- #1
pitaly
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- TL;DR Summary
- Need some clarifications on tensor calculus
I've started reading up on tensors. Since this lies well outside my usual area, I need some clarifications on some tensor calculus issues.
Let ##A## be a tensor of order ##j > 1##. Suppose that the tensor is cubical, i.e., every mode is of the same size. So for example, if ##A## is of order 3 then ##A \in R^{n \times n \times n}##.
Further assume that ##A## is symmetric (sometimes called supersymmetric), i.e., it is invariant under permutation of indices. For example, if the order is 3 then ##A_{ijk} = A_{ikj} = A_{jik} = A_{jki} = A_{kij} = A_{kij}##.
We say that a tensor is positive semidefinite if ##x \cdot A \cdot x \geq 0## for all vectors ##x \neq 0##. So for example, if ##A## is of order 2, we have a standard quadratic form and if ##A## is positive semidefinite then ##x \cdot A \cdot x \geq 0##.
Now, to my two questions:
1) Is there any clean notation for tensor differentiation? If ##A## is of order 2 then the gradient of ##x \cdot A \cdot x## with respect to ##x## is ##2 x \cdot A##. How do I write the gradient of ##x \cdot A \cdot x## with respect to ##x## when ##A## is a tensor of any order ##j>2##?
2) Consider a tensor ##A## of order 2 and the quadratic form ##(x-y) \cdot A \cdot (x-y)## for any vectors ##x,y##. If ##A## is positive semidefinite then ##x \cdot A \cdot x - y \cdot A \cdot y \geq 2y \cdot A \cdot (x-y) ##. Does there exist any analogous inequality for tensors of any order ##j>2##, where the tensor ##A## is positive semidefinite?
Any help on this is highly appreciated!
Let ##A## be a tensor of order ##j > 1##. Suppose that the tensor is cubical, i.e., every mode is of the same size. So for example, if ##A## is of order 3 then ##A \in R^{n \times n \times n}##.
Further assume that ##A## is symmetric (sometimes called supersymmetric), i.e., it is invariant under permutation of indices. For example, if the order is 3 then ##A_{ijk} = A_{ikj} = A_{jik} = A_{jki} = A_{kij} = A_{kij}##.
We say that a tensor is positive semidefinite if ##x \cdot A \cdot x \geq 0## for all vectors ##x \neq 0##. So for example, if ##A## is of order 2, we have a standard quadratic form and if ##A## is positive semidefinite then ##x \cdot A \cdot x \geq 0##.
Now, to my two questions:
1) Is there any clean notation for tensor differentiation? If ##A## is of order 2 then the gradient of ##x \cdot A \cdot x## with respect to ##x## is ##2 x \cdot A##. How do I write the gradient of ##x \cdot A \cdot x## with respect to ##x## when ##A## is a tensor of any order ##j>2##?
2) Consider a tensor ##A## of order 2 and the quadratic form ##(x-y) \cdot A \cdot (x-y)## for any vectors ##x,y##. If ##A## is positive semidefinite then ##x \cdot A \cdot x - y \cdot A \cdot y \geq 2y \cdot A \cdot (x-y) ##. Does there exist any analogous inequality for tensors of any order ##j>2##, where the tensor ##A## is positive semidefinite?
Any help on this is highly appreciated!