Explicit and Implicit Matrix Notation Question

AI Thread Summary
The discussion centers on the relationship between Lorentz transformations and matrix notation in the context of the Minkowski metric. The equation g_{\sigma\rho}\Lambda^{\sigma}_{\mu}\Lambda^{\rho}_{\nu} = g_{\mu\nu} is equivalent to the matrix form \Lambda^{T}g\Lambda = g, where \Lambda is a Lorentz transformation matrix. The need to transpose \Lambda arises from the requirement of proper matrix multiplication, where rows of one matrix must align with columns of another. This ensures that the components are correctly multiplied to maintain the equality. Understanding this transposition is crucial for correctly applying matrix notation in tensor calculus.
Alex86
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Ok so this is a fairly stupid question I'm sure, but I'm not quite clear about the following:

Given a Lorentz transformation we require the following to hold:

g_{\sigma\rho}\Lambda^{\sigma}_{\mu}\Lambda^{\rho}_{\nu} = g_{\mu\nu}

In other notation this is written:

\Lambda^{T}g\Lambda = g

where \Lambda \in O(1,3) and g is the Minkowski metric.

The first use of tensor notation is fine, however I am unsure why in the second expression the first \Lambda is transposed?

Any help greatly appreciated,
Alex
 
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In the first sum over sigma, the "rows" of g are summed with the "rows" of lambda. In matrix multiplication, rows are summed with columns. If we write lambda and g as matrices and want to express the same product as a matrix multiplication, then in order for the correct components to be multiplied, we must transpose lambda.
 
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