Docfixes and v0.14.10 bump

.github/workflows/PR_comment.yml

@@ -0,0 +1,17 @@
+name: Docs preview comment
+on:
+  pull_request:
+    types: [labeled]
+
+permissions:
+  pull-requests: write
+jobs:
+  pr_comment:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Create PR comment
+        if: github.event_name == 'pull_request' && github.repository == github.event.pull_request.head.repo.full_name && github.event.label.name == 'documentation'
+        uses: thollander/actions-comment-pull-request@v3
+        with:
+          message: 'After the build completes, the updated documentation will be available [here](https://quantumkithub.github.io/TensorKit.jl/previews/PR${{ github.event.number }}/)'
+          comment-tag: 'preview-doc'

CITATION.cff

@@ -8,10 +8,10 @@ authors:
   given-names: "Jutho"
   orcid: "https://orcid.org/0000-0002-0858-291X"
 title: "TensorKit.jl"
-version: "0.14.9"
+version: "0.14.10"
 doi: "10.5281/zenodo.8421339"
 date-released: "2025-07-18"
-url: "https://github.com/Jutho/TensorKit.jl"
+url: "https://github.com/QuantumKitHub/TensorKit.jl"
 preferred-citation:
   type: article
   authors:

Project.toml

@@ -1,7 +1,7 @@
 name = "TensorKit"
 uuid = "07d1fe3e-3e46-537d-9eac-e9e13d0d4cec"
 authors = ["Jutho Haegeman"]
-version = "0.14.9"
+version = "0.14.10"
 
 [deps]
 LRUCache = "8ac3fa9e-de4c-5943-b1dc-09c6b5f20637"

README.md

@@ -32,7 +32,7 @@ A Julia package for large-scale tensor computations, with a hint of category the
 [ci-img]: https://github.com/QuantumKitHub/TensorKit.jl/actions/workflows/CI.yml/badge.svg
 [ci-url]: https://github.com/QuantumKitHub/TensorKit.jl/actions/workflows/CI.yml
 
-[codecov-img]: https://codecov.io/gh/QuantumKitHub/TensorKit.jl/branch/master/graph/badge.svg
+[codecov-img]: https://codecov.io/gh/QuantumKitHub/TensorKit.jl/branch/main/graph/badge.svg
 [codecov-url]: https://codecov.io/gh/QuantumKitHub/TensorKit.jl
 
 [aqua-img]: https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg

benchmark/README.md

@@ -12,11 +12,11 @@ To do this, you can use the `--modules` flag to specify which modules to run.
 Alternatively, you can use the `TensorKitBenchmarks` module directly, which is designed after `BaseBenchmarks` to allow for conditional loading of the benchmarks.
 
 For a more streamlined CLI experience, you can use [`AirspeedVelocity.jl`](https://github.com/MilesCranmer/AirspeedVelocity.jl) to run the benchmarks.
-The following command will run the benchmarks and compare with the current master branch:
+The following command will run the benchmarks and compare with the current main branch:
 
 ```bash
 benchpkg TensorKit \
-    --rev=dirty,master \
+    --rev=dirty,main \
     -o benchmark/results/ \
     -exeflags="--threads=4"
 ```
@@ -25,7 +25,7 @@ To compare with previous results, the following command can be used:
 
 ```bash
 benchpkgtable TensorKit \
-    --rev=dirty,master \
+    --rev=dirty,main \
     -i benchmark/results/ \
     -o benchmark/results/ \
 ```

docs/Project.toml

@@ -1,6 +1,7 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+TensorKit = "07d1fe3e-3e46-537d-9eac-e9e13d0d4cec"
 TensorKitSectors = "13a9c161-d5da-41f0-bcbd-e1a08ae0647f"
 
 [compat]

docs/make.jl

@@ -17,4 +17,4 @@ makedocs(; modules=[TensorKit, TensorKitSectors],
          pages=pages,
          pagesonly=true)
 
-deploydocs(; repo="github.com/Jutho/TensorKit.jl.git", push_preview=true)
+deploydocs(; repo="github.com/QuantumKitHub/TensorKit.jl.git", push_preview=true)

docs/src/index.md

@@ -14,7 +14,7 @@ actually a specific case of the type [`TensorMap`](@ref)) and defines for these
 number of vector space operations (scalar multiplication, addition, norms and inner
 products), index operations (permutations) and linear algebra operations (multiplication,
 factorizations). Finally, tensor contractions can be performed using the `@tensor` macro
-from [TensorOperations.jl](https://github.com/Jutho/TensorOperations.jl).
+from [TensorOperations.jl](https://github.com/QuantumKitHub/TensorOperations.jl).
 
 Currently, most effort is oriented towards tensors as they appear in the context of quantum
 many body physics and in particular the field of tensor networks. Such tensors often have

docs/src/man/spaces.md

@@ -57,7 +57,7 @@ to introduce some syntactic sugar without committing type piracy. In particular,
 ```@repl tensorkit
 3 ∈ ℝ
 5.0 ∈ ℂ
-5.0+1.0*im ∈ ℝ
+5.0 + 1.0 * im ∈ ℝ
 Float64 ⊆ ℝ
 ComplexF64 ⊆ ℂ
 ℝ ⊆ ℂ
@@ -81,17 +81,17 @@ objects of the same concrete type (i.e. with the same type parameters in case of
 parametric type). In particular, every `ElementarySpace` should implement the following
 methods
 
-*   `dim(::ElementarySpace) -> ::Int` returns the dimension of the space as an `Int`
+*   `dim(::ElementarySpace)` returns the dimension of the space
 
 *   `dual(::S) where {S<:ElementarySpace} -> ::S` returns the
     [dual space](http://en.wikipedia.org/wiki/Dual_space) `dual(V)`, using an instance of
     the same concrete type (i.e. not via type parameters); this should satisfy
-    `dual(dual(V))==V`
+    `dual(dual(V)) == V`
 
 *   `conj(::S) where {S<:ElementarySpace} -> ::S` returns the
     [complex conjugate space](http://en.wikipedia.org/wiki/Complex_conjugate_vector_space)
     `conj(V)`, using an instance of the same concrete type (i.e. not via type parameters);
-    this should satisfy `conj(conj(V))==V` and we automatically have
+    this should satisfy `conj(conj(V)) == V` and we automatically have
     `conj(V::ElementarySpace{ℝ}) = V`.
 
 For convenience, the dual of a space `V` can also be obtained as `V'`.
@@ -186,15 +186,15 @@ struct ProductSpace{S<:ElementarySpace, N} <: CompositeSpace{S}
 end
 ```
 Given some `V1::S`, `V2::S`, `V3::S` of the same type `S<:ElementarySpace`, we can easily
-construct `ProductSpace{S,3}((V1,V2,V3))` as `ProductSpace(V1,V2,V3)` or using
+construct `ProductSpace{S,3}((V1, V2, V3))` as `ProductSpace(V1, V2, V3)` or using
 `V1 ⊗ V2 ⊗ V3`, where `⊗` is simply obtained by typing `\otimes`+TAB. In fact, for
 convenience, also the regular multiplication operator `*` acts as tensor product between
 vector spaces, and as a consequence so does raising a vector space to a positive integer
 power, i.e.
 ```@repl tensorkit
 V1 = ℂ^2
 V2 = ℂ^3
-V1 ⊗ V2 ⊗ V1' == V1 * V2 * V1' == ProductSpace(V1,V2,V1') == ProductSpace(V1,V2) ⊗ V1'
+V1 ⊗ V2 ⊗ V1' == V1 * V2 * V1' == ProductSpace(V1, V2, V1') == ProductSpace(V1, V2) ⊗ V1'
 V1^3
 dim(V1 ⊗ V2)
 dims(V1 ⊗ V2)