-instances].
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
maximal_orthonormal_iff_orthogonal_complement_eq_bot (hv : orthonormal 𝕜 (coe : v → E)) : (∀ u ⊇ v, orthonormal 𝕜 (coe : u → E) → u = v) ↔ (span 𝕜 v)ᗮ = ⊥
begin rw submodule.eq_bot_iff, split, { contrapose!, -- ** direction 1: nonempty orthogonal complement implies nonmaximal rintros ⟨x, hx', hx⟩, -- take a nonzero vector and normalize it let e := (‖x‖⁻¹ : 𝕜) • x, have he : ‖e‖ = 1 := by simp [e, norm_smul_inv_norm hx], have he' : e ∈ (span...
lemma
maximal_orthonormal_iff_orthogonal_complement_eq_bot
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "finsupp.mem_span_image_iff_total", "finsupp.supported", "finsupp.total", "inner_eq_zero_symm", "norm_smul_inv_norm", "orthonormal", "submodule.eq_bot_iff", "submodule.subset_span" ]
An orthonormal set in an `inner_product_space` is maximal, if and only if the orthogonal complement of its span is empty.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
maximal_orthonormal_iff_basis_of_finite_dimensional (hv : orthonormal 𝕜 (coe : v → E)) : (∀ u ⊇ v, orthonormal 𝕜 (coe : u → E) → u = v) ↔ ∃ b : basis v 𝕜 E, ⇑b = coe
begin haveI := proper_is_R_or_C 𝕜 (span 𝕜 v), rw maximal_orthonormal_iff_orthogonal_complement_eq_bot hv, have hv_compl : is_complete (span 𝕜 v : set E) := (span 𝕜 v).complete_of_finite_dimensional, rw submodule.orthogonal_eq_bot_iff, have hv_coe : range (coe : v → E) = v := by simp, split, { refine λ...
lemma
maximal_orthonormal_iff_basis_of_finite_dimensional
analysis.inner_product_space
src/analysis/inner_product_space/projection.lean
[ "algebra.direct_sum.decomposition", "analysis.convex.basic", "analysis.inner_product_space.orthogonal", "analysis.inner_product_space.symmetric", "analysis.normed_space.is_R_or_C", "data.is_R_or_C.lemmas" ]
[ "basis", "basis.coe_mk", "is_complete", "maximal_orthonormal_iff_orthogonal_complement_eq_bot", "orthonormal", "submodule.orthogonal_eq_bot_iff" ]
An orthonormal set in a finite-dimensional `inner_product_space` is maximal, if and only if it is a basis.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
rayleigh_smul (x : E) {c : 𝕜} (hc : c ≠ 0) : rayleigh_quotient (c • x) = rayleigh_quotient x
begin by_cases hx : x = 0, { simp [hx] }, have : ‖c‖ ≠ 0 := by simp [hc], have : ‖x‖ ≠ 0 := by simp [hx], field_simp [norm_smul, T.re_apply_inner_self_smul], ring end
lemma
continuous_linear_map.rayleigh_smul
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "norm_smul", "ring" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
image_rayleigh_eq_image_rayleigh_sphere {r : ℝ} (hr : 0 < r) : rayleigh_quotient '' {0}ᶜ = rayleigh_quotient '' (sphere 0 r)
begin ext a, split, { rintros ⟨x, (hx : x ≠ 0), hxT⟩, have : ‖x‖ ≠ 0 := by simp [hx], let c : 𝕜 := ↑‖x‖⁻¹ * r, have : c ≠ 0 := by simp [c, hx, hr.ne'], refine ⟨c • x, _, _⟩, { field_simp [norm_smul, abs_of_pos hr] }, { rw T.rayleigh_smul x this, exact hxT } }, { rintros ⟨x, hx, hx...
lemma
continuous_linear_map.image_rayleigh_eq_image_rayleigh_sphere
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "abs_of_pos", "norm_smul" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
supr_rayleigh_eq_supr_rayleigh_sphere {r : ℝ} (hr : 0 < r) : (⨆ x : {x : E // x ≠ 0}, rayleigh_quotient x) = ⨆ x : sphere (0:E) r, rayleigh_quotient x
show (⨆ x : ({0} : set E)ᶜ, rayleigh_quotient x) = _, by simp only [←@Sup_image' _ _ _ _ rayleigh_quotient, T.image_rayleigh_eq_image_rayleigh_sphere hr]
lemma
continuous_linear_map.supr_rayleigh_eq_supr_rayleigh_sphere
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "Sup_image'" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
infi_rayleigh_eq_infi_rayleigh_sphere {r : ℝ} (hr : 0 < r) : (⨅ x : {x : E // x ≠ 0}, rayleigh_quotient x) = ⨅ x : sphere (0:E) r, rayleigh_quotient x
show (⨅ x : ({0} : set E)ᶜ, rayleigh_quotient x) = _, by simp only [←@Inf_image' _ _ _ _ rayleigh_quotient, T.image_rayleigh_eq_image_rayleigh_sphere hr]
lemma
continuous_linear_map.infi_rayleigh_eq_infi_rayleigh_sphere
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "Inf_image'" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
_root_.linear_map.is_symmetric.has_strict_fderiv_at_re_apply_inner_self {T : F →L[ℝ] F} (hT : (T : F →ₗ[ℝ] F).is_symmetric) (x₀ : F) : has_strict_fderiv_at T.re_apply_inner_self (_root_.bit0 (innerSL ℝ (T x₀))) x₀
begin convert T.has_strict_fderiv_at.inner _ (has_strict_fderiv_at_id x₀), ext y, simp_rw [_root_.bit0, continuous_linear_map.comp_apply, continuous_linear_map.add_apply, innerSL_apply, fderiv_inner_clm_apply, id.def, continuous_linear_map.prod_apply, continuous_linear_map.id_apply, hT.apply_clm x₀ y, rea...
lemma
linear_map.is_symmetric.has_strict_fderiv_at_re_apply_inner_self
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "continuous_linear_map.add_apply", "continuous_linear_map.comp_apply", "continuous_linear_map.id_apply", "continuous_linear_map.prod_apply", "fderiv_inner_clm_apply", "has_strict_fderiv_at", "has_strict_fderiv_at_id", "innerSL", "innerSL_apply", "real_inner_comm" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
linearly_dependent_of_is_local_extr_on (hT : is_self_adjoint T) {x₀ : F} (hextr : is_local_extr_on T.re_apply_inner_self (sphere (0:F) ‖x₀‖) x₀) : ∃ a b : ℝ, (a, b) ≠ 0 ∧ a • x₀ + b • T x₀ = 0
begin have H : is_local_extr_on T.re_apply_inner_self {x : F | ‖x‖ ^ 2 = ‖x₀‖ ^ 2} x₀, { convert hextr, ext x, simp [dist_eq_norm] }, -- find Lagrange multipliers for the function `T.re_apply_inner_self` and the -- hypersurface-defining function `λ x, ‖x‖ ^ 2` obtain ⟨a, b, h₁, h₂⟩ := is_local_extr_on...
lemma
is_self_adjoint.linearly_dependent_of_is_local_extr_on
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "add_smul", "has_strict_fderiv_at_norm_sq", "innerSL", "inner_product_space.to_dual_map", "is_local_extr_on", "is_local_extr_on.exists_multipliers_of_has_strict_fderiv_at_1d", "is_self_adjoint", "linear_isometry.map_add", "linear_isometry.map_smul", "linear_isometry.map_zero", "one_smul", "smu...
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_smul_self_of_is_local_extr_on_real (hT : is_self_adjoint T) {x₀ : F} (hextr : is_local_extr_on T.re_apply_inner_self (sphere (0:F) ‖x₀‖) x₀) : T x₀ = (rayleigh_quotient x₀) • x₀
begin obtain ⟨a, b, h₁, h₂⟩ := hT.linearly_dependent_of_is_local_extr_on hextr, by_cases hx₀ : x₀ = 0, { simp [hx₀] }, by_cases hb : b = 0, { have : a ≠ 0 := by simpa [hb] using h₁, refine absurd _ hx₀, apply smul_right_injective F this, simpa [hb] using h₂ }, let c : ℝ := - b⁻¹ * a, have hc :...
lemma
is_self_adjoint.eq_smul_self_of_is_local_extr_on_real
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "inner_smul_left", "is_local_extr_on", "is_self_adjoint", "mul_comm", "real_inner_self_eq_norm_mul_norm", "smul_right_injective" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eq_smul_self_of_is_local_extr_on (hT : is_self_adjoint T) {x₀ : E} (hextr : is_local_extr_on T.re_apply_inner_self (sphere (0:E) ‖x₀‖) x₀) : T x₀ = (↑(rayleigh_quotient x₀) : 𝕜) • x₀
begin letI := inner_product_space.is_R_or_C_to_real 𝕜 E, let hSA := hT.is_symmetric.restrict_scalars.to_self_adjoint.prop, exact hSA.eq_smul_self_of_is_local_extr_on_real hextr, end
lemma
is_self_adjoint.eq_smul_self_of_is_local_extr_on
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "inner_product_space.is_R_or_C_to_real", "is_local_extr_on", "is_self_adjoint" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvector_of_is_local_extr_on (hT : is_self_adjoint T) {x₀ : E} (hx₀ : x₀ ≠ 0) (hextr : is_local_extr_on T.re_apply_inner_self (sphere (0:E) ‖x₀‖) x₀) : has_eigenvector (T : E →ₗ[𝕜] E) ↑(rayleigh_quotient x₀) x₀
begin refine ⟨_, hx₀⟩, rw module.End.mem_eigenspace_iff, exact hT.eq_smul_self_of_is_local_extr_on hextr end
lemma
is_self_adjoint.has_eigenvector_of_is_local_extr_on
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "is_local_extr_on", "is_self_adjoint", "module.End.mem_eigenspace_iff" ]
For a self-adjoint operator `T`, a local extremum of the Rayleigh quotient of `T` on a sphere centred at the origin is an eigenvector of `T`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvector_of_is_max_on (hT : is_self_adjoint T) {x₀ : E} (hx₀ : x₀ ≠ 0) (hextr : is_max_on T.re_apply_inner_self (sphere (0:E) ‖x₀‖) x₀) : has_eigenvector (T : E →ₗ[𝕜] E) ↑(⨆ x : {x : E // x ≠ 0}, rayleigh_quotient x) x₀
begin convert hT.has_eigenvector_of_is_local_extr_on hx₀ (or.inr hextr.localize), have hx₀' : 0 < ‖x₀‖ := by simp [hx₀], have hx₀'' : x₀ ∈ sphere (0:E) (‖x₀‖) := by simp, rw T.supr_rayleigh_eq_supr_rayleigh_sphere hx₀', refine is_max_on.supr_eq hx₀'' _, intros x hx, dsimp, have : ‖x‖ = ‖x₀‖ := by simpa ...
lemma
is_self_adjoint.has_eigenvector_of_is_max_on
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "div_le_div_of_le", "is_max_on", "is_max_on.supr_eq", "is_self_adjoint", "sq_nonneg" ]
For a self-adjoint operator `T`, a maximum of the Rayleigh quotient of `T` on a sphere centred at the origin is an eigenvector of `T`, with eigenvalue the global supremum of the Rayleigh quotient.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvector_of_is_min_on (hT : is_self_adjoint T) {x₀ : E} (hx₀ : x₀ ≠ 0) (hextr : is_min_on T.re_apply_inner_self (sphere (0:E) ‖x₀‖) x₀) : has_eigenvector (T : E →ₗ[𝕜] E) ↑(⨅ x : {x : E // x ≠ 0}, rayleigh_quotient x) x₀
begin convert hT.has_eigenvector_of_is_local_extr_on hx₀ (or.inl hextr.localize), have hx₀' : 0 < ‖x₀‖ := by simp [hx₀], have hx₀'' : x₀ ∈ sphere (0:E) (‖x₀‖) := by simp, rw T.infi_rayleigh_eq_infi_rayleigh_sphere hx₀', refine is_min_on.infi_eq hx₀'' _, intros x hx, dsimp, have : ‖x‖ = ‖x₀‖ := by simpa ...
lemma
is_self_adjoint.has_eigenvector_of_is_min_on
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "div_le_div_of_le", "is_min_on", "is_min_on.infi_eq", "is_self_adjoint", "sq_nonneg" ]
For a self-adjoint operator `T`, a minimum of the Rayleigh quotient of `T` on a sphere centred at the origin is an eigenvector of `T`, with eigenvalue the global infimum of the Rayleigh quotient.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvalue_supr_of_finite_dimensional (hT : T.is_symmetric) : has_eigenvalue T ↑(⨆ x : {x : E // x ≠ 0}, is_R_or_C.re ⟪T x, x⟫ / ‖(x:E)‖ ^ 2)
begin haveI := finite_dimensional.proper_is_R_or_C 𝕜 E, let T' := hT.to_self_adjoint, obtain ⟨x, hx⟩ : ∃ x : E, x ≠ 0 := exists_ne 0, have H₁ : is_compact (sphere (0:E) ‖x‖) := is_compact_sphere _ _, have H₂ : (sphere (0:E) ‖x‖).nonempty := ⟨x, by simp⟩, -- key point: in finite dimension, a continuous func...
lemma
linear_map.is_symmetric.has_eigenvalue_supr_of_finite_dimensional
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "exists_ne", "finite_dimensional.proper_is_R_or_C", "is_compact", "is_compact_sphere", "is_max_on", "norm_eq_zero" ]
The supremum of the Rayleigh quotient of a symmetric operator `T` on a nontrivial finite-dimensional vector space is an eigenvalue for that operator.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvalue_infi_of_finite_dimensional (hT : T.is_symmetric) : has_eigenvalue T ↑(⨅ x : {x : E // x ≠ 0}, is_R_or_C.re ⟪T x, x⟫ / ‖(x:E)‖ ^ 2)
begin haveI := finite_dimensional.proper_is_R_or_C 𝕜 E, let T' := hT.to_self_adjoint, obtain ⟨x, hx⟩ : ∃ x : E, x ≠ 0 := exists_ne 0, have H₁ : is_compact (sphere (0:E) ‖x‖) := is_compact_sphere _ _, have H₂ : (sphere (0:E) ‖x‖).nonempty := ⟨x, by simp⟩, -- key point: in finite dimension, a continuous func...
lemma
linear_map.is_symmetric.has_eigenvalue_infi_of_finite_dimensional
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "exists_ne", "finite_dimensional.proper_is_R_or_C", "is_compact", "is_compact_sphere", "is_min_on", "norm_eq_zero" ]
The infimum of the Rayleigh quotient of a symmetric operator `T` on a nontrivial finite-dimensional vector space is an eigenvalue for that operator.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
subsingleton_of_no_eigenvalue_finite_dimensional (hT : T.is_symmetric) (hT' : ∀ μ : 𝕜, module.End.eigenspace (T : E →ₗ[𝕜] E) μ = ⊥) : subsingleton E
(subsingleton_or_nontrivial E).resolve_right (λ h, by exactI absurd (hT' _) hT.has_eigenvalue_supr_of_finite_dimensional)
lemma
linear_map.is_symmetric.subsingleton_of_no_eigenvalue_finite_dimensional
analysis.inner_product_space
src/analysis/inner_product_space/rayleigh.lean
[ "analysis.inner_product_space.calculus", "analysis.inner_product_space.dual", "analysis.inner_product_space.adjoint", "analysis.calculus.lagrange_multipliers", "linear_algebra.eigenspace.basic" ]
[ "module.End.eigenspace", "subsingleton_or_nontrivial" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
invariant_orthogonal_eigenspace (μ : 𝕜) (v : E) (hv : v ∈ (eigenspace T μ)ᗮ) : T v ∈ (eigenspace T μ)ᗮ
begin intros w hw, have : T w = (μ:𝕜) • w := by rwa mem_eigenspace_iff at hw, simp [← hT w, this, inner_smul_left, hv w hw] end
lemma
linear_map.is_symmetric.invariant_orthogonal_eigenspace
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "inner_smul_left" ]
A self-adjoint operator preserves orthogonal complements of its eigenspaces.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
conj_eigenvalue_eq_self {μ : 𝕜} (hμ : has_eigenvalue T μ) : conj μ = μ
begin obtain ⟨v, hv₁, hv₂⟩ := hμ.exists_has_eigenvector, rw mem_eigenspace_iff at hv₁, simpa [hv₂, inner_smul_left, inner_smul_right, hv₁] using hT v v end
lemma
linear_map.is_symmetric.conj_eigenvalue_eq_self
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "inner_smul_left", "inner_smul_right" ]
The eigenvalues of a self-adjoint operator are real.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family_eigenspaces : orthogonal_family 𝕜 (λ μ, eigenspace T μ) (λ μ, (eigenspace T μ).subtypeₗᵢ)
begin rintros μ ν hμν ⟨v, hv⟩ ⟨w, hw⟩, by_cases hv' : v = 0, { simp [hv'] }, have H := hT.conj_eigenvalue_eq_self (has_eigenvalue_of_has_eigenvector ⟨hv, hv'⟩), rw mem_eigenspace_iff at hv hw, refine or.resolve_left _ hμν.symm, simpa [inner_smul_left, inner_smul_right, hv, hw, H] using (hT v w).symm end
lemma
linear_map.is_symmetric.orthogonal_family_eigenspaces
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "inner_smul_left", "inner_smul_right", "orthogonal_family" ]
The eigenspaces of a self-adjoint operator are mutually orthogonal.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_family_eigenspaces' : orthogonal_family 𝕜 (λ μ : eigenvalues T, eigenspace T μ) (λ μ, (eigenspace T μ).subtypeₗᵢ)
hT.orthogonal_family_eigenspaces.comp subtype.coe_injective
lemma
linear_map.is_symmetric.orthogonal_family_eigenspaces'
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "orthogonal_family", "subtype.coe_injective" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_supr_eigenspaces_invariant ⦃v : E⦄ (hv : v ∈ (⨆ μ, eigenspace T μ)ᗮ) : T v ∈ (⨆ μ, eigenspace T μ)ᗮ
begin rw ← submodule.infi_orthogonal at ⊢ hv, exact T.infi_invariant hT.invariant_orthogonal_eigenspace v hv end
lemma
linear_map.is_symmetric.orthogonal_supr_eigenspaces_invariant
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "submodule.infi_orthogonal" ]
The mutual orthogonal complement of the eigenspaces of a self-adjoint operator on an inner product space is an invariant subspace of the operator.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_supr_eigenspaces (μ : 𝕜) : eigenspace (T.restrict hT.orthogonal_supr_eigenspaces_invariant) μ = ⊥
begin set p : submodule 𝕜 E := (⨆ μ, eigenspace T μ)ᗮ, refine eigenspace_restrict_eq_bot hT.orthogonal_supr_eigenspaces_invariant _, have H₂ : eigenspace T μ ⟂ p := (submodule.is_ortho_orthogonal_right _).mono_left (le_supr _ _), exact H₂.disjoint end
lemma
linear_map.is_symmetric.orthogonal_supr_eigenspaces
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "le_supr", "submodule", "submodule.is_ortho_orthogonal_right" ]
The mutual orthogonal complement of the eigenspaces of a self-adjoint operator on an inner product space has no eigenvalues.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_supr_eigenspaces_eq_bot : (⨆ μ, eigenspace T μ)ᗮ = ⊥
begin have hT' : is_symmetric _ := hT.restrict_invariant hT.orthogonal_supr_eigenspaces_invariant, -- a self-adjoint operator on a nontrivial inner product space has an eigenvalue haveI := hT'.subsingleton_of_no_eigenvalue_finite_dimensional hT.orthogonal_supr_eigenspaces, exact submodule.eq_bot_of_subsingleton...
lemma
linear_map.is_symmetric.orthogonal_supr_eigenspaces_eq_bot
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "submodule.eq_bot_of_subsingleton" ]
The mutual orthogonal complement of the eigenspaces of a self-adjoint operator on a finite-dimensional inner product space is trivial.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
orthogonal_supr_eigenspaces_eq_bot' : (⨆ μ : eigenvalues T, eigenspace T μ)ᗮ = ⊥
show (⨆ μ : {μ // (eigenspace T μ) ≠ ⊥}, eigenspace T μ)ᗮ = ⊥, by rw [supr_ne_bot_subtype, hT.orthogonal_supr_eigenspaces_eq_bot]
lemma
linear_map.is_symmetric.orthogonal_supr_eigenspaces_eq_bot'
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "supr_ne_bot_subtype" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
direct_sum_decomposition [hT : fact T.is_symmetric] : direct_sum.decomposition (λ μ : eigenvalues T, eigenspace T μ)
begin haveI h : ∀ μ : eigenvalues T, complete_space (eigenspace T μ) := λ μ, by apply_instance, exact hT.out.orthogonal_family_eigenspaces'.decomposition (submodule.orthogonal_eq_bot_iff.mp hT.out.orthogonal_supr_eigenspaces_eq_bot'), end
instance
linear_map.is_symmetric.direct_sum_decomposition
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "complete_space", "direct_sum.decomposition", "fact" ]
The eigenspaces of a self-adjoint operator on a finite-dimensional inner product space `E` gives an internal direct sum decomposition of `E`. Note this takes `hT` as a `fact` to allow it to be an instance.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
direct_sum_decompose_apply [hT : fact T.is_symmetric] (x : E) (μ : eigenvalues T) : direct_sum.decompose (λ μ : eigenvalues T, eigenspace T μ) x μ = orthogonal_projection (eigenspace T μ) x
rfl
lemma
linear_map.is_symmetric.direct_sum_decompose_apply
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "direct_sum.decompose", "fact", "orthogonal_projection" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
direct_sum_is_internal : direct_sum.is_internal (λ μ : eigenvalues T, eigenspace T μ)
hT.orthogonal_family_eigenspaces'.is_internal_iff.mpr hT.orthogonal_supr_eigenspaces_eq_bot'
lemma
linear_map.is_symmetric.direct_sum_is_internal
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "direct_sum.is_internal" ]
The eigenspaces of a self-adjoint operator on a finite-dimensional inner product space `E` gives an internal direct sum decomposition of `E`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
diagonalization : E ≃ₗᵢ[𝕜] pi_Lp 2 (λ μ : eigenvalues T, eigenspace T μ)
hT.direct_sum_is_internal.isometry_L2_of_orthogonal_family hT.orthogonal_family_eigenspaces'
def
linear_map.is_symmetric.diagonalization
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "pi_Lp" ]
Isometry from an inner product space `E` to the direct sum of the eigenspaces of some self-adjoint operator `T` on `E`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
diagonalization_symm_apply (w : pi_Lp 2 (λ μ : eigenvalues T, eigenspace T μ)) : hT.diagonalization.symm w = ∑ μ, w μ
hT.direct_sum_is_internal.isometry_L2_of_orthogonal_family_symm_apply hT.orthogonal_family_eigenspaces' w
lemma
linear_map.is_symmetric.diagonalization_symm_apply
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "pi_Lp" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
diagonalization_apply_self_apply (v : E) (μ : eigenvalues T) : hT.diagonalization (T v) μ = (μ : 𝕜) • hT.diagonalization v μ
begin suffices : ∀ w : pi_Lp 2 (λ μ : eigenvalues T, eigenspace T μ), (T (hT.diagonalization.symm w)) = hT.diagonalization.symm (λ μ, (μ : 𝕜) • w μ), { simpa only [linear_isometry_equiv.symm_apply_apply, linear_isometry_equiv.apply_symm_apply] using congr_arg (λ w, hT.diagonalization w μ) (this (hT.diago...
lemma
linear_map.is_symmetric.diagonalization_apply_self_apply
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "linear_isometry_equiv.apply_symm_apply", "linear_isometry_equiv.symm_apply_apply", "pi_Lp", "submodule.coe_smul_of_tower" ]
*Diagonalization theorem*, *spectral theorem*; version 1: A self-adjoint operator `T` on a finite-dimensional inner product space `E` acts diagonally on the decomposition of `E` into the direct sum of the eigenspaces of `T`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eigenvector_basis : orthonormal_basis (fin n) 𝕜 E
hT.direct_sum_is_internal.subordinate_orthonormal_basis hn hT.orthogonal_family_eigenspaces'
def
linear_map.is_symmetric.eigenvector_basis
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "orthonormal_basis" ]
A choice of orthonormal basis of eigenvectors for self-adjoint operator `T` on a finite-dimensional inner product space `E`. TODO Postcompose with a permutation so that these eigenvectors are listed in increasing order of eigenvalue.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eigenvalues (i : fin n) : ℝ
@is_R_or_C.re 𝕜 _ $ hT.direct_sum_is_internal.subordinate_orthonormal_basis_index hn i hT.orthogonal_family_eigenspaces'
def
linear_map.is_symmetric.eigenvalues
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[]
The sequence of real eigenvalues associated to the standard orthonormal basis of eigenvectors for a self-adjoint operator `T` on `E`. TODO Postcompose with a permutation so that these eigenvalues are listed in increasing order.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvector_eigenvector_basis (i : fin n) : has_eigenvector T (hT.eigenvalues hn i) (hT.eigenvector_basis hn i)
begin let v : E := hT.eigenvector_basis hn i, let μ : 𝕜 := hT.direct_sum_is_internal.subordinate_orthonormal_basis_index hn i hT.orthogonal_family_eigenspaces', simp_rw [eigenvalues], change has_eigenvector T (is_R_or_C.re μ) v, have key : has_eigenvector T μ v, { have H₁ : v ∈ eigenspace T μ, { si...
lemma
linear_map.is_symmetric.has_eigenvector_eigenvector_basis
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "is_R_or_C.conj_eq_iff_re" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
has_eigenvalue_eigenvalues (i : fin n) : has_eigenvalue T (hT.eigenvalues hn i)
module.End.has_eigenvalue_of_has_eigenvector (hT.has_eigenvector_eigenvector_basis hn i)
lemma
linear_map.is_symmetric.has_eigenvalue_eigenvalues
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "module.End.has_eigenvalue_of_has_eigenvector" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
apply_eigenvector_basis (i : fin n) : T (hT.eigenvector_basis hn i) = (hT.eigenvalues hn i : 𝕜) • hT.eigenvector_basis hn i
mem_eigenspace_iff.mp (hT.has_eigenvector_eigenvector_basis hn i).1
lemma
linear_map.is_symmetric.apply_eigenvector_basis
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
diagonalization_basis_apply_self_apply (v : E) (i : fin n) : (hT.eigenvector_basis hn).repr (T v) i = hT.eigenvalues hn i * (hT.eigenvector_basis hn).repr v i
begin suffices : ∀ w : euclidean_space 𝕜 (fin n), T ((hT.eigenvector_basis hn).repr.symm w) = (hT.eigenvector_basis hn).repr.symm (λ i, hT.eigenvalues hn i * w i), { simpa [orthonormal_basis.sum_repr_symm] using congr_arg (λ v, (hT.eigenvector_basis hn).repr v i) (this ((hT.eigenvector_basis ...
lemma
linear_map.is_symmetric.diagonalization_basis_apply_self_apply
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "euclidean_space", "linear_map.map_smul", "linear_map.map_sum", "mul_comm", "orthonormal_basis.sum_repr_symm", "smul_smul" ]
*Diagonalization theorem*, *spectral theorem*; version 2: A self-adjoint operator `T` on a finite-dimensional inner product space `E` acts diagonally on the identification of `E` with Euclidean space induced by an orthonormal basis of eigenvectors of `T`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
inner_product_apply_eigenvector {μ : 𝕜} {v : E} {T : E →ₗ[𝕜] E} (h : v ∈ module.End.eigenspace T μ) : ⟪v, T v⟫ = μ * ‖v‖ ^ 2
by simp only [mem_eigenspace_iff.mp h, inner_smul_right, inner_self_eq_norm_sq_to_K]
lemma
inner_product_apply_eigenvector
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "inner_self_eq_norm_sq_to_K", "inner_smul_right", "module.End.eigenspace" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eigenvalue_nonneg_of_nonneg {μ : ℝ} {T : E →ₗ[𝕜] E} (hμ : has_eigenvalue T μ) (hnn : ∀ (x : E), 0 ≤ is_R_or_C.re ⟪x, T x⟫) : 0 ≤ μ
begin obtain ⟨v, hv⟩ := hμ.exists_has_eigenvector, have hpos : 0 < ‖v‖ ^ 2, by simpa only [sq_pos_iff, norm_ne_zero_iff] using hv.2, have : is_R_or_C.re ⟪v, T v⟫ = μ * ‖v‖ ^ 2, { exact_mod_cast congr_arg is_R_or_C.re (inner_product_apply_eigenvector hv.1) }, exact (zero_le_mul_right hpos).mp (this ▸ hnn v), e...
lemma
eigenvalue_nonneg_of_nonneg
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "inner_product_apply_eigenvector", "sq_pos_iff", "zero_le_mul_right" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
eigenvalue_pos_of_pos {μ : ℝ} {T : E →ₗ[𝕜] E} (hμ : has_eigenvalue T μ) (hnn : ∀ (x : E), 0 < is_R_or_C.re ⟪x, T x⟫) : 0 < μ
begin obtain ⟨v, hv⟩ := hμ.exists_has_eigenvector, have hpos : 0 < ‖v‖ ^ 2, by simpa only [sq_pos_iff, norm_ne_zero_iff] using hv.2, have : is_R_or_C.re ⟪v, T v⟫ = μ * ‖v‖ ^ 2, { exact_mod_cast congr_arg is_R_or_C.re (inner_product_apply_eigenvector hv.1) }, exact (zero_lt_mul_right hpos).mp (this ▸ hnn v), e...
lemma
eigenvalue_pos_of_pos
analysis.inner_product_space
src/analysis/inner_product_space/spectrum.lean
[ "analysis.inner_product_space.rayleigh", "analysis.inner_product_space.pi_L2", "algebra.direct_sum.decomposition", "linear_algebra.eigenspace.minpoly" ]
[ "inner_product_apply_eigenvector", "sq_pos_iff", "zero_lt_mul_right" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric (T : E →ₗ[𝕜] E) : Prop
∀ x y, ⟪T x, y⟫ = ⟪x, T y⟫
def
linear_map.is_symmetric
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[]
A (not necessarily bounded) operator on an inner product space is symmetric, if for all `x`, `y`, we have `⟪T x, y⟫ = ⟪x, T y⟫`.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric_iff_sesq_form (T : E →ₗ[𝕜] E) : T.is_symmetric ↔ @linear_map.is_self_adjoint 𝕜 E _ _ _ (star_ring_end 𝕜) sesq_form_of_inner T
⟨λ h x y, (h y x).symm, λ h x y, (h y x).symm⟩
lemma
linear_map.is_symmetric_iff_sesq_form
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "linear_map.is_self_adjoint", "sesq_form_of_inner", "star_ring_end" ]
An operator `T` on an inner product space is symmetric if and only if it is `linear_map.is_self_adjoint` with respect to the sesquilinear form given by the inner product.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.conj_inner_sym {T : E →ₗ[𝕜] E} (hT : is_symmetric T) (x y : E) : conj ⟪T x, y⟫ = ⟪T y, x⟫
by rw [hT x y, inner_conj_symm]
lemma
linear_map.is_symmetric.conj_inner_sym
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "inner_conj_symm" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.apply_clm {T : E →L[𝕜] E} (hT : is_symmetric (T : E →ₗ[𝕜] E)) (x y : E) : ⟪T x, y⟫ = ⟪x, T y⟫
hT x y
lemma
linear_map.is_symmetric.apply_clm
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric_zero : (0 : E →ₗ[𝕜] E).is_symmetric
λ x y, (inner_zero_right x : ⟪x, 0⟫ = 0).symm ▸ (inner_zero_left y : ⟪0, y⟫ = 0)
lemma
linear_map.is_symmetric_zero
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "inner_zero_left", "inner_zero_right" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric_id : (linear_map.id : E →ₗ[𝕜] E).is_symmetric
λ x y, rfl
lemma
linear_map.is_symmetric_id
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "linear_map.id" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.add {T S : E →ₗ[𝕜] E} (hT : T.is_symmetric) (hS : S.is_symmetric) : (T + S).is_symmetric
begin intros x y, rw [linear_map.add_apply, inner_add_left, hT x y, hS x y, ← inner_add_right], refl end
lemma
linear_map.is_symmetric.add
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "inner_add_left", "inner_add_right", "linear_map.add_apply" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.continuous [complete_space E] {T : E →ₗ[𝕜] E} (hT : is_symmetric T) : continuous T
begin -- We prove it by using the closed graph theorem refine T.continuous_of_seq_closed_graph (λ u x y hu hTu, _), rw [←sub_eq_zero, ←@inner_self_eq_zero 𝕜], have hlhs : ∀ k : ℕ, ⟪T (u k) - T x, y - T x⟫ = ⟪u k - x, T (y - T x)⟫ := by { intro k, rw [←T.map_sub, hT] }, refine tendsto_nhds_unique ((hTu.sub_...
lemma
linear_map.is_symmetric.continuous
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "complete_space", "continuous", "filter.tendsto.inner", "inner_self_eq_zero", "tendsto_const_nhds", "tendsto_nhds_unique" ]
The **Hellinger--Toeplitz theorem**: if a symmetric operator is defined on a complete space, then it is automatically continuous.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.coe_re_apply_inner_self_apply {T : E →L[𝕜] E} (hT : is_symmetric (T : E →ₗ[𝕜] E)) (x : E) : (T.re_apply_inner_self x : 𝕜) = ⟪T x, x⟫
begin rsuffices ⟨r, hr⟩ : ∃ r : ℝ, ⟪T x, x⟫ = r, { simp [hr, T.re_apply_inner_self_apply] }, rw ← conj_eq_iff_real, exact hT.conj_inner_sym x x end
lemma
linear_map.is_symmetric.coe_re_apply_inner_self_apply
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[]
For a symmetric operator `T`, the function `λ x, ⟪T x, x⟫` is real-valued.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.restrict_invariant {T : E →ₗ[𝕜] E} (hT : is_symmetric T) {V : submodule 𝕜 E} (hV : ∀ v ∈ V, T v ∈ V) : is_symmetric (T.restrict hV)
λ v w, hT v w
lemma
linear_map.is_symmetric.restrict_invariant
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "submodule" ]
If a symmetric operator preserves a submodule, its restriction to that submodule is symmetric.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.restrict_scalars {T : E →ₗ[𝕜] E} (hT : T.is_symmetric) : @linear_map.is_symmetric ℝ E _ _ (inner_product_space.is_R_or_C_to_real 𝕜 E) (@linear_map.restrict_scalars ℝ 𝕜 _ _ _ _ _ _ (inner_product_space.is_R_or_C_to_real 𝕜 E).to_module (inner_product_space.is_R_or_C_to_real 𝕜 E).to_module _ ...
λ x y, by simp [hT x y, real_inner_eq_re_inner, linear_map.coe_restrict_scalars_eq_coe]
lemma
linear_map.is_symmetric.restrict_scalars
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "inner_product_space.is_R_or_C_to_real", "linear_map.coe_restrict_scalars_eq_coe", "linear_map.is_symmetric", "linear_map.restrict_scalars", "real_inner_eq_re_inner" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric_iff_inner_map_self_real (T : V →ₗ[ℂ] V): is_symmetric T ↔ ∀ (v : V), conj ⟪T v, v⟫_ℂ = ⟪T v, v⟫_ℂ
begin split, { intros hT v, apply is_symmetric.conj_inner_sym hT }, { intros h x y, nth_rewrite 1 ← inner_conj_symm, nth_rewrite 1 inner_map_polarization, simp only [star_ring_end_apply, star_div', star_sub, star_add, star_mul], simp only [← star_ring_end_apply], rw [h (x + y), h (x - y), ...
lemma
linear_map.is_symmetric_iff_inner_map_self_real
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "complex.I", "complex.conj_I", "inner_conj_symm", "inner_map_polarization", "inner_map_polarization'", "ring", "star_div'", "star_ring_end_apply", "star_sub" ]
A linear operator on a complex inner product space is symmetric precisely when `⟪T v, v⟫_ℂ` is real for all v.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.inner_map_polarization {T : E →ₗ[𝕜] E} (hT : T.is_symmetric) (x y : E) : ⟪T x, y⟫ = (⟪T (x + y), x + y⟫ - ⟪T (x - y), x - y⟫ - I * ⟪T (x + (I : 𝕜) • y), x + (I : 𝕜) • y⟫ + I * ⟪T (x - (I : 𝕜) • y), x - (I : 𝕜) • y⟫) / 4
begin rcases @I_mul_I_ax 𝕜 _ with (h | h), { simp_rw [h, zero_mul, sub_zero, add_zero, map_add, map_sub, inner_add_left, inner_add_right, inner_sub_left, inner_sub_right, hT x, ← inner_conj_symm x (T y)], suffices : (re ⟪T y, x⟫ : 𝕜) = ⟪T y, x⟫, { rw conj_eq_iff_re.mpr this, ring, }, { rw ...
lemma
linear_map.is_symmetric.inner_map_polarization
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "inner_add_left", "inner_add_right", "inner_conj_symm", "inner_smul_left", "inner_smul_right", "inner_sub_left", "inner_sub_right", "is_R_or_C.conj_I", "linear_map.map_smul", "mul_assoc", "mul_neg", "mul_zero", "neg_one_mul", "one_mul", "ring", "zero_mul" ]
Polarization identity for symmetric linear maps. See `inner_map_polarization` for the complex version without the symmetric assumption.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
is_symmetric.inner_map_self_eq_zero {T : E →ₗ[𝕜] E} (hT : T.is_symmetric) : (∀ x, ⟪T x, x⟫ = 0) ↔ T = 0
begin simp_rw [linear_map.ext_iff, zero_apply], refine ⟨λ h x, _, λ h, by simp_rw [h, inner_zero_left, forall_const]⟩, rw [← @inner_self_eq_zero 𝕜, hT.inner_map_polarization], simp_rw [h _], ring, end
lemma
linear_map.is_symmetric.inner_map_self_eq_zero
analysis.inner_product_space
src/analysis/inner_product_space/symmetric.lean
[ "analysis.inner_product_space.basic", "analysis.normed_space.banach", "linear_algebra.sesquilinear_form" ]
[ "forall_const", "inner_self_eq_zero", "inner_zero_left", "linear_map.ext_iff", "ring" ]
A symmetric linear map `T` is zero if and only if `⟪T x, x⟫_ℝ = 0` for all `x`. See `inner_map_self_eq_zero` for the complex version without the symmetric assumption.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form : E →ₗ[ℝ] E →ₗ[ℝ] ℝ
begin let z : alternating_map ℝ E ℝ (fin 0) ≃ₗ[ℝ] ℝ := alternating_map.const_linear_equiv_of_is_empty.symm, let y : alternating_map ℝ E ℝ (fin 1) →ₗ[ℝ] E →ₗ[ℝ] ℝ := (linear_map.llcomp ℝ E (alternating_map ℝ E ℝ (fin 0)) ℝ z) ∘ₗ alternating_map.curry_left_linear_map, exact y ∘ₗ (alternating_map.curry...
def
orientation.area_form
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "alternating_map", "alternating_map.curry_left_linear_map", "linear_map.llcomp" ]
An antisymmetric bilinear form on an oriented real inner product space of dimension 2 (usual notation `ω`). When evaluated on two vectors, it gives the oriented area of the parallelogram they span.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_to_volume_form (x y : E) : ω x y = o.volume_form ![x, y]
by simp [area_form]
lemma
orientation.area_form_to_volume_form
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_apply_self (x : E) : ω x x = 0
begin rw area_form_to_volume_form, refine o.volume_form.map_eq_zero_of_eq ![x, x] _ (_ : (0 : fin 2) ≠ 1), { simp }, { norm_num } end
lemma
orientation.area_form_apply_self
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_swap (x y : E) : ω x y = - ω y x
begin simp only [area_form_to_volume_form], convert o.volume_form.map_swap ![y, x] (_ : (0 : fin 2) ≠ 1), { ext i, fin_cases i; refl }, { norm_num } end
lemma
orientation.area_form_swap
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_neg_orientation : (-o).area_form = -o.area_form
begin ext x y, simp [area_form_to_volume_form] end
lemma
orientation.area_form_neg_orientation
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form' : E →L[ℝ] (E →L[ℝ] ℝ)
((↑(linear_map.to_continuous_linear_map : (E →ₗ[ℝ] ℝ) ≃ₗ[ℝ] (E →L[ℝ] ℝ))) ∘ₗ o.area_form).to_continuous_linear_map
def
orientation.area_form'
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "linear_map.to_continuous_linear_map" ]
Continuous linear map version of `orientation.area_form`, useful for calculus.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form'_apply (x : E) : o.area_form' x = (o.area_form x).to_continuous_linear_map
rfl
lemma
orientation.area_form'_apply
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
abs_area_form_le (x y : E) : |ω x y| ≤ ‖x‖ * ‖y‖
by simpa [area_form_to_volume_form, fin.prod_univ_succ] using o.abs_volume_form_apply_le ![x, y]
lemma
orientation.abs_area_form_le
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "fin.prod_univ_succ" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_le (x y : E) : ω x y ≤ ‖x‖ * ‖y‖
by simpa [area_form_to_volume_form, fin.prod_univ_succ] using o.volume_form_apply_le ![x, y]
lemma
orientation.area_form_le
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "fin.prod_univ_succ" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
abs_area_form_of_orthogonal {x y : E} (h : ⟪x, y⟫ = 0) : |ω x y| = ‖x‖ * ‖y‖
begin rw [o.area_form_to_volume_form, o.abs_volume_form_apply_of_pairwise_orthogonal], { simp [fin.prod_univ_succ] }, intros i j hij, fin_cases i; fin_cases j, { simpa }, { simpa using h }, { simpa [real_inner_comm] using h }, { simpa } end
lemma
orientation.abs_area_form_of_orthogonal
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "fin.prod_univ_succ", "real_inner_comm" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_map {F : Type*} [normed_add_comm_group F] [inner_product_space ℝ F] [fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) (x y : F) : (orientation.map (fin 2) φ.to_linear_equiv o).area_form x y = o.area_form (φ.symm x) (φ.symm y)
begin have : φ.symm ∘ ![x, y] = ![φ.symm x, φ.symm y], { ext i, fin_cases i; refl }, simp [area_form_to_volume_form, volume_form_map, this], end
lemma
orientation.area_form_map
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "fact", "inner_product_space", "normed_add_comm_group", "orientation.map" ]
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83
area_form_comp_linear_isometry_equiv (φ : E ≃ₗᵢ[ℝ] E) (hφ : 0 < (φ.to_linear_equiv : E →ₗ[ℝ] E).det) (x y : E) : o.area_form (φ x) (φ y) = o.area_form x y
begin convert o.area_form_map φ (φ x) (φ y), { symmetry, rwa ← o.map_eq_iff_det_pos φ.to_linear_equiv at hφ, rw [fact.out (finrank ℝ E = 2), fintype.card_fin] }, { simp }, { simp } end
lemma
orientation.area_form_comp_linear_isometry_equiv
analysis.inner_product_space
src/analysis/inner_product_space/two_dim.lean
[ "analysis.inner_product_space.dual", "analysis.inner_product_space.orientation", "data.complex.orientation", "tactic.linear_combination" ]
[ "fintype.card_fin" ]
The area form is invariant under pullback by a positively-oriented isometric automorphism.
https://github.com/leanprover-community/mathlib
65a1391a0106c9204fe45bc73a039f056558cb83