Null-space proof for square matrix

In summary, the given conversation discusses the null space of a square matrix and its properties. It is proven that the sum and scalar multiple of vectors in the null space of the matrix also belong to the null space. Additionally, there is a question about the proof for assuming the matrix is non-singular.
  • #1
VitaminC
4
0

Homework Statement



Suppose F is a field and A ε Mnn(F) is a square matrix whose kjth entry is denoted
by akj ε F for all 1 ≤ k,j ≤ n. Suppose further that (b1; . . . ; bn) and (c1; . . . ; cn)
belong to the null space of A.

i) Prove that the sum (b1 + c1; b2 + c2; . . . ; bn + cn) also belongs to the null space of A

ii) Suppose d ε F. Prove that the scalar multiple (db1; . . . ; dbn) also belongs to the
null space of A.

Homework Equations


The Attempt at a Solution



For both proofs,

Assume A is a non-singular; the linear system (A,0) has a unique solution
----> is there a proof for this assumption using akj ε F for all 1 ≤ k,j ≤ n ?

Thus, A is non-singular <=> LS(A,0)
<=> leading ones (# of nonzero rows) is equal to the number of rows
<=> A = I (identity matrix)

For i)
Each leading one of the matrix will equal to some corresponding (b1,...,bn) or (c1,...,cn).
Since (b1,...,bn) and (c1,...,cn) fall in the null space of A, the corresponding (b1,...,bn) and (c1,...,cn) of A = I ,should equal 0.

Thus, b1 = 0 and c1 = 0 --> b1 = c1 --> b1 + b1 = 0 --> b1 + c1 = 0 for all (b1,...,bn) and (c1,...,cn). Thus, (b1 + c1, b2 + c2, . . . , bn + cn) is also in the null space of A. For ii) from i), I established that some corresponding (b1,...,bn) will equal 0, when A = I. Thus, multiplying by the scalar 'd' does not change the output.

So, (db1,...,dbn) = (b1,...,bn) --> (db1,...,dbn) is also in the null space of A.
 
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  • #2
VitaminC said:

Homework Statement



Suppose F is a field and A ε Mnn(F) is a square matrix whose kjth entry is denoted
by akj ε F for all 1 ≤ k,j ≤ n. Suppose further that (b1; . . . ; bn) and (c1; . . . ; cn)
belong to the null space of A.

i) Prove that the sum (b1 + c1; b2 + c2; . . . ; bn + cn) also belongs to the null space of A

ii) Suppose d ε F. Prove that the scalar multiple (db1; . . . ; dbn) also belongs to the
null space of A.

Homework Equations





The Attempt at a Solution



For both proofs,

Assume A is a non-singular; the linear system (A,0) has a unique solution
----> is there a proof for this assumption using akj ε F for all 1 ≤ k,j ≤ n ?

Thus, A is non-singular <=> LS(A,0)
<=> leading ones (# of nonzero rows) is equal to the number of rows
<=> A = I (identity matrix)

For i)
Each leading one of the matrix will equal to some corresponding (b1,...,bn) or (c1,...,cn).
Since (b1,...,bn) and (c1,...,cn) fall in the null space of A, the corresponding (b1,...,bn) and (c1,...,cn) of A = I ,should equal 0.

Thus, b1 = 0 and c1 = 0 --> b1 = c1 --> b1 + b1 = 0 --> b1 + c1 = 0 for all (b1,...,bn) and (c1,...,cn). Thus, (b1 + c1, b2 + c2, . . . , bn + cn) is also in the null space of A.


For ii) from i), I established that some corresponding (b1,...,bn) will equal 0, when A = I. Thus, multiplying by the scalar 'd' does not change the output.

So, (db1,...,dbn) = (b1,...,bn) --> (db1,...,dbn) is also in the null space of A.

Someone else asked what seems to be the same question - see https://www.physicsforums.com/showthread.php?t=539211.
 

FAQ: Null-space proof for square matrix

1. What is a null-space proof for a square matrix?

A null-space proof for a square matrix is a mathematical method used to determine if a given square matrix has a non-trivial null-space, meaning that it has a non-zero vector that when multiplied by the matrix results in a zero vector.

2. Why is it important to prove the existence of a null-space in a square matrix?

Proving the existence of a null-space in a square matrix is important because it helps us understand the properties and behavior of the matrix. It also allows us to determine if the matrix is invertible or not, which is crucial in many applications.

3. How is a null-space proof for a square matrix performed?

A null-space proof for a square matrix is typically performed by finding the reduced row-echelon form of the matrix and identifying any free variables. If there are any free variables, it indicates the existence of a non-trivial null-space.

4. What does a non-trivial null-space mean?

A non-trivial null-space means that there is at least one non-zero vector that when multiplied by the matrix results in a zero vector. This indicates that the matrix is not invertible and has some linearly dependent columns or rows.

5. Can a square matrix have a non-trivial null-space and still be invertible?

No, a square matrix cannot have a non-trivial null-space and be invertible at the same time. A non-trivial null-space indicates that the matrix is not invertible and has some linearly dependent columns or rows. An invertible matrix must have linearly independent columns and rows.

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