Merge remote-tracking branch 'origin/main' into normalize!

Author: JoeyT1994

Project.toml

@@ -1,7 +1,7 @@
 name = "ITensorNetworks"
 uuid = "2919e153-833c-4bdc-8836-1ea460a35fc7"
 authors = ["Matthew Fishman <[email protected]>, Joseph Tindall <[email protected]> and contributors"]
-version = "0.11.15"
+version = "0.11.24"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -62,20 +62,20 @@ DocStringExtensions = "0.9"
 EinExprs = "0.6.4"
 Graphs = "1.8"
 GraphsFlows = "0.1.1"
-ITensorMPS = "0.2.2"
-ITensors = "0.6.8"
-IsApprox = "0.1"
+ITensorMPS = "0.3"
+ITensors = "0.7"
+IsApprox = "0.1, 1, 2"
 IterTools = "1.4.0"
-KrylovKit = "0.6, 0.7"
+KrylovKit = "0.6, 0.7, 0.8"
 MacroTools = "0.5"
 NDTensors = "0.3"
 NamedGraphs = "0.6.0"
-OMEinsumContractionOrders = "0.8.3"
+OMEinsumContractionOrders = "0.8.3, 0.9"
 Observers = "0.2.4"
 PackageExtensionCompat = "1"
 SerializedElementArrays = "0.1"
 SimpleTraits = "0.9"
-SparseArrayKit = "0.3"
+SparseArrayKit = "0.3, 0.4"
 SplitApplyCombine = "1.2"
 StaticArrays = "1.5.12"
 StructWalk = "0.2"

README.md

@@ -0,0 +1,21 @@
+using ITensorNetworks: IndsNetwork, siteinds, ttn
+using ITensorNetworks.ModelHamiltonians: ising
+using ITensors: Index, OpSum, terms, sites
+using NamedGraphs.NamedGraphGenerators: named_grid
+using NamedGraphs.GraphsExtensions: rem_vertex
+
+function filter_terms(H, verts)
+    H_new = OpSum()
+    for term in terms(H)
+        if isempty(filter(v -> v ∈ verts, sites(term)))
+            H_new += term
+        end
+    end
+    return H_new
+end
+
+g = named_grid((8,1))
+s = siteinds("S=1/2", g)
+H = ising(s)
+H_mod = filter_terms(H, [(4,1)])
+ttno = ttn(H_mod, s)

examples/test.jl

@@ -7,6 +7,7 @@ using Graphs:
   add_edge!,
   add_vertex!,
   bfs_tree,
+  center,
   dst,
   edges,
   edgetype,
@@ -18,6 +19,7 @@ using Graphs:
 using ITensors:
   ITensors,
   ITensor,
+  @Algorithm_str,
   addtags,
   combiner,
   commoninds,
@@ -40,10 +42,10 @@ using ITensorMPS: ITensorMPS, add, linkdim, linkinds, siteinds
 using .ITensorsExtensions: ITensorsExtensions, indtype, promote_indtype
 using LinearAlgebra: LinearAlgebra, factorize
 using MacroTools: @capture
-using NamedGraphs: NamedGraphs, NamedGraph, not_implemented
+using NamedGraphs: NamedGraphs, NamedGraph, not_implemented, steiner_tree
 using NamedGraphs.GraphsExtensions:
   ⊔, directed_graph, incident_edges, rename_vertices, vertextype
-using NDTensors: NDTensors, dim
+using NDTensors: NDTensors, dim, Algorithm
 using SplitApplyCombine: flatten
 
 abstract type AbstractITensorNetwork{V} <: AbstractDataGraph{V,ITensor,ITensor} end
@@ -584,7 +586,9 @@ function LinearAlgebra.factorize(tn::AbstractITensorNetwork, edge::Pair; kwargs.
 end
 
 # For ambiguity error; TODO: decide whether to use graph mutating methods when resulting graph is unchanged?
-function _orthogonalize_edge(tn::AbstractITensorNetwork, edge::AbstractEdge; kwargs...)
+function gauge_edge(
+  alg::Algorithm"orthogonalize", tn::AbstractITensorNetwork, edge::AbstractEdge; kwargs...
+)
   # tn = factorize(tn, edge; kwargs...)
   # # TODO: Implement as `only(common_neighbors(tn, src(edge), dst(edge)))`
   # new_vertex = only(neighbors(tn, src(edge)) ∩ neighbors(tn, dst(edge)))
@@ -598,23 +602,43 @@ function _orthogonalize_edge(tn::AbstractITensorNetwork, edge::AbstractEdge; kwa
   return tn
 end
 
-function ITensorMPS.orthogonalize(tn::AbstractITensorNetwork, edge::AbstractEdge; kwargs...)
-  return _orthogonalize_edge(tn, edge; kwargs...)
+# For ambiguity error; TODO: decide whether to use graph mutating methods when resulting graph is unchanged?
+function gauge_walk(
+  alg::Algorithm, tn::AbstractITensorNetwork, edges::Vector{<:AbstractEdge}; kwargs...
+)
+  tn = copy(tn)
+  for edge in edges
+    tn = gauge_edge(alg, tn, edge; kwargs...)
+  end
+  return tn
+end
+
+function gauge_walk(alg::Algorithm, tn::AbstractITensorNetwork, edge::Pair; kwargs...)
+  return gauge_edge(alg::Algorithm, tn, edgetype(tn)(edge); kwargs...)
 end
 
-function ITensorMPS.orthogonalize(tn::AbstractITensorNetwork, edge::Pair; kwargs...)
-  return orthogonalize(tn, edgetype(tn)(edge); kwargs...)
+function gauge_walk(
+  alg::Algorithm, tn::AbstractITensorNetwork, edges::Vector{<:Pair}; kwargs...
+)
+  return gauge_walk(alg, tn, edgetype(tn).(edges); kwargs...)
 end
 
-# Orthogonalize an ITensorNetwork towards a source vertex, treating
+# Gauge a ITensorNetwork towards a region, treating
 # the network as a tree spanned by a spanning tree.
-# TODO: Rename `tree_orthogonalize`.
-function ITensorMPS.orthogonalize(ψ::AbstractITensorNetwork, source_vertex)
-  spanning_tree_edges = post_order_dfs_edges(bfs_tree(ψ, source_vertex), source_vertex)
-  for e in spanning_tree_edges
-    ψ = orthogonalize(ψ, e)
-  end
-  return ψ
+function tree_gauge(alg::Algorithm, ψ::AbstractITensorNetwork, region::Vector)
+  region_center =
+    length(region) != 1 ? first(center(steiner_tree(ψ, region))) : only(region)
+  path = post_order_dfs_edges(bfs_tree(ψ, region_center), region_center)
+  path = filter(e -> !((src(e) ∈ region) && (dst(e) ∈ region)), path)
+  return gauge_walk(alg, ψ, path)
+end
+
+function tree_gauge(alg::Algorithm, ψ::AbstractITensorNetwork, region)
+  return tree_gauge(alg, ψ, [region])
+end
+
+function tree_orthogonalize(ψ::AbstractITensorNetwork, region; kwargs...)
+  return tree_gauge(Algorithm("orthogonalize"), ψ, region; kwargs...)
 end
 
 # TODO: decide whether to use graph mutating methods when resulting graph is unchanged?
@@ -759,7 +783,7 @@ end
 # Link dimensions
 # 
 
-function ITensors.maxlinkdim(tn::AbstractITensorNetwork)
+function ITensorMPS.maxlinkdim(tn::AbstractITensorNetwork)
   md = 1
   for e in edges(tn)
     md = max(md, linkdim(tn, e))

src/abstractitensornetwork.jl

@@ -200,7 +200,7 @@ function ITensors.apply(
   v⃗ = neighbor_vertices(ψ, o)
   if length(v⃗) == 1
     if ortho
-      ψ = orthogonalize(ψ, v⃗[1])
+      ψ = tree_orthogonalize(ψ, v⃗[1])
     end
     oψᵥ = apply(o, ψ[v⃗[1]])
     if normalize
@@ -215,7 +215,7 @@ function ITensors.apply(
       error("Vertices where the gates are being applied must be neighbors for now.")
     end
     if ortho
-      ψ = orthogonalize(ψ, v⃗[1])
+      ψ = tree_orthogonalize(ψ, v⃗[1])
     end
     if variational_optimization_only || !is_product_env
       ψᵥ₁, ψᵥ₂ = full_update_bp(

src/apply.jl

@@ -16,7 +16,6 @@ using NDTensors: NDTensors
 
 default_message(elt, inds_e) = ITensor[denseblocks(delta(elt, i)) for i in inds_e]
 default_messages(ptn::PartitionedGraph) = Dictionary()
-default_message_norm(m::ITensor) = norm(m)
 function default_message_update(contract_list::Vector{ITensor}; normalize=true, kwargs...)
   sequence = optimal_contraction_sequence(contract_list)
   updated_messages = contract(contract_list; sequence, kwargs...)
@@ -107,7 +106,7 @@ end
 
 function message(bp_cache::BeliefPropagationCache, edge::PartitionEdge)
   mts = messages(bp_cache)
-  return get(mts, edge, default_message(bp_cache, edge))
+  return get(() -> default_message(bp_cache, edge), mts, edge)
 end
 function messages(bp_cache::BeliefPropagationCache, edges; kwargs...)
   return map(edge -> message(bp_cache, edge; kwargs...), edges)
@@ -153,24 +152,16 @@ end
 function environment(bp_cache::BeliefPropagationCache, verts::Vector)
   partition_verts = partitionvertices(bp_cache, verts)
   messages = environment(bp_cache, partition_verts)
-  central_tensors = ITensor[
-    tensornetwork(bp_cache)[v] for v in setdiff(vertices(bp_cache, partition_verts), verts)
-  ]
+  central_tensors = factors(bp_cache, setdiff(vertices(bp_cache, partition_verts), verts))
   return vcat(messages, central_tensors)
 end
 
-function factors(bp_cache::BeliefPropagationCache, vertices)
-  tn = tensornetwork(bp_cache)
-  return map(vertex -> tn[vertex], vertices)
-end
-
-function factor(bp_cache::BeliefPropagationCache, vertex)
-  return only(factors(bp_cache, [vertex]))
+function factors(bp_cache::BeliefPropagationCache, verts::Vector)
+  return ITensor[tensornetwork(bp_cache)[v] for v in verts]
 end
 
 function factor(bp_cache::BeliefPropagationCache, vertex::PartitionVertex)
-  ptn = partitioned_tensornetwork(bp_cache)
-  return collect(eachtensor(subgraph(ptn, vertex)))
+  return factors(bp_cache, vertices(bp_cache, vertex))
 end
 
 """

src/caches/beliefpropagationcache.jl

@@ -1,4 +1,5 @@
-using ITensors: inner, scalar, loginner
+using ITensors: inner, scalar
+using ITensorMPS: ITensorMPS, loginner
 using LinearAlgebra: norm, norm_sqr
 
 default_contract_alg(tns::Tuple) = "bp"
@@ -53,7 +54,7 @@ function ITensors.inner(
   return scalar(tn; sequence)
 end
 
-function ITensors.loginner(
+function ITensorMPS.loginner(
   ϕ::AbstractITensorNetwork,
   ψ::AbstractITensorNetwork;
   alg=default_contract_alg((ϕ, ψ)),
@@ -62,7 +63,7 @@ function ITensors.loginner(
   return loginner(Algorithm(alg), ϕ, ψ; kwargs...)
 end
 
-function ITensors.loginner(
+function ITensorMPS.loginner(
   ϕ::AbstractITensorNetwork,
   A::AbstractITensorNetwork,
   ψ::AbstractITensorNetwork;
@@ -72,13 +73,13 @@ function ITensors.loginner(
   return loginner(Algorithm(alg), ϕ, A, ψ; kwargs...)
 end
 
-function ITensors.loginner(
+function ITensorMPS.loginner(
   alg::Algorithm"exact", ϕ::AbstractITensorNetwork, ψ::AbstractITensorNetwork; kwargs...
 )
   return log(inner(alg, ϕ, ψ); kwargs...)
 end
 
-function ITensors.loginner(
+function ITensorMPS.loginner(
   alg::Algorithm"exact",
   ϕ::AbstractITensorNetwork,
   A::AbstractITensorNetwork,
@@ -88,7 +89,7 @@ function ITensors.loginner(
   return log(inner(alg, ϕ, A, ψ); kwargs...)
 end
 
-function ITensors.loginner(
+function ITensorMPS.loginner(
   alg::Algorithm"bp",
   ϕ::AbstractITensorNetwork,
   ψ::AbstractITensorNetwork;
@@ -99,7 +100,7 @@ function ITensors.loginner(
   return logscalar(alg, tn; kwargs...)
 end
 
-function ITensors.loginner(
+function ITensorMPS.loginner(
   alg::Algorithm"bp",
   ϕ::AbstractITensorNetwork,
   A::AbstractITensorNetwork,

src/inner.jl

@@ -9,8 +9,8 @@ function alternating_update(
   nsites, # define default for each level of solver implementation
   updater,  # this specifies the update performed locally
   outputlevel=default_outputlevel(),
-  region_printer=nothing,
-  sweep_printer=nothing,
+  region_printer=default_region_printer,
+  sweep_printer=default_sweep_printer,
   (sweep_observer!)=nothing,
   (region_observer!)=nothing,
   root_vertex=GraphsExtensions.default_root_vertex(init_state),
@@ -59,7 +59,7 @@ function alternating_update(
   (sweep_observer!)=nothing,
   sweep_printer=default_sweep_printer,#?
   (region_observer!)=nothing,
-  region_printer=nothing,
+  region_printer=default_region_printer,
 )
   state = copy(init_state)
   @assert !isnothing(sweep_plans)

src/solvers/alternating_update/alternating_update.jl

@@ -1,44 +1,3 @@
-#ToDo: generalize beyond 2-site
-#ToDo: remove concept of orthogonality center for generality
-function current_ortho(sweep_plan, which_region_update)
-  regions = first.(sweep_plan)
-  region = regions[which_region_update]
-  current_verts = support(region)
-  if !isa(region, AbstractEdge) && length(region) == 1
-    return only(current_verts)
-  end
-  if which_region_update == length(regions)
-    # look back by one should be sufficient, but may be brittle?
-    overlapping_vertex = only(
-      intersect(current_verts, support(regions[which_region_update - 1]))
-    )
-    return overlapping_vertex
-  else
-    # look forward
-    other_regions = filter(
-      x -> !(issetequal(x, current_verts)), support.(regions[(which_region_update + 1):end])
-    )
-    # find the first region that has overlapping support with current region 
-    ind = findfirst(x -> !isempty(intersect(support(x), support(region))), other_regions)
-    if isnothing(ind)
-      # look backward
-      other_regions = reverse(
-        filter(
-          x -> !(issetequal(x, current_verts)),
-          support.(regions[1:(which_region_update - 1)]),
-        ),
-      )
-      ind = findfirst(x -> !isempty(intersect(support(x), support(region))), other_regions)
-    end
-    @assert !isnothing(ind)
-    future_verts = union(support(other_regions[ind]))
-    # return ortho_ceter as the vertex in current region that does not overlap with following one
-    overlapping_vertex = intersect(current_verts, future_verts)
-    nonoverlapping_vertex = only(setdiff(current_verts, overlapping_vertex))
-    return nonoverlapping_vertex
-  end
-end
-
 function region_update(
   projected_operator,
   state;
@@ -64,14 +23,13 @@ function region_update(
 
   # ToDo: remove orthogonality center on vertex for generality
   # region carries same information 
-  ortho_vertex = current_ortho(sweep_plan, which_region_update)
   if !isnothing(transform_operator)
     projected_operator = transform_operator(
       state, projected_operator; outputlevel, transform_operator_kwargs...
     )
   end
   state, projected_operator, phi = extracter(
-    state, projected_operator, region, ortho_vertex; extracter_kwargs..., internal_kwargs
+    state, projected_operator, region; extracter_kwargs..., internal_kwargs
   )
   # create references, in case solver does (out-of-place) modify PH or state
   state! = Ref(state)
@@ -97,9 +55,8 @@ function region_update(
   #  drho = noise * noiseterm(PH, phi, ortho) # TODO: actually implement this for trees...
   # so noiseterm is a solver
   #end
-  state, spec = inserter(
-    state, phi, region, ortho_vertex; inserter_kwargs..., internal_kwargs
-  )
+  #if isa(region, AbstractEdge) && 
+  state, spec = inserter(state, phi, region; inserter_kwargs..., internal_kwargs)
   all_kwargs = (;
     which_region_update,
     sweep_plan,

src/solvers/alternating_update/region_update.jl

@@ -1,5 +1,6 @@
 using Graphs: nv, vertices
-using ITensors: ITensors, linkinds, sim
+using ITensors: ITensors, sim
+using ITensorMPS: linkinds
 using ITensors.NDTensors: Algorithm, @Algorithm_str, contract
 using NamedGraphs: vertextype