Inner product and hermitic product

In summary, to prove the triangle inequality ||v+w|| ≤ ||v||+||w|| in a Hermitic space, we used the Hermitic product and the property |[v,w]| ≤ ||v|| . ||w|| to expand and simplify ||v+w||². This led us to the conclusion that ||v+w|| ≤ ||v|| + ||w||, thus proving the triangle inequality.
  • #1
damabo
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Homework Statement



prove the triangle inequality ||v+w|| ≤ ||v||+||w||
if (ℂ, V, + , [ , ] ) is a Hermitic space where [ , ] is the Hermitic product.


Homework Equations



|[v,w]| ≤ ||v|| . ||w||

[itex]\overline{a+b i}[/itex]= a-b i (where i is the imaginary number, a+bi a complex number)

The Attempt at a Solution



||v+w||² = [v+w,v+w]. Since [v+w,v+w] = [itex]\overline{[v+w,v+w]}[/itex], [v+w,v+w] must be a real number. this means that the same rules will apply as in the inner product on the innerproductspace (ℝ, V, +, [ , ] ) ( true ?). so [v+w,v+w] = [v,v] + [w,w] + 2[v,w] ≤ ||v||²+||w||²+2||v|| ||w|| = (||v|| + ||w|| ) ²
this means ||v+w|| ≤ ||v|| + ||w||
 
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  • #2


To prove the triangle inequality, we will use the Hermitic product and the property that |[v,w]| ≤ ||v|| . ||w||. We will start by expanding ||v+w||² using the Hermitic product as follows:

||v+w||² = [v+w,v+w] = [v,v] + [v,w] + [w,v] + [w,w]

Since the Hermitic product is a real number, we can take its complex conjugate without changing its value. Therefore, we can rewrite the above equation as:

||v+w||² = \overline{[v,v] + [v,w] + [w,v] + [w,w]}

Using the property that |[v,w]| ≤ ||v|| . ||w||, we can further simplify the equation as:

||v+w||² = \overline{[v,v] + [w,w]} + \overline{[v,w] + [w,v]}

Next, we can use the property that \overline{a+b i}= a-b i to rewrite the above equation as:

||v+w||² = [v,v] + [w,w] + [v,w] + [w,v]

Now, we can use the Hermitic product to rewrite [v,w] and [w,v] as:

||v+w||² = [v,v] + [w,w] + [v,w] + [w,v] = [v,v] + [w,w] + 2[v,w]

Finally, we can use the property that |[v,w]| ≤ ||v|| . ||w|| to rewrite the above equation as:

||v+w||² = [v,v] + [w,w] + 2[v,w] ≤ ||v||² + ||w||² + 2||v|| ||w|| = (||v|| + ||w||)²

Since ||v+w||² is a real number, we can take its square root without changing its value. Therefore, we can conclude that:

||v+w|| ≤ ||v|| + ||w||

Thus, we have proven the triangle inequality for a Hermitic space.
 

1. What is an inner product?

An inner product is a mathematical operation that takes two vectors and produces a scalar value. It is often used in linear algebra and functional analysis to measure the length of a vector, the angle between two vectors, and to define notions of orthogonality and projection.

2. What is the difference between an inner product and a hermitic product?

While both inner and hermitic products take two vectors and produce a scalar value, they differ in the properties of the vectors they can operate on. Inner products are defined for real vector spaces, while hermitic products are defined for complex vector spaces. Additionally, hermitic products are required to be linear in the first argument and conjugate-linear in the second argument, while inner products do not have this restriction.

3. How is an inner product used in quantum mechanics?

In quantum mechanics, inner products are used to calculate the probability amplitudes of various quantum states. The inner product of two quantum states gives the probability of transitioning from one state to another. It is also used to define the concept of orthogonality between quantum states, which plays a crucial role in the measurement process.

4. Can an inner product be negative?

Yes, an inner product can be negative. In fact, the inner product of two vectors can be positive, negative, or zero. The sign of the inner product depends on the angle between the two vectors. If the angle is acute, the inner product will be positive. If the angle is obtuse, the inner product will be negative. And if the angle is a right angle, the inner product will be zero.

5. How is a hermitic product related to a matrix product?

A hermitic product is closely related to a matrix product. In fact, the hermitic product between two vectors can be expressed as the matrix product of one vector with the conjugate transpose of the other vector. This property is useful in many applications, including solving systems of linear equations and calculating eigenvalues and eigenvectors.

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