Kets and Vectors: Exploring 3-D Representation

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In summary, when working in 3-D, the kets | x > and | p > are not vectors but rather elements in an infinite-dimensional space. They are not coordinates or numbers, but rather distributions in the dual space of a Schwartz space of smooth functions. The labels are the only vectors in 3D. The need for conjugation arises due to the presence of a minus sign in the real part of complex number multiplication.
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dyn
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Hi. I have read that when working in 3-D the following kets | x > and | p > are not vectors in 3-D. If that is correct what are they ? I know | ψ > is an abstract vector but I thought | x > and | p > would be 3-D vectors in the position and momentum representation ?
Thanks
 
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  • #2
They are vectors in an infinite-dimensional space. It is natural to feel that ##|x\rangle## should be in a 3d space because ##x##, without the enclosing symbols, is a coordinate in 3D space. But ##|x\rangle## is not a coordinate or any other type of number. In the position representation it is the Dirac delta function ##\delta_x##, which is an element of a space of functions, which - like most function spaces - is infinite-dimensional.
 
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  • #3
<a is conjugate of a>
<a|b> kind of dot(a.conjugate , b)
b><b|a> projection into other direction like b*dot(b.conjugate , a)

v2=pol><pol|v> is equivalent with this pseudo code
amp=dot(v,pol)
v2.x = pol.x*amp
v2.y = pol.y*amp

conjugate of V is V.imaginary=-V.imaginary
 
  • #4
The Pauli matrices transform the 3d direction into 2d complex vector like spin.
 
  • #5
Why do we need conjugation?
because there is a minus sign in real part of multiplication of complex numbers.

complex operator *(complex c)
{
complex e;
e.real = this->real*c.real - this->img*c.img;
e.img = this->img*c.real + this->real*c.img;
return e;
}
 
  • #6
dyn said:
x > and | p > are not vectors in 3-D. If that is correct what are they ?
They are distributions, elements in the dual space of a Schwartz space of smooth functions. Only the labels are vectors in 3D.
 
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Related to Kets and Vectors: Exploring 3-D Representation

1. What are kets and vectors?

Kets and vectors are mathematical representations of physical quantities or properties. They are commonly used in quantum mechanics and linear algebra to describe the state of a system.

2. How are kets and vectors related to 3-D representation?

Kets and vectors can be used to represent three-dimensional space by assigning coordinates to each component of the vector. This allows for a more visual and intuitive understanding of the system.

3. What is the difference between a ket and a vector?

A ket is a specific type of vector that is used in quantum mechanics, while a vector can represent any physical quantity or property. Kets have additional mathematical properties that make them useful for describing quantum systems.

4. How are kets and vectors used in scientific research?

Kets and vectors are used in various fields of science, including quantum mechanics, physics, and engineering. They are particularly useful for understanding the behavior of particles and systems at the microscopic level.

5. Are there any limitations to using kets and vectors for 3-D representation?

While kets and vectors are powerful tools for representing three-dimensional space, they may not always accurately reflect the complexity of certain systems. In some cases, other mathematical representations may be needed to fully understand a system.

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