Dismiss Notice
Join Physics Forums Today!
The friendliest, high quality science and math community on the planet! Everyone who loves science is here!

Homework Help: Question on tensor notation

  1. Apr 21, 2010 #1
    1. The problem statement, all variables and given/known data
    Not a specific problem; I'm trying to understand what the notation means; I'm using primarily Griffiths, Marion and Jackson textbooks.

    The notation for a matrix, with the superscript row index and subscript column index I understand. For the EM field tensor, Griffiths has both indices superscripted, and Marion has both subscripted. My questions are:
    1. What is the difference?
    2. What is the meaning when they are both on the same level? I assume one is rows and one is columns - but which is which?
    3. When you take a derivative of the tensor, what exactly are you doing in terms of the indices of the tensor and the index of the variable of integration?

    2. Relevant equations

    3. The attempt at a solution I've searched Boas, Arfken & Webber, Wikipedia, and some other web sites to no avail.
  2. jcsd
  3. Apr 21, 2010 #2


    User Avatar
    Homework Helper
    Gold Member

    The difference is in how the components of the tensor transform, under any given coordinate transformation. The usual convention is that tensors with lowered (subscript) indices are covariant and tensors with raised (superscript) indices are contravariant. Tensors with both lowered and raised indices are called mixed tensors.

    Tensors are not just matrices. In the case of second rank tensors (whether they are covariant, contravariant or mixed), you can represent them by a matrix by defining certain basis vectors to be represented as row vectors, and others as columns. Which is which depends on how you define your representation.

    Taking the derivative of a tensor with respect to any given variable simply means that you take the derivative of each component of the tensor. In the case of the field tensors you work with in electrodynamics, there are 16 components for each second rank tensor (matrix) and 4 components for each 1st rank tensor (vector).
Share this great discussion with others via Reddit, Google+, Twitter, or Facebook