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5 changes: 2 additions & 3 deletions docs/src/blocktensors.md
Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@ BlockTensorMap <: AbstractBlockTensorMap <: AbstractTensorMap
SparseBlockTensorMap <: AbstractBlockTensorMap <: AbstractTensorMap
```

In particular, these structures hold the structural information as a `HomSpace` of `SumSpace`s, as defined in [`SumSpaces`](@ref), as well as the individual tensors that make up the block tensor.
In particular, these structures hold the structural information as a `HomSpace` of `SumSpace`s, as defined in [`SumSpaces`](@ref sec_sumspaces), as well as the individual tensors that make up the block tensor.
For `BlockTensorMap`, the list of tensors is dense, thus they are stored in an `Array{AbstractTensorMap,N}`, where `N` is the total number of indices of a tensor.
For `SparseBlockTensorMap`, this is not the case, and the list of tensors is stored in a `Dict{CartesianIndex{N},AbstractTensorMap}`.

Expand Down Expand Up @@ -41,8 +41,7 @@ Typically though, the most convenient way of obtaining a block tensor is by usin

```@repl blocktensors
using TensorKit, BlockTensorKit
using BlockTensorKit: ⊕
V = ℂ^1 ⊕ ℂ^2;
V = ℂ^1 ⊞ ℂ^2;
W = V * V → V;
t = rand(W)
eltype(t)
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2 changes: 1 addition & 1 deletion docs/src/sumspaces.md
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@@ -1,4 +1,4 @@
## Direct Sum Spaces
## [Direct Sum Spaces](@id sec_sumspaces)

The underlying concept that defines any array (or operator) that has some blocked structure is that of a direct sum of vector spaces.
These spaces are a natural extension of the `TensorKit` vector spaces, and you can think of them as a way to lazily concatenate multiple vector spaces into one.
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