Delete src/lib (ITensorsExtensions + BaseExtensions submodules)

Project.toml

@@ -7,33 +7,25 @@ authors = ["Matthew Fishman <mfishman@flatironinstitute.org>, Joseph Tindall <jt
 projects = ["benchmark", "dev", "docs", "examples", "test"]
 
 [deps]
-AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
-Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
-Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
-ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
 DataGraphs = "b5a273c3-7e6c-41f6-98bd-8d7f1525a36a"
 Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
 IsApprox = "28f27b66-4bd8-47e7-9110-e2746eb8bed7"
-IterTools = "c8e1da08-722c-5040-9ed9-7db0dc04731e"
 KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 NamedGraphs = "678767b0-92e7-4007-89e4-4527a8725b19"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-SerializedElementArrays = "d3ce8812-9567-47e9-a7b5-65a6d70a3065"
 SimpleTraits = "699a6c99-e7fa-54fc-8d76-47d257e15c1d"
 SplitApplyCombine = "03a91e81-4c3e-53e1-a0a4-9c0c8f19dd66"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 StructWalk = "31cdf514-beb7-4750-89db-dda9d2eb8d3d"
-Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"
-TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 TupleTools = "9d95972d-f1c8-5527-a6e0-b4b365fa01f6"
 
 [weakdeps]
@@ -45,31 +37,23 @@ ITensorNetworksOMEinsumContractionOrdersExt = "OMEinsumContractionOrders"
 ITensorNetworksTensorOperationsExt = "TensorOperations"
 
 [compat]
-AbstractTrees = "0.4.4"
 Accessors = "0.1.42"
 Adapt = "4"
-Combinatorics = "1"
-Compat = "3, 4"
-ConstructionBase = "1.6"
 DataGraphs = "0.4"
 Dictionaries = "0.4"
 DocStringExtensions = "0.9"
 Graphs = "1.8"
 ITensors = "0.7, 0.8, 0.9"
 IsApprox = "0.1, 1, 2"
-IterTools = "1.4"
 KrylovKit = "0.6, 0.7, 0.8, 0.9, 0.10"
 MacroTools = "0.5"
 NDTensors = "0.3, 0.4"
 NamedGraphs = "0.11"
 OMEinsumContractionOrders = "0.8.3, 0.9, 1"
-SerializedElementArrays = "0.1"
 SimpleTraits = "0.9"
 SplitApplyCombine = "1.2"
 StaticArrays = "1.5.12"
 StructWalk = "0.2"
-Suppressor = "0.2"
 TensorOperations = "5.2"
-TimerOutputs = "0.5.22"
 TupleTools = "1.4"
 julia = "1.10"

docs/src/deprecated_methods.md

@@ -1,15 +1,3 @@
 # Deprecated Methods
 
 Suggestions of methods which could be deleted.
-
-## Global Operations on ITensorNetworks
-
-
-## Miscellaneous Methods
-
-* Methods in `partitioneditensornetwork.jl`.
-  ```julia
-  linkinds(pitn::PartitionedGraph, edge::QuotientEdge)
-  ```
-  Likely removable once the BP `default_message` chain is cleaned up.
-

docs/src/experimental_methods.md

@@ -204,11 +204,6 @@ Methods which still need to be discussed, modified, or deprecated.
   rename_vertices(f::Function, tn::AbstractIndsNetwork)
   ```
 
-* Promoted index type across all site and link indices in the network (`abstractindsnetwork.jl`):
-  ```julia
-  promote_indtypeof(is::AbstractIndsNetwork)
-  ```
-
 * Build an `IndsNetwork` whose site/link indices at each vertex/edge are the union
   of the corresponding indices from each input network (graphs must match) (`abstractindsnetwork.jl`):
   ```julia
@@ -219,8 +214,6 @@ Methods which still need to be discussed, modified, or deprecated.
 
 * Type-parameter accessors and graph-type metadata (`indsnetwork.jl`):
   ```julia
-  indtype(inds_network::IndsNetwork)
-  indtype(::Type{<:IndsNetwork{V, I}}) where {V, I}
   data_graph(is::IndsNetwork)
   underlying_graph(is::IndsNetwork)
   vertextype(::Type{<:IndsNetwork{V}}) where {V}

docs/src/interface_methods.md

@@ -276,13 +276,10 @@ These ITensorNetwork constructor interfaces are foundational to other constructo
     )
   ```
 
-* Apply a set of gates to an ITensorNetwork (`apply.jl`):
+* Apply a gate (or a sequence of gates) to an ITensorNetwork (`apply.jl`):
   ```julia
-  ITensors.apply(o::Union{NamedEdge, ITensor},ψ::AbstractITensorNetwork; kws...)
-  ITensors.apply(o⃗::Union{Vector{NamedEdge}, Vector{ITensor}}, ψ::AbstractITensorNetwork; kws...)
-  ITensors.apply(o⃗::Scaled,ψ::AbstractITensorNetwork; kws...)
-  ITensors.apply(o⃗::Prod, ψ::AbstractITensorNetwork; kws...)
-  ITensors.apply(o::Op, ψ::AbstractITensorNetwork; kws...)
+  ITensors.apply(o::ITensor, ψ::AbstractITensorNetwork; kws...)
+  ITensors.apply(o⃗::Vector{ITensor}, ψ::AbstractITensorNetwork; kws...)
   ```
 
 ## Visualization System

src/ITensorNetworks.jl

@@ -1,7 +1,5 @@
 module ITensorNetworks
 
-include("lib/BaseExtensions/src/BaseExtensions.jl")
-include("lib/ITensorsExtensions/src/ITensorsExtensions.jl")
 include("visualize.jl")
 include("abstractindsnetwork.jl")
 include("indextags.jl")
@@ -13,7 +11,6 @@ include("contraction_sequences.jl")
 include("tebd.jl")
 include("itensornetwork.jl")
 include("contract.jl")
-include("partitioneditensornetwork.jl")
 include("edge_sequences.jl")
 include("caches/abstractbeliefpropagationcache.jl")
 include("caches/beliefpropagationcache.jl")

src/abstractindsnetwork.jl

@@ -1,9 +1,8 @@
-using .ITensorsExtensions: ITensorsExtensions, promote_indtype, trivial_space
 using DataGraphs: DataGraphs, AbstractDataGraph, DataGraph, IsUnderlyingGraph, edge_data,
     get_edge_data, get_vertex_data, is_edge_assigned, is_vertex_assigned, map_data,
     set_edge_data!, set_vertex_data!, underlying_graph_type, vertex_data
 using Graphs: Graphs, AbstractEdge
-using ITensors: ITensors, unioninds
+using ITensors: ITensors, Index, unioninds
 using NamedGraphs.GraphsExtensions:
     GraphsExtensions, directed_graph, incident_edges, rename_vertices
 using NamedGraphs: NamedGraphs
@@ -62,18 +61,6 @@ end
 # Convenience functions
 #
 
-function ITensorsExtensions.promote_indtypeof(is::AbstractIndsNetwork)
-    sitetype = mapreduce(promote_indtype, vertices(is); init = Index{Int}) do v
-        # TODO: Replace with `is[v]` once `getindex(::IndsNetwork, ...)` is smarter.
-        return mapreduce(typeof, promote_indtype, get(is, v, Index[]); init = Index{Int})
-    end
-    linktype = mapreduce(promote_indtype, edges(is); init = Index{Int}) do e
-        # TODO: Replace with `is[e]` once `getindex(::IndsNetwork, ...)` is smarter.
-        return mapreduce(typeof, promote_indtype, get(is, e, Index[]); init = Index{Int})
-    end
-    return promote_indtype(sitetype, linktype)
-end
-
 function union_all_inds(is_in::AbstractIndsNetwork...)
     @assert all(map(ug -> ug == underlying_graph(is_in[1]), underlying_graph.(is_in)))
     is_out = IndsNetwork(underlying_graph(is_in[1]))

src/abstractitensornetwork.jl

@@ -1,4 +1,3 @@
-using .ITensorsExtensions: ITensorsExtensions, indtype, promote_indtype, trivial_space
 using Adapt: Adapt, adapt, adapt_structure
 using DataGraphs: DataGraphs, edge_data, get_vertex_data, is_vertex_assigned,
     set_vertex_data!, underlying_graph, underlying_graph_type, vertex_data
@@ -65,7 +64,6 @@ function ITensors.datatype(tn::AbstractITensorNetwork)
     return mapreduce(v -> datatype(tn[v]), promote_type, vertices(tn))
 end
 
-# TODO: Move to `BaseExtensions` module.
 function is_setindex!_expr(expr::Expr)
     return is_assignment_expr(expr) && is_getindex_expr(first(expr.args))
 end
@@ -210,10 +208,6 @@ end
 # Promotion and conversion
 #
 
-function ITensorsExtensions.promote_indtypeof(tn::AbstractITensorNetwork)
-    return mapreduce(v -> indtype(tn[v]), promote_indtype, vertices(tn))
-end
-
 function NDTensors.scalartype(tn::AbstractITensorNetwork)
     return mapreduce(v -> eltype(tn[v]), promote_type, vertices(tn); init = Bool)
 end

src/apply.jl

@@ -1,11 +1,28 @@
-using .BaseExtensions: maybe_real
 using Graphs: has_edge, ne
 using ITensors.NDTensors: scalartype
-using ITensors: ITensors, ITensor, Index, Ops, apply, commonind, commoninds, contract, dag,
-    denseblocks, factorize, factorize_svd, hascommoninds, hasqns, isdiag, noprime, prime,
-    replaceind, replaceinds, tags, unioninds, uniqueinds
+using ITensors: ITensors, ITensor, Index, apply, commonind, commoninds, contract, dag,
+    denseblocks, factorize, factorize_svd, hascommoninds, hasqns, isdiag, map_diag,
+    noncommonind, noprime, prime, replaceind, replaceinds, tags, unioninds, uniqueinds
 using LinearAlgebra: eigen, norm, qr, svd
-using NamedGraphs: NamedEdge
+
+#TODO: Make this work for non-hermitian A
+function eigendecomp(A::ITensor, linds, rinds; ishermitian = false, kwargs...)
+    @assert ishermitian
+    D, U = eigen(A, linds, rinds; ishermitian, kwargs...)
+    ul, ur = noncommonind(D, U), commonind(D, U)
+    Ul = replaceinds(U, vcat(rinds, ur), vcat(linds, ul))
+    return Ul, D, dag(U)
+end
+
+# Apply `f` to the eigenvalues of `A` (assumed Hermitian along the
+# `Linds | Rinds` bipartition) and rebuild the operator. Used by
+# `simple_update_bp` to form `sqrt(env)` and `inv ∘ sqrt(env)` of each
+# product-environment factor.
+function map_eigvals(f::Function, A::ITensor, Linds, Rinds; kws...)
+    isdiag(A) && return map_diag(f, A)
+    Ul, D, Ur = eigendecomp(A, Linds, Rinds; kws...)
+    return Ul * map_diag(f, D) * Ur
+end
 
 # Reduced simple-update on a 2-site gate `o`. Assumes `envs` is a product
 # environment: each `env` shares indices with exactly one of `ψ[v⃗[1]]` or
@@ -14,31 +31,41 @@ using NamedGraphs: NamedEdge
 # each endpoint into a small bond tensor, applies the gate, factor-SVDs back,
 # then unwinds the inverse sqrt envs.
 function simple_update_bp(
-        o::Union{NamedEdge, ITensor}, ψ, v⃗; envs, callback = Returns(nothing), apply_kwargs...
+        o::ITensor, ψ, v⃗; envs, callback = Returns(nothing), apply_kwargs...
     )
     cutoff = 10 * eps(real(scalartype(ψ)))
     envs_v1 = filter(env -> hascommoninds(env, ψ[v⃗[1]]), envs)
     envs_v2 = filter(env -> hascommoninds(env, ψ[v⃗[2]]), envs)
     @assert all(ndims(env) == 2 for env in vcat(envs_v1, envs_v2))
     sqrt_envs_v1 = [
-        ITensorsExtensions.map_eigvals(
-                sqrt, env, inds(env)[1], inds(env)[2]; cutoff, ishermitian = true
-            ) for env in envs_v1
+        map_eigvals(sqrt, env, inds(env)[1], inds(env)[2]; cutoff, ishermitian = true)
+            for env in envs_v1
     ]
     sqrt_envs_v2 = [
-        ITensorsExtensions.map_eigvals(
-                sqrt, env, inds(env)[1], inds(env)[2]; cutoff, ishermitian = true
-            ) for env in envs_v2
+        map_eigvals(sqrt, env, inds(env)[1], inds(env)[2]; cutoff, ishermitian = true)
+            for env in envs_v2
     ]
     inv_sqrt_envs_v1 = [
-        ITensorsExtensions.map_eigvals(
-                inv ∘ sqrt, env, inds(env)[1], inds(env)[2]; cutoff, ishermitian = true
-            ) for env in envs_v1
+        map_eigvals(
+                inv ∘ sqrt,
+                env,
+                inds(env)[1],
+                inds(env)[2];
+                cutoff,
+                ishermitian = true
+            )
+            for env in envs_v1
     ]
     inv_sqrt_envs_v2 = [
-        ITensorsExtensions.map_eigvals(
-                inv ∘ sqrt, env, inds(env)[1], inds(env)[2]; cutoff, ishermitian = true
-            ) for env in envs_v2
+        map_eigvals(
+                inv ∘ sqrt,
+                env,
+                inds(env)[1],
+                inds(env)[2];
+                cutoff,
+                ishermitian = true
+            )
+            for env in envs_v2
     ]
     ψᵥ₁ = contract([ψ[v⃗[1]]; sqrt_envs_v1])
     ψᵥ₂ = contract([ψ[v⃗[2]]; sqrt_envs_v2])
@@ -68,7 +95,7 @@ function simple_update_bp(
 end
 
 function ITensors.apply(
-        o::Union{NamedEdge, ITensor},
+        o::ITensor,
         ψ::AbstractITensorNetwork;
         envs = ITensor[],
         normalize = false,
@@ -119,7 +146,7 @@ function ITensors.apply(
 end
 
 function ITensors.apply(
-        o⃗::Union{Vector{NamedEdge}, Vector{ITensor}},
+        o⃗::Vector{ITensor},
         ψ::AbstractITensorNetwork;
         normalize = false,
         ortho = false,
@@ -131,31 +158,3 @@ function ITensors.apply(
     end
     return o⃗ψ
 end
-
-function ITensors.apply(
-        o⃗::Scaled,
-        ψ::AbstractITensorNetwork;
-        cutoff = nothing,
-        normalize = false,
-        ortho = false,
-        apply_kwargs...
-    )
-    return maybe_real(Ops.coefficient(o⃗)) *
-        apply(Ops.argument(o⃗), ψ; cutoff, maxdim, normalize, ortho, apply_kwargs...)
-end
-
-function ITensors.apply(
-        o⃗::Prod, ψ::AbstractITensorNetwork; normalize = false, ortho = false, apply_kwargs...
-    )
-    o⃗ψ = ψ
-    for oᵢ in o⃗
-        o⃗ψ = apply(oᵢ, o⃗ψ; normalize, ortho, apply_kwargs...)
-    end
-    return o⃗ψ
-end
-
-function ITensors.apply(
-        o::Op, ψ::AbstractITensorNetwork; normalize = false, ortho = false, apply_kwargs...
-    )
-    return apply(ITensor(o, siteinds(ψ)), ψ; normalize, ortho, apply_kwargs...)
-end

src/caches/abstractbeliefpropagationcache.jl

@@ -1,10 +1,12 @@
 using Adapt: Adapt, adapt, adapt_structure
-using Graphs: Graphs, IsDirected
-using ITensors: delta, dir
+using Graphs: Graphs, IsDirected, dst, src
+using ITensors: commoninds, delta, dir
 using LinearAlgebra: diag, dot
 using NDTensors: NDTensors
-using NamedGraphs.PartitionedGraphs: PartitionedGraph, PartitionedGraphs, QuotientVertex,
-    boundary_quotientedges, quotientedges, quotientvertices, unpartitioned_graph
+using NamedGraphs.GraphsExtensions: subgraph
+using NamedGraphs.PartitionedGraphs: PartitionedGraph, PartitionedGraphs, QuotientEdge,
+    QuotientVertex, boundary_quotientedges, quotientedges, quotientvertices,
+    unpartitioned_graph
 using NamedGraphs.SimilarType: SimilarType
 using NamedGraphs: to_graph_index
 using SimpleTraits: SimpleTraits, @traitfn, Not
@@ -161,7 +163,8 @@ function PartitionedGraphs.quotientedge(
 end
 
 function linkinds(bpc::AbstractBeliefPropagationCache, pe::QuotientEdge)
-    return linkinds(partitioned_tensornetwork(bpc), pe)
+    pitn = partitioned_tensornetwork(bpc)
+    return commoninds(subgraph(pitn, src(pe)), subgraph(pitn, dst(pe)))
 end
 
 NDTensors.scalartype(bpc::AbstractBeliefPropagationCache) = scalartype(tensornetwork(bpc))