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Co-authored-by: Jutho <[email protected]>

Author: lkdvos

docs/src/man/sectors.md

@@ -28,8 +28,8 @@ there is a canonical order of the sectors, so that the vector space ``V`` is
 completely specified by the values of ``n_a``.
 
 The gain in efficiency (both in memory occupation and computation time) obtained from using
-(technically: equivariant) tensor maps is that, by Schur's lemma, they are block-diagonal in
-the basis of coupled sectors. To exploit this block-diagonal form, it is however essential
+(technically: equivariant) tensor maps is that, by Schur's lemma, they are block diagonal in
+the basis of coupled sectors. To exploit this block diagonal form, it is however essential
 that we know the basis transformation from the individual (uncoupled) sectors appearing in
 the tensor product form of the domain and codomain, to the totally coupled sectors that
 label the different blocks. We refer to the latter as block sectors. The transformation from

docs/src/man/tensors.md

@@ -764,7 +764,7 @@ braid(t::AbstractTensorMap{T,S,N₁,N₂}, (p1, p2)::Index2Tuple{N₁′,N₂′
 and
 
 ```julia
-permute(t::AbstractTensorMap{T,S,N₁,N₂}(p1, p2)::Index2Tuple{N₁′,N₂′}; copy = false)
+permute(t::AbstractTensorMap{T,S,N₁,N₂}, (p1, p2)::Index2Tuple{N₁′,N₂′}; copy = false)
 ```
 
 both of which return an instance of `AbstractTensorMap{T,S,N₁′,N₂′}`.
@@ -873,7 +873,7 @@ A final operation that one might expect in this section is to fuse or join indic
 inverse, to split a given index into two or more indices. For a plain tensor (i.e. with
 `sectortype(t) == Trivial`) amount to the equivalent of `reshape` on the multidimensional
 data. However, this represents only one possibility, as there is no canonically unique way
-to embed the tensor product of two spaces `V1 ⊗ V₂` in a new space `V = fuse(V1⊗V₂)`. Such a
+to embed the tensor product of two spaces `V1 ⊗ V2` in a new space `V = fuse(V1 ⊗ V2)`. Such a
 mapping can always be accompagnied by a basis transform. However, one particular choice is
 created by the function `isomorphism`, or for `EuclideanProduct` spaces, `unitary`.
 Hence, we can join or fuse two indices of a tensor by first constructing

docs/src/man/tutorial.md

@@ -302,11 +302,11 @@ More power becomes visible when involving symmetries. With symmetries, we imply
 is some symmetry action defined on every vector space associated with each of the indices
 of a `TensorMap`, and the `TensorMap` is then required to be equivariant, i.e. it acts as
 an intertwiner between the tensor product representation on the domain and that on the
-codomain. By Schur's lemma, this means that the tensor is block-diagonal in some basis
+codomain. By Schur's lemma, this means that the tensor is block diagonal in some basis
 corresponding to the irreducible representations that can be coupled to by combining the
 different representations on the different spaces in the domain or codomain. For Abelian
 symmetries, this does not require a basis change and it just imposes that the tensor has
-some block-sparsity. Let's clarify all of this with some examples.
+some block sparsity. Let's clarify all of this with some examples.
 
 We start with a simple ``ℤ₂`` symmetry: