Dream Scatter

What's this? I have no idea what you're trying to discuss here.

Grassmann.jl has its own experimental automatic differentiation built-in to the tensor algebra. It is not intended to be used with a separate AD package, but is its own experimental AD...

If you want to discuss my experimental AD design, we can do that in private. I no longer like to publicly discuss design details, these type of discussions with me...

Alright, I will email you to discuss this privately for now.

By the way, you can make all your examples above work just by using a `Signature` instead of an `Int` ```Julia julia> @basis S"++" (⟨++⟩, v, v₁, v₂, v₁₂) julia>...

Thanks for opening the issue, I cannot respond on the discourse right now and do not receive any pings from there either, i only saw your post because i checked...

As it so happens, I am working on another tensor product implementation (already before you raised this issue): ```Julia julia> using Grassmann#master julia> Chain(1,2)⊗Chain(3,4) (1v₁ + 2v₂)⊗(3v₁ + 4v₂) julia>...

This feature is already implemented in `Grassmann` you simply take the `DirectSum` of the two: ```Julia julia> Λ(ℝ3)⊕Λ(ℝ3) DirectSum.Basis{⟨××××××⟩,64}(v, v₁, v₂, v₃, v₄, v₅, v₆, v₁₂, v₁₃, v₁₄, v₁₅, v₁₆,...

@hammerfunctor another way of representing this object might be with nested geometric algebra, which is more easily possible to do without much additional effort, otherwise the change you are proposing...

Thank you for your question. This repository is currently mainly intended to give access to geometric algebra for researchers. I recall you @TsurHerman from discussions on the Julia discourse in...