Hello everyone I was trying to define the following ket state from a paper which has the following equation:
where \varphi is a complex valued function, the only way I was able to produce this is by the usage of the following code for a 3d case:
i = Index(N,"i") j = Index(N,"j") k = Index(N,"k") p = ITensor(i,j,k) for iv in eachindex(p) j = collect(Tuple(iv) .- N/2) p[iv] = phi(-eta .*j .- im *alpha) end
Is it possible to avoid the for loop and use the formalism of the ITensor to provide a TT-train approximation of such quantity?
For example if I use the tntorch python library I can use a lambda function to define it:
tn.cross(function=lambda x: x**2, tensors=[t]) # Compute the element-wise square of `t` using 5 TT-ranks