Rank-2 tensor: multiple definitions

In summary: A tensor is a 2-linear functions or vectors or one forms. In the case it is, for example, completely covariant, it will transform likeT'_{ij}=\frac{\partial x^{'a}}{\partial x^i}\frac{\partial x^{'b}}{\partial x^j}T_{ab}What is the link between the two definitions? Why should a spin-2 object be a tensor?The link between the two definitions is that a spin-2 object corresponds to a symmetric traceless rank-2 tensor. A rank-2 tensor is a 2-linear function or vectors or one forms that transforms like a
  • #1
fairy._.queen
47
0
Hi all!
In a paper they say that a certain quantity is a rank-2 tensor because it transforms like a spin-2 object under rotations, that is: if the basis vectors undergo a rotation of angle [itex]\phi[/itex], then this quantity, say A, transforms like
[itex]A\mapsto Ae^{i2\phi}[/itex]

As far as I knew, a rank-2 tensor is a 2-linear functions or vectors or one forms. In the case it is, for example, completely covariant, it will transform like
[itex]T'_{ij}=\frac{\partial x^{'a}}{\partial x^i}\frac{\partial x^{'b}}{\partial x^j}T_{ab}[/itex]

What is the link between the two definitions? Why should a spin-2 object be a tensor?

Thanks in advance!
 
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  • #2
A spin-2 object corresponds to a symmetric traceless rank-2 tensor.

In Cartesian coordinates the components are Txx, Txy = Tyx, Tyy, etc, with five independent components. To relate this to spin 2, we go to the spherical basis,

e+ = (ex + iey)/√2,
e0 = ez,
e- = (ex - iey)/√2.

The five independent components are then T++, T+0 = T0+, T00, T-0 = T0-, T--, and these transform under rotations like the |j=2, m> components of a spin 2 object.
 
  • #3
Thank you for your reply!
Why is the tensor corresponding to the spin-2 object traceless?
 
  • #4
fairy._.queen said:
Why is the tensor corresponding to the spin-2 object traceless?
To get a definite spin we need an object that is irreducible. But in general a symmetric tensor can be reduced. That is, it can be split into parts that behave differently under rotations.

The trace T = ∑Tii is a scalar, meaning it's invariant under 3-D rotations. So to look at how the rest of Tab behaves, we split the trace off and consider what's left - the traceless part, which is Tab - δabT/3.

This leaves us with five independent components rather than six. And under 3-D rotations these five components transform only into linear combinations of themselves - the trace is no longer involved. In the spherical basis the five components correspond to the five values of m allowed for spin 2, namely T++ is m = 2, T+0 is m = 1, T00 is m = 0, etc. Under a rotation about the z-axis, T++ ~ T++ e2iφ, and so on.
 
  • #5
Thank you again for replying!

There is a thing I don't get: if [itex]T_{00}\mapsto T_{00}[/itex] under rotations, doesn't that mean it is a scalar, rather than a component of a spin-2 object?

A spin-2 object corresponds to a symmetric traceless rank-2 tensor.
From what you said in your last post, it seems to me that a spin-2 object corresponds to the [itex]T_{++}[/itex] component of a rank-2 tensor... where am I wrong?
 
  • #6
fairy._.queen said:
There is a thing I don't get: if [itex]T_{00}\mapsto T_{00}[/itex] under rotations, doesn't that mean it is a scalar, rather than a component of a spin-2 object?
This happens only under one particular rotation - the rotation about the z-axis. Under other rotations, the five components get mixed together.
fairy._.queen said:
From what you said in your last post, it seems to me that a spin-2 object corresponds to the [itex]T_{++}[/itex] component of a rank-2 tensor... where am I wrong?
T++ is only the state in which the spin is spin-up (m = 2). Of course the spin of a spin-2 object can have any other orientation besides.
 
  • #7
I'm afraid I didn't really understand how an object of spin [itex]s[/itex] transforms, then.
Do the [itex]m=1[/itex] component of a spin-1 and spin-2 objects both transform as
[itex]C\mapsto Ce^{i\phi}[/itex]?

I thought all the components of a spin-2 object would transform as
[itex]C\mapsto Ce^{i2\phi}[/itex]

Sorry if the question is trivial!
 
  • #8
fairy._.queen said:
I thought all the components of a spin-2 object would transform as
[itex]C\mapsto Ce^{i2\phi}[/itex]
You're thinking of "spin" as meaning the spin projection, m = 2. A spin-2 object meaning total spin, j = 2 can be in different states |j=2, m> with any spin projection m between ±2. Under a rotation about the z-axis, each of these five states does something different:

|j=2, m=+2> → |j=2, m=+2> e2iφ
|j=2, m=+1> → |j=2, m=+1> e
|j=2, m=0> → |j=2, m=0>
|j=2, m=-1> → |j=2, m=-1> e-iφ
|j=2, m=-1> → |j=2, m=-2> e-2iφ

And under rotations about some other axis, the states will mix together. But forgive me, for spin 2 it gets rather messy, so let me do it instead for spin 1, where the three spin-1 states transform like the three components of a vector.

Under a rotation through an angle θ about the y-axis, the Cartesian components of a vector or spin-1 object do this:

Vx → Vx cos θ - Vz sin θ
Vy → Vy
Vz → Vz cos θ + Vx sin θ [Eq 1]

Now replace the Cartesian components with the spherical components (see way up above). I'll just write out one of them, [Eq 1]:

V0 → V0 cos θ + (V+ + V-)/√2 sin θ

So there they are mixing together as promised.
 
  • #9
Thank you for your thorough reply!
In the paper I am reading, the anisotropies of the CMB which are due to a Bianchi background geometry (not the usual statistical perturbations to the FRW Universe) can be split in 5 according to their behaviour under rotation around some preferred axis which reflects some symmetry. 2 of them are called rank-2 tensors, because they transform with an [itex]m=2[/itex] rule, another 2 are called vectors, because they transform with an [itex]m=1[/itex] rule and 1 is called scalar, [itex]m=0[/itex].
From what you say, it seems to me that, strictly speaking, you shouldn't say that the [itex]m=0,1[/itex] parts of the perturbation are scalars or vectors, in that they could be the [itex]m=0,1[/itex] components of a spin-2 object. If you confirm that this terminology is not 100% correct, then I think I got the point.
 

FAQ: Rank-2 tensor: multiple definitions

What is a Rank-2 Tensor?

A Rank-2 tensor is a mathematical object that represents a multilinear mapping between two vector spaces. It is a generalization of a matrix, which represents a linear mapping between two vector spaces.

What are some common definitions of a Rank-2 Tensor?

There are multiple definitions of a Rank-2 tensor, but some common ones include: a matrix of numbers, a linear transformation between two vector spaces, a bilinear form, and a second-order tensor in the context of continuum mechanics.

How is a Rank-2 Tensor different from a Rank-1 Tensor?

A Rank-1 tensor, also known as a vector, represents a linear mapping between a vector space and its dual space. It has only one index and can be thought of as a list of numbers. In contrast, a Rank-2 tensor has two indices and represents a multilinear mapping between two vector spaces.

What are the components of a Rank-2 Tensor?

The components of a Rank-2 tensor depend on the chosen basis for the vector spaces it maps between. For example, in three-dimensional space, a Rank-2 tensor will have 9 components in the standard basis, but if a different basis is chosen, the components will be different.

Where are Rank-2 Tensors used in science?

Rank-2 tensors are used in various fields of science, including mathematics, physics, engineering, and computer science. They are particularly important in continuum mechanics, where they are used to describe physical quantities such as stress, strain, and elasticity. They are also used in machine learning and data analysis to model and manipulate multivariate data.

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