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What you’re seeing is a basic acceptance-rejection method. $\Delta S$ generated in that way will be uniform in the ball of radius $\Delta S_{\text{max}}$ centered at the origin. Added I imagine you're doing some kind of optimization by random search, in which case the goal is to find a set of spins that extremize some objective function. The way it looks is ...

3

A dyadic product takes as input two vectors and outputs a second order tensor. This is what I know as a dyadic product, and a dyad is the term $\mathbf{a}\mathbf{b}$. A general second order tensor can be written as a linear combination of dyads. Commonly the symbol $\otimes$ is referred as the tensor product and it outputs higher-order tensors. I think that ...

2

The first equality you wrote is not correct, as noted by other users. However, what I think you want to know is why $(I:A)I = (I \otimes I)A$. You can show this just by using dyads properties. (B \otimes B) : A =(B_{ij}B_{kl} e_i \otimes e_j \otimes e_k \otimes e_l):(A_{mn} e_m \otimes e_n) = B_{ij}B_{kl} A_{mn} \delta_{km} \delta_{ln} e_i \otimes e_j = B_{...

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