Graduate Special Relativity: A^μ_ν Differences Explained

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SUMMARY

The discussion clarifies the differences between the tensor notations A^{\mu}_{\nu}, A^{\mu}_{\hspace{0.2cm}\nu}, and A^{\mu}_{\nu}. The first two notations represent components of a second-rank tensor, while the last notation is discouraged due to unclear index placement. The ability to raise and lower indices using the metric components g_{\mu \nu} and g^{\mu \nu} is emphasized, particularly in symmetric tensors where A_{\mu \nu} = A_{\nu \mu}. Additionally, the relationship between tensors and matrices is discussed, noting that while tensors can be represented as matrices, the correspondence between indices and matrix rows/columns must be clearly defined.

PREREQUISITES
  • Understanding of second-rank tensors
  • Familiarity with metric components g_{\mu \nu} and g^{\mu \nu}
  • Knowledge of tensor symmetry
  • Basic concepts of matrix representation of tensors
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  • Study the properties of second-rank tensors in detail
  • Learn about the process of raising and lowering indices in tensor calculus
  • Explore the implications of tensor symmetry in physical applications
  • Investigate the representation of tensors as matrices in various bases
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LagrangeEuler
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Can someone explain me difference between
A^{\mu}_{\hspace{0.2cm} \nu}
A^{\hspace{0.2cm} \mu}_{\nu}
and
A^{\mu}_{\nu}?
 
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The first two expressions are correct and usually denote components of a 2nd-rank tensor. You can lower and raise indices with the metric components ##g_{\mu \nu}## and ##g^{\mu \nu}##, respectively, i.e., you have
$${A_{\nu}}^{\mu} = g_{\nu \sigma} g^{\mu \rho} {A^\sigma}_{\rho}.$$
The last expression should be avoided, because the horizontal placement of the indices is not indicated. It's ok if the tensor ##A## is symmetric, i.e., if ##A_{\mu \nu}=A_{\nu \mu}##, because (only!) then
$${A^{\mu}}_{\nu} = g^{\mu \rho} A_{\rho \nu} = g^{\mu \rho} A_{\nu \rho} ={A_{\nu}}^{\mu},$$
and the horizontal ordering is not important.
 
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vanhees71 said:
The first two expressions are correct and usually denote components of a 2nd-rank tensor. You can lower and raise indices with the metric components ##g_{\mu \nu}## and ##g^{\mu \nu}##, respectively, i.e., you have
$${A_{\nu}}^{\mu} = g_{\nu \sigma} g^{\mu \rho} {A^\sigma}_{\rho}.$$
The last expression should be avoided, because the horizontal placement of the indices is not indicated. It's ok if the tensor ##A## is symmetric, i.e., if ##A_{\mu \nu}=A_{\nu \mu}##, because (only!) then
$${A^{\mu}}_{\nu} = g^{\mu \rho} A_{\rho \nu} = g^{\mu \rho} A_{\nu \rho} ={A_{\nu}}^{\mu},$$
and the horizontal ordering is not important.
Is there some connection with matrices? For instance, if we have two indices.
A^{\mu}_{\hspace{0.2cm}\nu} what is the row and what is the column? And in this case
A^{\hspace{0.2cm}\mu}_{\nu} what is the row and what is the column?
 
Tensors are not matrices and matrices are not tensors. Tensors (of rank 2) may be represented by matrices in some basis but it is then up to you to define how indices correspond to rows and columns in a consistent manner.
 
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LagrangeEuler said:
And in this case A^{\hspace{0.2cm}\mu}_{\nu} what is the row and what is the column?
Typically when in a given basis you represent a tensor as a matrix the first index (on the left) is the row and the second the column. So in your example ##\nu## is the row and ##\mu## the column.
 
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I'd repeat Orodruin's caution. Any rank 2 tensor can be represented as a matrix (4×4 in relativity), and it's quite common to get metric tensors represented like this. But there isn't a way to notate upper and lower indices in that form, so it isn't clear what can be legally contracted with what and it's easy to end up writing a matrix equation that contracts over two lower indices. That's difficult to debug, so you do it at your own risk.
 
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