Hilbert space of direct products

In summary, a Hilbert space of direct products is a mathematical concept that combines elements from two or more spaces with additional structure. It differs from a regular direct product by including inner products and norms, allowing for more advanced analysis. It has various real-world applications in fields such as quantum mechanics and engineering. In a Hilbert space of direct products, orthogonality is defined as having an inner product of zero. These spaces can also be infinite-dimensional, making them useful for modeling complex systems.
  • #1
Wiemster
72
0
How come if all states in the representation space (of say rotations) have the same energy, Hilbert space can be written as a direct product space of these representation spaces?
 
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  • #2
Direct product ? More like a direct sum.

Daniel.
 
  • #3


The concept of Hilbert space is a fundamental tool in mathematical physics, particularly in the study of quantum mechanics. It is a mathematical structure that allows us to describe the states of a physical system and the evolution of those states over time. In the case of rotations, the representation space refers to the set of all possible states of a system under rotation. These states can be described by a set of quantum numbers, such as spin, angular momentum, and energy.

Now, if all states in the representation space have the same energy, it means that they are degenerate states. This implies that they can be transformed into each other without changing the energy of the system. In other words, they are equivalent states in terms of energy. This degeneracy can occur due to symmetries of the system, such as rotational symmetry.

In such a case, the Hilbert space can be written as a direct product space of these representation spaces. This means that the states in the Hilbert space can be written as a combination of states from each representation space. This is because in a direct product space, every state is a unique combination of states from different spaces. In this case, the different representation spaces correspond to different quantum numbers, and the direct product space allows us to describe all possible combinations of these quantum numbers.

In summary, if the states in the representation space have the same energy, it implies a degeneracy in the system, which allows us to write the Hilbert space as a direct product space. This is a powerful mathematical tool that helps us understand and study the symmetries and degeneracies in physical systems, such as rotations.
 

1. What is a Hilbert space of direct products?

A Hilbert space of direct products is a mathematical concept used in functional analysis to describe a space that consists of all possible combinations of elements from two or more other spaces. It is a generalization of the Cartesian product of two sets, but with additional mathematical structure.

2. How is a Hilbert space of direct products different from a regular direct product?

A regular direct product simply combines elements from two or more sets, while a Hilbert space of direct products also includes additional mathematical structure, such as inner products and norms. This allows for more advanced analysis and calculations to be done within the space.

3. What are some real-world applications of Hilbert spaces of direct products?

Hilbert spaces of direct products have applications in many areas of mathematics and science, including quantum mechanics, signal processing, and computer science. They are also used in engineering and economics for modeling and optimization problems.

4. How is orthogonality defined in a Hilbert space of direct products?

In a Hilbert space of direct products, two elements are considered orthogonal if their inner product is equal to zero. This definition is similar to the concept of perpendicularity in geometry, but it extends to any number of dimensions within the space.

5. Can a Hilbert space of direct products be infinite-dimensional?

Yes, a Hilbert space of direct products can be infinite-dimensional, meaning it contains an infinite number of elements. This is often the case in applications of functional analysis, where infinite-dimensional spaces are used to model complex systems or phenomena.

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