Merge remote-tracking branch 'upstream/main'

Project.toml

@@ -1,7 +1,7 @@
 name = "ITensorNetworks"
 uuid = "2919e153-833c-4bdc-8836-1ea460a35fc7"
 authors = ["Matthew Fishman <[email protected]> and contributors"]
-version = "0.4.1"
+version = "0.4.2"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -51,7 +51,7 @@ DocStringExtensions = "0.8, 0.9"
 EinExprs = "0.6.4"
 Graphs = "1.8"
 GraphsFlows = "0.1.1"
-ITensors = "0.3.23"
+ITensors = "0.3.58"
 IsApprox = "0.1"
 IterTools = "1.4.0"
 KrylovKit = "0.6.0"

README.md

@@ -10,10 +10,14 @@
 > In short, use this package with caution, and don't expect the interface to be stable
 > or for us to clearly announce parts of the code we are changing.
 
+
+
 # ITensorNetworks
 
 A package to provide general network data structures and tools to use with ITensors.jl.
 
+
+
 ## Installation
 
 You can install this package through the Julia package manager:
@@ -99,13 +103,13 @@ and 4 edge(s):
 
 with vertex data:
 4-element Dictionary{Tuple{Int64, Int64}, Any}
- (1, 1) │ ((dim=2|id=74|"1×1,2×1"), (dim=2|id=723|"1×1,1×2"))
- (2, 1) │ ((dim=2|id=74|"1×1,2×1"), (dim=2|id=823|"2×1,2×2"))
- (1, 2) │ ((dim=2|id=723|"1×1,1×2"), (dim=2|id=712|"1×2,2×2"))
- (2, 2) │ ((dim=2|id=823|"2×1,2×2"), (dim=2|id=712|"1×2,2×2"))
+ (1, 1) │ ((dim=2|id=712|"1×1,2×1"), (dim=2|id=598|"1×1,1×2"))
+ (2, 1) │ ((dim=2|id=712|"1×1,2×1"), (dim=2|id=457|"2×1,2×2"))
+ (1, 2) │ ((dim=2|id=598|"1×1,1×2"), (dim=2|id=683|"1×2,2×2"))
+ (2, 2) │ ((dim=2|id=457|"2×1,2×2"), (dim=2|id=683|"1×2,2×2"))
 
 julia> tn[1, 1]
-ITensor ord=2 (dim=2|id=74|"1×1,2×1") (dim=2|id=723|"1×1,1×2")
+ITensor ord=2 (dim=2|id=712|"1×1,2×1") (dim=2|id=598|"1×1,1×2")
 NDTensors.EmptyStorage{NDTensors.EmptyNumber, NDTensors.Dense{NDTensors.EmptyNumber, Vector{NDTensors.EmptyNumber}}}
 
 julia> neighbors(tn, (1, 1))
@@ -129,8 +133,8 @@ and 1 edge(s):
 
 with vertex data:
 2-element Dictionary{Tuple{Int64, Int64}, Any}
- (1, 1) │ ((dim=2|id=74|"1×1,2×1"), (dim=2|id=723|"1×1,1×2"))
- (1, 2) │ ((dim=2|id=723|"1×1,1×2"), (dim=2|id=712|"1×2,2×2"))
+ (1, 1) │ ((dim=2|id=712|"1×1,2×1"), (dim=2|id=598|"1×1,1×2"))
+ (1, 2) │ ((dim=2|id=598|"1×1,1×2"), (dim=2|id=683|"1×2,2×2"))
 
 julia> tn_2 = subgraph(v -> v[1] == 2, tn)
 ITensorNetwork{Tuple{Int64, Int64}} with 2 vertices:
@@ -143,8 +147,8 @@ and 1 edge(s):
 
 with vertex data:
 2-element Dictionary{Tuple{Int64, Int64}, Any}
- (2, 1) │ ((dim=2|id=74|"1×1,2×1"), (dim=2|id=823|"2×1,2×2"))
- (2, 2) │ ((dim=2|id=823|"2×1,2×2"), (dim=2|id=712|"1×2,2×2"))
+ (2, 1) │ ((dim=2|id=712|"1×1,2×1"), (dim=2|id=457|"2×1,2×2"))
+ (2, 2) │ ((dim=2|id=457|"2×1,2×2"), (dim=2|id=683|"1×2,2×2"))
 ```
 
 
@@ -166,9 +170,9 @@ and 2 edge(s):
 
 with vertex data:
 3-element Dictionary{Int64, Vector{Index}}
- 1 │ Index[(dim=2|id=598|"S=1/2,Site,n=1")]
- 2 │ Index[(dim=2|id=457|"S=1/2,Site,n=2")]
- 3 │ Index[(dim=2|id=683|"S=1/2,Site,n=3")]
+ 1 │ Index[(dim=2|id=830|"S=1/2,Site,n=1")]
+ 2 │ Index[(dim=2|id=369|"S=1/2,Site,n=2")]
+ 3 │ Index[(dim=2|id=558|"S=1/2,Site,n=3")]
 
 and edge data:
 0-element Dictionary{NamedEdge{Int64}, Vector{Index}}
@@ -186,9 +190,9 @@ and 2 edge(s):
 
 with vertex data:
 3-element Dictionary{Int64, Any}
- 1 │ ((dim=2|id=598|"S=1/2,Site,n=1"), (dim=2|id=123|"1,2"))
- 2 │ ((dim=2|id=457|"S=1/2,Site,n=2"), (dim=2|id=123|"1,2"), (dim=2|id=656|"2,3…
- 3 │ ((dim=2|id=683|"S=1/2,Site,n=3"), (dim=2|id=656|"2,3"))
+ 1 │ ((dim=2|id=830|"S=1/2,Site,n=1"), (dim=2|id=186|"1,2"))
+ 2 │ ((dim=2|id=369|"S=1/2,Site,n=2"), (dim=2|id=186|"1,2"), (dim=2|id=430|"2,3…
+ 3 │ ((dim=2|id=558|"S=1/2,Site,n=3"), (dim=2|id=430|"2,3"))
 
 julia> tn2 = ITensorNetwork(s; link_space=2)
 ITensorNetwork{Int64} with 3 vertices:
@@ -203,9 +207,9 @@ and 2 edge(s):
 
 with vertex data:
 3-element Dictionary{Int64, Any}
- 1 │ ((dim=2|id=598|"S=1/2,Site,n=1"), (dim=2|id=382|"1,2"))
- 2 │ ((dim=2|id=457|"S=1/2,Site,n=2"), (dim=2|id=382|"1,2"), (dim=2|id=190|"2,3…
- 3 │ ((dim=2|id=683|"S=1/2,Site,n=3"), (dim=2|id=190|"2,3"))
+ 1 │ ((dim=2|id=830|"S=1/2,Site,n=1"), (dim=2|id=994|"1,2"))
+ 2 │ ((dim=2|id=369|"S=1/2,Site,n=2"), (dim=2|id=994|"1,2"), (dim=2|id=978|"2,3…
+ 3 │ ((dim=2|id=558|"S=1/2,Site,n=3"), (dim=2|id=978|"2,3"))
 
 julia> @visualize tn1;
     ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ 

examples/README.jl

@@ -1,3 +1,15 @@
+#' > [!WARNING]
+#' > This is a pre-release software. There are no guarantees that functionality won't break
+#' > from version to version, though we will try our best to indicate breaking changes
+#' > following [semantic versioning](https://semver.org/) (semver) by bumping the minor
+#' > version of the package. We are biasing heavily towards "moving fast and breaking things"
+#' > during this stage of development, which will allow us to more quickly develop the package
+#' > and bring it to a point where we have enough features and are happy enough with the external
+#' > interface to officially release it for general public use.
+#' >
+#' > In short, use this package with caution, and don't expect the interface to be stable
+#' > or for us to clearly announce parts of the code we are changing.
+
 #' # ITensorNetworks
 #'
 #' A package to provide general network data structures and tools to use with ITensors.jl.

src/abstractitensornetwork.jl

@@ -733,6 +733,15 @@ end
 # Common index checking
 # 
 
+function hascommoninds(
+  ::typeof(siteinds), A::AbstractITensorNetwork{V}, B::AbstractITensorNetwork{V}
+) where {V}
+  for v in vertices(A)
+    !hascommoninds(siteinds(A, v), siteinds(B, v)) && return false
+  end
+  return true
+end
+
 function hassameinds(
   ::typeof(siteinds), A::AbstractITensorNetwork{V}, B::AbstractITensorNetwork{V}
 ) where {V}

src/imports.jl

@@ -82,6 +82,8 @@ import ITensors:
   dag,
   # permute
   permute,
+  #commoninds
+  hascommoninds,
   # linkdims
   linkdim,
   linkdims,

src/solvers/alternating_update/alternating_update.jl

@@ -94,8 +94,6 @@ function alternating_update(
 end
 
 function alternating_update(operator::AbstractTTN, init_state::AbstractTTN; kwargs...)
-  check_hascommoninds(siteinds, operator, init_state)
-  check_hascommoninds(siteinds, operator, init_state')
   # Permute the indices to have a better memory layout
   # and minimize permutations
   operator = ITensors.permute(operator, (linkind, siteinds, linkind))
@@ -106,8 +104,6 @@ end
 function alternating_update(
   operator::AbstractTTN, init_state::AbstractTTN, sweep_plans; kwargs...
 )
-  check_hascommoninds(siteinds, operator, init_state)
-  check_hascommoninds(siteinds, operator, init_state')
   # Permute the indices to have a better memory layout
   # and minimize permutations
   operator = ITensors.permute(operator, (linkind, siteinds, linkind))
@@ -138,10 +134,6 @@ Returns:
 function alternating_update(
   operators::Vector{<:AbstractTTN}, init_state::AbstractTTN; kwargs...
 )
-  for operator in operators
-    check_hascommoninds(siteinds, operator, init_state)
-    check_hascommoninds(siteinds, operator, init_state')
-  end
   operators .= ITensors.permute.(operators, Ref((linkind, siteinds, linkind)))
   projected_operators = ProjTTNSum(operators)
   return alternating_update(projected_operators, init_state; kwargs...)
@@ -150,10 +142,6 @@ end
 function alternating_update(
   operators::Vector{<:AbstractTTN}, init_state::AbstractTTN, sweep_plans; kwargs...
 )
-  for operator in operators
-    check_hascommoninds(siteinds, operator, init_state)
-    check_hascommoninds(siteinds, operator, init_state')
-  end
   operators .= ITensors.permute.(operators, Ref((linkind, siteinds, linkind)))
   projected_operators = ProjTTNSum(operators)
   return alternating_update(projected_operators, init_state, sweep_plans; kwargs...)

src/solvers/contract.jl

@@ -27,8 +27,6 @@ function sum_contract(
     return typeof(tn2)([res])
   end
 
-  # check_hascommoninds(siteinds, tn1, tn2)
-
   # In case `tn1` and `tn2` have the same internal indices
   operator = ProjOuterProdTTN{vertextype(first(tn1s))}[]
   for (tn1, tn2) in zip(tn1s, tn2s)

src/treetensornetworks/abstracttreetensornetwork.jl

@@ -242,7 +242,6 @@ function loginner(
   end
   ψ1dag = sim(dag(ψ1); sites=[])
   traversal_order = reverse(post_order_dfs_vertices(ψ1, root_vertex))
-  check_hascommoninds(siteinds, ψ1dag, ψ2)
 
   O = ψ1dag[root_vertex] * ψ2[root_vertex]
 
@@ -370,8 +369,6 @@ function inner(
   y::AbstractTTN, A::AbstractTTN, x::AbstractTTN; root_vertex=default_root_vertex(x, A, y)
 )
   traversal_order = reverse(post_order_dfs_vertices(x, root_vertex))
-  check_hascommoninds(siteinds, A, x)
-  check_hascommoninds(siteinds, A, y)
   ydag = sim(dag(y); sites=[])
   x = sim(x; sites=[])
   O = ydag[root_vertex] * A[root_vertex] * x[root_vertex]
@@ -397,15 +394,6 @@ function inner(
       ),
     )
   end
-  check_hascommoninds(siteinds, A, x)
-  check_hascommoninds(siteinds, B, y)
-  for v in vertices(B)
-    !hascommoninds(
-      uniqueinds(siteinds(A, v), siteinds(x, v)), uniqueinds(siteinds(B, v), siteinds(y, v))
-    ) && error(
-      "$(typeof(x)) Ax and $(typeof(y)) By must share site indices. On site $v, Ax has site indices $(uniqueinds(siteinds(A, v), (siteinds(x, v)))) while By has site indices $(uniqueinds(siteinds(B, v), siteinds(y, v))).",
-    )
-  end
   ydag = sim(linkinds, dag(y))
   Bdag = sim(linkinds, dag(B))
   traversal_order = reverse(post_order_dfs_vertices(x, root_vertex))