Inner Product Spaces of 2x2 Matrix

In summary: This board doesn't have a way to do subscripts, so I used u12 to mean "u subscript 1 squared" and so on.Based on the given formula, it looks like the positivity axiom does not hold true for this inner product. In order to prove this, we need to find a 2x2 matrix U such that <U,U> = u1^2 + 2(u2.u3) + u4^2 < 0. This can be done through trial and error, by choosing values for u2 and u3 that make the middle term 2(u2.u3) more negative than the two squared terms are positive. This shows that the positivity axiom does not hold true for <U,V
  • #1
abbasb
5
0

Homework Statement



Show that <U,V> = u1.v1 + u2.v3 + u2.v3 + u4.v4 is NOT an inner product on M2x2

Homework Equations


U: row 1 = [u1 u2] row 2 = [u3 u4] V: row 1 = [v1 v2] row 2 = [v3 v4]

The Attempt at a Solution



As I went through each of the axioms, I found that they were all correct (at least the way I did it), I've been stuck for quite some time now. I found that the symmetry axiom, additivity axiom and homogeneity axiom all remained true. So I'm assuming the positivity axiom doesn't hold true, I'm just confused as how to show this.
 
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  • #2
abbasb said:

Homework Statement



Show that <U,V> = u1.v1 + u2.v3 + u2.v3 + u4.v4 is NOT an inner product on M2x2
Your formula looks like it might have a typo, with u2.v3 appearing twice. Is that how the problem is worded?
abbasb said:

Homework Equations


U: row 1 = [u1 u2] row 2 = [u3 u4] V: row 1 = [v1 v2] row 2 = [v3 v4]

The Attempt at a Solution



As I went through each of the axioms, I found that they were all correct (at least the way I did it), I've been stuck for quite some time now. I found that the symmetry axiom, additivity axiom and homogeneity axiom all remained true. So I'm assuming the positivity axiom doesn't hold true, I'm just confused as how to show this.
 
  • #3
Sorry, its supposed to be <U,V> = u1.v1 + u2.v3 + u3.v2 + u4.v4

and U and V are supposed to be matrices...couldn't find a better way to show them as so.
 
  • #4
I'm leaning toward the positivity thing, too. Can you come up with a 2x2 matrix U for which <U, U> = u12 + u2u3 + u3u2 + u42 < 0? Try playing around with a mix of positive and negative numbers for which the sume of u2u3 and u3u2 is more negative than the two squared terms are positive.
 
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  • #5
Mark44 said:
I'm leaning toward the positivity thing, too. Can you come up with a 2x2 matrix U for which <U, U> = u12 + u2u3 + u3u2 + u22 < 0? Try playing around with a mix of positive and negative numbers for which the sume of u2u3 and u3u2 is more negative than the two squared terms are positive.

But shouldn't I be looking for a 2x2 matrix such that <U,U> = u1^2 + 2(u2.u3) + u4^2 < 0? And the only way I could find such a matrix is through trial and error?
 
  • #6
abbasb said:
But shouldn't I be looking for a 2x2 matrix such that <U,U> = u1^2 + 2(u2.u3) + u4^2 < 0? And the only way I could find such a matrix is through trial and error?
First question: yes. u12 and u42 are always going to be nonnegative, so can you fiddle with values of u2 and u3 so that 2u2u3 is more negative than the two squared terms are positive?
Second question: Yes, but using judicious trial and error. You're only dealing with 2x2 matrices, and you can start with 1s in the main diagonal positions. That leaves you only two other positions to fill in.

BTW, I edited my previous post to fix a subscript.
 

FAQ: Inner Product Spaces of 2x2 Matrix

1. What is an inner product space?

An inner product space is a mathematical concept that combines the properties of a vector space and an inner product. It is a set of vectors with defined operations of addition and scalar multiplication, as well as an inner product operation that satisfies certain properties such as linearity and symmetry.

2. How do you define an inner product for 2x2 matrices?

The inner product of two 2x2 matrices A and B can be defined as the sum of the products of their corresponding elements. In other words, if A = [a, b; c, d] and B = [e, f; g, h], then their inner product is a*e + b*f + c*g + d*h. This definition satisfies the properties of linearity and symmetry, making it a valid inner product for 2x2 matrices.

3. What is the significance of inner product spaces in linear algebra?

Inner product spaces play a crucial role in linear algebra as they allow for the definition of important concepts such as orthogonality, projections, and norms. They also provide a way to measure the angle between two vectors, which is useful in many applications such as signal processing and data analysis.

4. Can an inner product space of 2x2 matrices be infinite-dimensional?

Yes, an inner product space of 2x2 matrices can be infinite-dimensional. This means that the set of 2x2 matrices with a defined inner product operation can have an infinite number of basis vectors, making it a larger space compared to a finite-dimensional inner product space.

5. How are inner product spaces of 2x2 matrices used in real-world applications?

Inner product spaces of 2x2 matrices have many applications in various fields such as physics, engineering, and computer science. For example, they are used in quantum mechanics to describe the properties of quantum states, in image processing to analyze and manipulate images, and in machine learning to perform matrix factorization and dimensionality reduction.

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