Why does the description of a composite system involve a tensor product?

In summary, the conversation discusses the use of tensor product in the description of composite systems, as well as its application in single particle systems. The tensor product is an abstract representation that combines two independent spaces, vectors, or tensors into one, while preserving their linearity. This allows for a more intuitive understanding of the relationship between different systems.
  • #1
prabin
1
0
Can anyone answer me that why the description of composite system involve tensor product ? Is there any way to realize this intuitively ?
 
Physics news on Phys.org
  • #2
The tensor product is not only used for composite systems, even for a single particle moving in space the 3d base kets are built as a product of 1d kets

$$\left|x,y,z\right\rangle =\left|x\right\rangle \otimes\left|y\right\rangle \otimes\left|z\right\rangle $$

As I see it, the tensor product is an abstract formalization of the following fact: Let ##\psi(x_{1,}x_{2})## be a two-particle wave function and ##{\phi_{n}(x)}## an orthogonal basis of functions for the one particle Hilbert space ##L^{2}## (say, the Hermite polynomials). Then you can write ##\psi(x_{1,}x_{2})## as a linear combination of functions of the form ##\phi_{n}(x_{1})\phi_{m}(x_{2})##. If we write this using an abstract vector, we are basically defining a tensor product.
 
  • Like
Likes PeroK and vanhees71
  • #3
The tensor product is the mathematical respresentation of two independent spaces, two independent unit vectors/kets or two independent tensors to be viewed as one. The context is linearity, and the tensor product preserves the linearity of both factors in such a way that the restriction to one of both (via the trace over the other) returns the original vector/ket/space/tensor.
 
Last edited:
  • Like
Likes vanhees71

FAQ: Why does the description of a composite system involve a tensor product?

What is a composite system in quantum mechanics?

A composite system in quantum mechanics refers to a system that is made up of two or more subsystems. Each subsystem can be described by its own Hilbert space, and the overall system's state is described by the combined Hilbert space of all subsystems.

Why do we use the tensor product to describe composite systems?

The tensor product is used to describe composite systems because it provides a mathematical framework that allows for the combination of the state spaces of individual subsystems into a single state space. This combined state space can then describe the entire composite system, capturing all possible states and interactions between the subsystems.

How does the tensor product preserve the properties of individual subsystems?

The tensor product preserves the properties of individual subsystems by maintaining their individual state spaces while also allowing for their combination. Each subsystem's state can be independently described, and the tensor product ensures that the combined state space includes all possible combinations of these states.

What is the significance of entanglement in the context of tensor products?

Entanglement is a phenomenon that arises in composite systems where the state of one subsystem cannot be described independently of the state of another subsystem. The tensor product framework allows for the representation of entangled states, which are crucial for understanding many quantum phenomena and for applications in quantum computing and quantum information theory.

Can you provide an example of a tensor product in a simple composite system?

Consider a composite system consisting of two qubits, each described by a 2-dimensional Hilbert space. The state of each qubit can be represented as a vector in its respective Hilbert space. The tensor product of these two state vectors forms a new vector in the 4-dimensional Hilbert space of the composite system. For example, if the first qubit is in state |0⟩ and the second qubit is in state |1⟩, the combined state of the system is described by the tensor product |0⟩ ⊗ |1⟩, which is a vector in the 4-dimensional space.

Similar threads

Replies
17
Views
2K
Replies
4
Views
874
Replies
6
Views
863
Replies
12
Views
2K
Replies
1
Views
1K
Replies
7
Views
1K
Replies
1
Views
1K
Back
Top