MATHEMATICS S6 UNIT 6: Intersection and Sum of Subspaces.

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In linear algebra, the concepts of Intersection and Sum of Subspaces are fundamental operations that allow us to combine and relate different subspaces within a larger vector space.

Let be a vector space over a field , and let and be two subspaces of .

Intersection of Subspaces (∩W)

Definition: The intersection of two subspaces and , denoted ∩W, is the set of all vectors that are common to both and .

                                                           U∩W= {v∈V ∣v∈U and v∈W}

Property: W is always a Subspace.

 A key property is that the intersection of any two (or more) subspaces is always a subspace itself. To prove this, we can use the subspace test:

  1. Contains the zero vector: Since and are subspaces, they both contain the zero vector ​. Therefore, ​∈ U∩W.
  2. Closed under vector addition: Let ​, v2​∈U∩W. This means ​∈U, ​∈W, ​∈U, and ​∈W. Since is a subspace, ​+v2​∈U. Since is a subspace, ​+v2​∈W. Thus, ​+v2​∈U∩W.
  3. Closed under scalar multiplication: Let ∈U∩W and ∈F (a scalar). This means ∈U and ∈W. Since is a subspace, ∈U. Since is a subspace, ∈W. Thus, ∈U∩W.

Since all three conditions are met, ∩W is a subspace of .

Example: In , let be the x-y plane (= {(x, y,0) ∣x,y∈R}) and be the y-z plane (={(0,y,z) ∣y,z∈R}). Their intersection ∩W would be the y-axis: ∩W= {(0, y,0) ∣y∈R}. This is indeed a subspace of .

Sum of Subspaces (+W)

Definition: The sum of two subspaces and , denoted +W, is the set of all possible sums of a vector from and a vector from .

                                                             U+W= {u+w ∣u∈U and w∈W}

Property: +W is always a Subspace The sum of two subspaces is also always a subspace. We can prove this using the subspace test:

  1. Contains the zero vector: Since and are subspaces, ​∈U and ​∈W. Therefore, ​=0V​+0V​∈U+W.
  2. Closed under vector addition: Let ​, v2​∈U+W. By definition, ​=u1​+w1​ for some ​∈U, w1​∈W, and ​=u2​+w2​ for some ​∈U, w2​∈W. Then ​+v2 ​=(u1​+w1​) +(u2​+w2​) = (u1​+u2​) +(w1​+w2​). Since is a subspace, ​+u2​∈U. Since is a subspace, ​+w2​∈W. Thus, u1​+u2​) +(w1​+w2​) ∈U+W.
  3. Closed under scalar multiplication: Let ∈U+W and ∈F. By definition, = u+w for some ∈U, w∈W. Then =c(u+w) =cu+cw. Since is a subspace, ∈U. Since is a subspace, ∈W. Thus, +cw ∈U+W.

Since all three conditions are met, +W is a subspace of . The sum +W is often described as the smallest subspace that contains both and . It’s equivalent to the span of the union of bases for and .

Example: In , let be the x-axis (={(x,0,0) ∣x∈R}) and be the y-axis (= {(0, y,0) ∣y∈R}). Their sum +W would be the x-y plane: +W= {(x, y,0) ∣x,y∈R}.

Dimension Formula (Grassmann’s Formula)

For finite-dimensional vector spaces, there’s an important relationship between the dimensions of , , ∩W, and +W:

(U)+dim(W)=dim(U∩W) + dim(U+W)

This formula is extremely useful for finding the dimension of the sum or intersection if the other dimensions are known.

Example using the formula: Using the previous example in :

  • : x-y plane, (U)=2
  • : y-z plane, (W)=2
  • ∩W: y-axis, (U∩W) =1

Using the formula: (U+W) = dim(U)+dim(W)−dim(U∩W) =2+2−1=3. This matches, as +W in this case would be all of , which has dimension 3.

Direct Sum (⊕W)

A special case of the sum of subspaces is the direct sum.

Definition: The sum +W is called a direct sum, denoted ⊕W, if and only if their intersection is the zero vector only: ∩W={0V​}

Properties of Direct Sums:

  • If =U⊕W, then every vector ∈V can be written uniquely as a sum =u+w, where ∈U and ∈W.
  • For a direct sum, the dimension formula simplifies: (U⊕W) = dim(U)+dim(W). This makes sense because there’s no “overlap” (beyond the zero vector) to subtract.
  • The concept of direct sum is crucial for decomposing a vector space into simpler components.

Example of Direct Sum: In , let be the x-axis (={(x,0,0) ∣x∈R}) and be the y-z plane (= {(0, y,z) ∣y,z∈R}).

  • ∩W= {(0,0,0)}, so their intersection is just the zero vector.
  • Therefore, their sum is a direct sum: =U⊕W. Every vector a,b,c) in can be uniquely written as a,0,0)+(0,b,c).
  • (U)=1, (W)=2.
  • (U⊕W) =1+2=3, which is (R3).

Understanding the intersection and sum of subspaces is crucial for comprehending the structure of vector spaces, linear transformations, and many other advanced topics in linear algebra.

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What Will You Learn?

  • Define Subspace: Clearly articulate what a subspace is and be able to verify if a given subset of a vector space is indeed a subspace.
  • Define Intersection of Subspaces: Understand the definition of U∩W as the set of vectors common to both U and W.
  • Define Sum of Subspaces: Understand the definition of U+W as the set of all possible sums of a vector from U and a vector from W.
  • Understand Subspace Properties: Prove that both U∩W and U+W are themselves subspaces. This demonstrates a deeper understanding of the subspace axioms.
  • Geometric Intuition: Develop a strong geometric intuition for intersection and sum, especially in R*R and R*R*R (e.g., intersection of planes, sum of lines forming a plane).
  • Formulate a system of linear equations that vectors in the intersection must satisfy.
  • Solve the system to find the general form of vectors in the intersection.
  • Extract a basis for U∩W from the general solution.
  • Determine the dimension of U∩W.
  • Form the union of the bases of U and W.
  • Identify and remove linearly dependent vectors from this union to find a basis for U+W.
  • Determine the dimension of U+W.
  • Understand that U+W=span(Bu ∪ Bw) where Bu and Bw are bases for U and W respectively.
  • State and apply the formula: dim(U)+dim(W)=dim(U∩W)+dim(U+W).
  • Use the formula to calculate an unknown dimension (e.g., find dim(U+W) if dim(U), dim(W), and dim(U∩W) are known).
  • Define Direct Sum (U⊕W): Understand that U+W is a direct sum if and only if U∩W={0v}.
  • Unique Representation Property: Understand that if V=U⊕W, every vector in V has a unique representation as a sum of a vector from U and a vector from W.
  • Dimension of Direct Sums: Apply the simplified dimension formula for direct sums: dim(U⊕W)=dim(U)+dim(W).
  • Identifying Direct Sums: Given two subspaces, determine if their sum is a direct sum.
  • Finding Complements: Understand the concept of a "complementary subspace" (i.e., a subspace W such that V=U⊕W).

Course Content

Definition.

  • Definitions.
    15:45

Intersection and Sum of two Vector Spaces.

Checking My Progress

End of Unit Assessment.

Final Unit Exam.

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