Sum
Definition 1. Let W1,...,Wk≤VW1,...,Wk≤V. We define the sum of these subspaces to be the set {v1+⋯+vk|vi∈Wi for 1≤i≤k}{v1+⋯+vk|vi∈Wi for 1≤i≤k}, which we denote by k∑i=1Wi.k∑i=1Wi.
Direct Sum
Definition 2. Let W1,...,Wk≤VW1,...,Wk≤V. We call VV the direct sum of W1,...,WkW1,...,Wk and write V=k⨁i=1Wi,V=k⨁i=1Wi, if V=∑ki=1WiV=∑ki=1Wi and Wj∩∑i≠jWi={0}Wj∩∑i≠jWi={0} for each j(1≤j≤k)j(1≤j≤k).
조건 Wj∩∑i≠jWi={0}Wj∩∑i≠jWi={0}은 W1∩⋯∩Wk={0}W1∩⋯∩Wk={0}과 동치이다. 두 조건 모두 유일성과 관련된 조건이기 때문이다.
Theorem 1
Theorem 1. Let W1,...,Wk≤VW1,...,Wk≤V where VV is finite-dimensional. The following conditions are equivalent.
(a) V=⨁ki=1WiV=⨁ki=1Wi.
(b) V=∑ki=1WiV=∑ki=1Wi and for any v1,...,vkv1,...,vk such that vi∈Wi(1≤i≤k)vi∈Wi(1≤i≤k), if v1+⋯+vk=0v1+⋯+vk=0, then vi=0,∀ivi=0,∀i.
(c) ∀v∈V,v∀v∈V,v can be uniquely written as v=v1+⋯+vk,v=v1+⋯+vk, where vi∈Wi(1≤i≤k)vi∈Wi(1≤i≤k).
(d) If γiγi is an ordered basis for Wi(1≤i≤k)Wi(1≤i≤k), then ∪ki=1γi∪ki=1γi is an ordered basis for VV.
(e) ∀i∈{1,...,k}∀i∈{1,...,k}, ∃∃ an ordered basis γiγi for WiWi such that ∪ki=1γi∪ki=1γi is an ordered basis for VV.
Proof. (a) ⟹⟹ (b)
Clearly V=∑ki=1WiV=∑ki=1Wi. Suppose that ∀vi∈Wi(1≤i≤k)∀vi∈Wi(1≤i≤k), v1+⋯+vk=0v1+⋯+vk=0. Then −vj=v1+⋯+vj−1+vj+1+⋯+vk−vj=v1+⋯+vj−1+vj+1+⋯+vk. Note that −vj∈Wj∩∑i≠jWi−vj∈Wj∩∑i≠jWi. Then vj=0,∀jvj=0,∀j.
(b) ⟹⟹ (c)
Suppose that there is two representation of vv: v=v1+⋯+vk=u1+⋯+ukv=v1+⋯+vk=u1+⋯+uk. Then (v1−u1)+⋯+(vk−uk)=0, and we have each vi−ui=0, so vi=ui for each i(1≤i≤k). Thus v can be uniquely written as v=v1+⋯+vk.
(c) ⟹ (d)
γ=∑ki=1γi generates V from (c). Suppose that k∑i=1ni∑j=1aijvij for some aij∈F, where ni=|γi|. Denote wi=∑nij=1aijvij. Then ∑ki=1wi=0.
Since 0=0+⋯+0, each wi=0=∑nij=1aijvij. Then aij=0,∀i,∀j, because γi is linearly independent. Thus γ is an ordered basis for V.
(d) ⟹ (e)
Trivial.
(e) ⟹ (a)
Let γi be an ordered basis for Wi(1≤i≤k) such that γ:=∪ki=1γi is an ordered basis for V. Then V=⟨∪ki=1γi⟩=⟨γi⟩+⋯⟨γk⟩=k∑i=1Wi. Suppose that for some v∈Wj∩∑i≠jWi, v is nonzero. Then v∈Wj=⟨γj⟩ and v∈∑i≠jWi=⟨∪i≠jγi⟩. Thus v can be expressed as a linear combination of γ in more than one way. ⨂ Thus v=0. Hence for each j(1≤j≤k), Wj∩∑i≠jWi={0} , i.e., V=⨁ki=1Wi. ◼
Remark
Remark. If V=⨁ki=1Wi, then Wi∩Wj={0} for all i≠j.
Theorem 2
Theorem 2. Let W1,W2≤V be finite-dimensional. Then W1+W2 is finite-dimensional, and dim(W1+W2)=dim(W1)+dim(W2)−dim(W1∩W2).
Proof. Let γ={u1,...,uk} be a basis for W1∩W2. Extend γ to a basis β1={u1,...,uk,v1,...,vm} for W1 and β2={u1,...,uk,w1,...,wp} for W2. Let β:=β1∪β2={u1,...,uk,v1,...,vm,w1,...,wp}. Clearly, ⟨β⟩=W1+W2. Thus β generates W1+W2.
Suppose that β1∪{w1} is linearly dependent. Then w1∈⟨β1⟩. Then w1=∑ki=1akwk+∑mj=1bjvj for some ai,bj∈F. Note that w1∈W1∩W2. Then w1=∑ki=1ciui for some ci∈F. Thus ∑ki=1(ci−ai)ui+∑mj=1bjvj=0, so ci=ai and bj=0 for all i,j. By Theorem 2, w1∈⟨γ⟩, so γ∪{w1} is linearly dependent. ⨂
In similar manner, we can show that Si={u1,...,uk,v1,...,vm,w1,...,wi} is linearly independent for 1≤i≤p. Since β=Sp is linaerly independent, β is a basis for W1+W2. Hence W1+W2 is finite-dimensional, and dim(W1)+dim(W2)−dim(W1∩W2) = k+m+k+p−k = k+m+p=dim(W1+W2). ◼
Corollary
Corollary. Let W1,W2≤V be finite-dimensional, and let V=W1+W2. Then V=W1⨁W2 ⟺ dim(V)=dim(W1)+dim(W2).
Direct Sum of Matrices
Definition 3. Let B1∈Mm×m(F), and let B2∈Mn×n(F). We define the direct sum of B1 and B2, denoted B1⨁B2, as the (m+n)×(m+n) matrix A such that Aij={(B1)ijfor 1≤i,j≤m(B2)(i−m),(j−m)for m+1≤i,j≤n+m0otherwise.
If B1,...,Bk are square matrices with entries from F, then we define the direct sum of B1,...,Bk recursively by k⨁i=1Bi=(k−1⨁i=1Bi)⨁Bk. If A=⨁ki=1Bi, then we often write A=(B1⋯O⋮⋱⋮O⋯Bk).
Theorem 3
Theorem 3. Let T∈L(V) where V is finite-dimensional, and let W1,...,Wk be T-invariant subspaces of V such that V=⨁ki=1Wi. For each i, let βi be an ordered basis for Wi, and let β=∪ki=1βi. Let A=[T]β and Bi=[TWi]βi for i=1,...,k. Then A=⨁ki=1Bi.