professor said:
well I am 15 now :P 16 in march :)
also- a tensor is a triple vector? - or a three dimensional vector (triple probably not the right word)
professor said:
well I am 15 now :P 16 in march :)
also- a tensor is a triple vector? - or a three dimensional vector (triple probably not the right word)
A tensor can have an arbitrarily high rank. A vector is a rank 1 tensor, and a matrix is a specific form of a rnak 2 tensor.
The Riemann tensor is a rank 4 tensor, which is the highest rank tensor used in relativity.
One of the best defintions of a tensor is this:
a rank M+N tensor is a linear map from N vectors and M dual-vectors to a scalar. Linearity is applied to each slot in the tensor individually.
see for instance
http://math.ucr.edu/home/baez/gr/outline2.html
Of course, you have to understand what a dual vector is to make use of or appreciate this simple definition, that's what my other post was about.
Suppose you have two vectors - their dot product, A . B, is a rank 2 tensor by defintion. This tensor is usually called the "metric" tensor. It is symmetric because A . B = B . A, i.e. the dot product commutes.
It turns out, by pure logic and the defintion of vectors and dual vectors, that the metric tensor as defined in this way also defines a map from vectors to dual vectors.
I.e. given a map from 2 vectors to a scalar, we can determine a map from
a vector to a (map of a vector to a scalar). This can be done in two ways - if we take A . B, A defines the vector, and the map of (B to a scalar) which is equal to (A . B) defines the dual vector. Or we can let B define the vector, and the map of (A to a scalar) defines the dual. Because of symmetry, the order in which we take the vectors doesn't matter.
This means that the metric tensor can be used to convert vectors into their duals, and vica-versa - or to put it another way, the dot product relation of a vector space which maps two vectors to a scalar defines, by necessity, the mapping of a vector to it's dual.
You may be used to seeing dot products as some vector X = (x,y,z) being
X dot X = x^2 + y^2 + z^2
this works in cartesian coordinates, but not in generalized coordinates (for example, r, theta, phi).
With a non-diagonal metric tensor, the dot product can be expressed in any arbitrary coordinate system. Thus every coordinate system has its own unique defintion of the dot product (metic tensor), and every such defintion of the metric tensor defines a unique relationship between vectors and their duals.
This may seem complicated at first, but it really isn't.