Dot Product Notation Clarification

In summary, the notation \left|\left\langle f,g\right\rangle\right|^{2} means the square of the absolute value of the dot product between two vectors, f and g, in R^{n}. This notation accounts for both real and complex dot products, where the absolute value may be redundant for real dot products but is necessary for complex dot products. This is different from the notation for the norm of a vector, where the dot product is squared without taking the absolute value.
  • #1
CantorSet
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The following notation is from the book "Frames and Bases."

Let f and g be vectors in [tex]R^{n}[/tex] with the usual dot product <,>.

Then, what does the notation [tex]\left|\left\langle f,g\right\rangle\right|^{2}[/tex] mean?

Specifically, does it mean [tex]\left|\sum^{n}_{i=1}f_{i} g_{i}\right|[/tex]

or does it mean [tex]\left(\sum^{n}_{i=1}f_{i} g_{i}\right)^{2}[/tex]
 
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  • #2
so in such notation <f,g> is the dot product of f and g.
|<f,g>|^2 is the square of the absolute value of that dot product.
Some dot products are always real and the absolute value is redundent.
Other dot products can be complex and the absolute value is needed.
 
  • #3
lurflurf said:
so in such notation <f,g> is the dot product of f and g.
|<f,g>|^2 is the square of the absolute value of that dot product.
Some dot products are always real and the absolute value is redundent.
Other dot products can be complex and the absolute value is needed.

Thanks for responding. I was thinking that too. But it just seems inconsistent with the notation for the norm of a vector f in [tex]R^{n}[/tex].

For example, [tex]\left\langle \right f, f\rangle = \left\right\|f\|^{2}[/tex]

In this case, f dot f without further squaring is equal to [tex]\left\right\|f\|^{2}[/tex].

But in |<f,g>|^2, you need compute f dot g, and THEN you still square its absolute value.

Is that correct?
 

1. What is dot product notation and why is it used in scientific calculations?

Dot product notation, also known as scalar product notation, is a mathematical tool used to calculate the magnitude of vectors and the angle between two vectors in a multi-dimensional space. It is commonly used in scientific calculations because it simplifies complex vector calculations and allows for efficient representation of physical quantities.

2. How is dot product notation different from cross product notation?

While dot product notation calculates the magnitude of vectors, cross product notation calculates the vector that is perpendicular to two given vectors. Dot product notation involves multiplying the corresponding components of two vectors and adding them together, while cross product notation involves finding the determinant of a matrix composed of the given vectors.

3. Can dot product notation be used for vectors of any dimension?

Yes, dot product notation can be used for vectors of any dimension. However, it is most commonly used in three-dimensional space and can be extended to higher dimensions.

4. How is the dot product of two vectors related to the cosine of the angle between them?

The dot product of two vectors is equal to the product of their magnitudes and the cosine of the angle between them. This relationship is known as the geometric definition of the dot product and is often used to calculate the angle between two vectors.

5. Are there any real-life applications of dot product notation?

Yes, dot product notation has many real-life applications in fields such as physics, engineering, and computer science. It is used to calculate work, energy, force, and torque in physical systems and is also used in computer graphics to determine the lighting and shading of 3D objects.

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