Keep index count to avoid index clash

ext/QrochetQuacExt.jl

@@ -12,10 +12,9 @@ Qrochet.evolve!(qtn::Ansatz, gate::Gate) = evolve!(qtn, Qrochet.Dense(gate))
 
 function Qrochet.Quantum(circuit::Circuit)
     n = lanes(circuit)
-    wire = [[Tenet.letter(i)] for i in 1:n]
+    wire = [[Qrochet.nextindex()] for _ in 1:n]
     tensors = Tensor[]
 
-    i = n + 1
     for gate in circuit
         G = arraytype(gate)
         array = G(gate)
@@ -27,8 +26,7 @@ function Qrochet.Quantum(circuit::Circuit)
         end
 
         inds = map(lanes(gate)) do l
-            from, to = last(wire[l]), Tenet.letter(i)
-            i += 1
+            from, to = last(wire[l]), Qrochet.nextindex()
             push!(wire[l], to)
             (from, to)
         end |> x -> zip(x...) |> Iterators.flatten |> collect

src/Ansatz/Chain.jl

@@ -1,5 +1,4 @@
 using Tenet
-using Tenet: letter
 using LinearAlgebra
 using Random
 using Muscle: gramschmidt!
@@ -32,12 +31,13 @@ function Chain(::State, boundary::Periodic, arrays::Vector{<:AbstractArray})
     @assert all(==(3) ∘ ndims, arrays) "All arrays must have 3 dimensions"
 
     n = length(arrays)
+    symbols = [nextindex() for _ in 1:2n]
 
     _tensors = map(enumerate(arrays)) do (i, array)
-        Tensor(array, [letter(i), letter(n + mod1(i - 1, length(arrays))), letter(n + mod1(i, length(arrays)))])
+        Tensor(array, [symbols[i], symbols[n+mod1(i - 1, n)], symbols[n+mod1(i, n)]])
     end
 
-    sitemap = Dict(Site(i) => letter(i) for i in 1:length(arrays))
+    sitemap = Dict(Site(i) => symbols[i] for i in 1:n)
 
     Chain(Quantum(TensorNetwork(_tensors), sitemap), boundary)
 end
@@ -48,17 +48,19 @@ function Chain(::State, boundary::Open, arrays::Vector{<:AbstractArray})
     @assert ndims(arrays[end]) == 2 "Last array must have 2 dimensions"
 
     n = length(arrays)
+    symbols = [nextindex() for _ in 1:2n-1]
+
     _tensors = map(enumerate(arrays)) do (i, array)
         if i == 1
-            Tensor(array, [letter(1), letter(1 + n)])
+            Tensor(array, [symbols[1], symbols[1+n]])
         elseif i == n
-            Tensor(array, [letter(n), letter(n + mod1(n - 1, length(arrays)))])
+            Tensor(array, [symbols[n], symbols[n+mod1(n - 1, n)]])
         else
-            Tensor(array, [letter(i), letter(n + mod1(i - 1, length(arrays))), letter(n + mod1(i, length(arrays)))])
+            Tensor(array, [symbols[i], symbols[n+mod1(i - 1, n)], symbols[n+mod1(i, n)]])
         end
     end
 
-    sitemap = Dict(Site(i) => letter(i) for i in 1:length(arrays))
+    sitemap = Dict(Site(i) => symbols[i] for i in 1:n)
 
     Chain(Quantum(TensorNetwork(_tensors), sitemap), boundary)
 end
@@ -67,21 +69,14 @@ function Chain(::Operator, boundary::Periodic, arrays::Vector{<:AbstractArray})
     @assert all(==(4) ∘ ndims, arrays) "All arrays must have 3 dimensions"
 
     n = length(arrays)
+    symbols = [nextindex() for _ in 1:3n]
 
     _tensors = map(enumerate(arrays)) do (i, array)
-        Tensor(
-            array,
-            [
-                letter(i),
-                letter(i + n),
-                letter(2 * n + mod1(i - 1, length(arrays))),
-                letter(2 * n + mod1(i, length(arrays))),
-            ],
-        )
+        Tensor(array, [symbols[i], symbols[i+n], symbols[2n+mod1(i - 1, n)], symbols[2n+mod1(i, n)]])
     end
 
-    sitemap = Dict(Site(i) => letter(i) for i in 1:length(arrays))
-    merge!(sitemap, Dict(Site(i; dual = true) => letter(i + n) for i in 1:length(arrays)))
+    sitemap = Dict(Site(i) => symbols[i] for i in 1:n)
+    merge!(sitemap, Dict(Site(i; dual = true) => symbols[i+n] for i in 1:n))
 
     Chain(Quantum(TensorNetwork(_tensors), sitemap), boundary)
 end
@@ -92,26 +87,20 @@ function Chain(::Operator, boundary::Open, arrays::Vector{<:AbstractArray})
     @assert ndims(arrays[end]) == 3 "Last array must have 3 dimensions"
 
     n = length(arrays)
+    symbols = [nextindex() for _ in 1:3n-1]
+
     _tensors = map(enumerate(arrays)) do (i, array)
         if i == 1
-            Tensor(array, [letter(1), letter(n + 1), letter(1 + 2 * n)])
+            Tensor(array, [symbols[1], symbols[n+1], symbols[1+2n]])
         elseif i == n
-            Tensor(array, [letter(n), letter(2 * n), letter(2 * n + mod1(n - 1, length(arrays)))])
+            Tensor(array, [symbols[n], symbols[2n], symbols[2n+mod1(n - 1, n)]])
         else
-            Tensor(
-                array,
-                [
-                    letter(i),
-                    letter(i + n),
-                    letter(2 * n + mod1(i - 1, length(arrays))),
-                    letter(2 * n + mod1(i, length(arrays))),
-                ],
-            )
+            Tensor(array, [symbols[i], symbols[i+n], symbols[2n+mod1(i - 1, n)], symbols[2n+mod1(i, n)]])
         end
     end
 
-    sitemap = Dict(Site(i) => letter(i) for i in 1:length(arrays))
-    merge!(sitemap, Dict(Site(i; dual = true) => letter(i + n) for i in 1:length(arrays)))
+    sitemap = Dict(Site(i) => symbols[i] for i in 1:n)
+    merge!(sitemap, Dict(Site(i; dual = true) => symbols[i+n] for i in 1:n))
 
     Chain(Quantum(TensorNetwork(_tensors), sitemap), boundary)
 end

src/Ansatz/Dense.jl

@@ -6,11 +6,12 @@ function Dense(::State, array::AbstractArray)
     @assert ndims(array) > 0
     @assert all(>(1), size(array))
 
+    symbols = [nextindex() for _ in 1:ndims(array)]
     sitemap = map(1:ndims(array)) do i
-        Site(i) => letter(i)
+        Site(i) => symbols[i]
     end |> Dict{Int,Symbol}
 
-    tensor = Tensor(array, [letter(i) for i in 1:ndims(array)])
+    tensor = Tensor(array, symbols)
 
     tn = TensorNetwork([tensor])
     qtn = Quantum(tn, sitemap)
@@ -22,7 +23,7 @@ function Dense(::Operator, array::AbstractArray; sitemap::Vector{Site})
     @assert all(>(1), size(array))
     @assert length(sitemap) == ndims(array)
 
-    tensor_inds = [letter(i) for i in 1:ndims(array)]
+    tensor_inds = [nextindex() for _ in 1:ndims(array)]
     tensor = Tensor(array, tensor_inds)
     tn = TensorNetwork([tensor])
 

src/Ansatz/Product.jl

@@ -1,5 +1,4 @@
 using Tenet
-using Tenet: letter
 using LinearAlgebra
 
 struct Product <: Ansatz
@@ -12,22 +11,24 @@ struct Product <: Ansatz
 end
 
 function Product(arrays::Vector{<:Vector})
+    symbols = [nextindex() for _ in 1:length(arrays)]
     _tensors = map(enumerate(arrays)) do (i, array)
-        Tensor(array, [letter(i)])
+        Tensor(array, [symbols[i]])
     end
 
-    sitemap = Dict(Site(i) => letter(i) for i in 1:length(arrays))
+    sitemap = Dict(Site(i) => symbols[i] for i in 1:length(arrays))
 
     Product(TensorNetwork(_tensors), sitemap)
 end
 
 function Product(arrays::Vector{<:Matrix})
     n = length(arrays)
+    symbols = [nextindex() for _ in 1:2*length(arrays)]
     _tensors = map(enumerate(arrays)) do (i, array)
-        Tensor(array, [letter(i + n), letter(i)])
+        Tensor(array, [symbols[i+n], symbols[i]])
     end
 
-    sitemap = merge!(Dict(Site(i, dual = true) => letter(i) for i in 1:n), Dict(Site(i) => letter(i + n) for i in 1:n))
+    sitemap = merge!(Dict(Site(i, dual = true) => symbols[i] for i in 1:n), Dict(Site(i) => symbols[i+n] for i in 1:n))
 
     Product(TensorNetwork(_tensors), sitemap)
 end

src/Qrochet.jl

@@ -1,5 +1,7 @@
 module Qrochet
 
+include("Utils.jl")
+
 include("Quantum.jl")
 export Site, @site_str, isdual
 export ninputs, noutputs, inputs, outputs, sites, nsites

src/Utils.jl

@@ -0,0 +1,6 @@
+using Tenet
+
+const __indexcounter::Threads.Atomic{Int} = Threads.Atomic{Int}(1)
+
+currindex() = Tenet.letter(__indexcounter[])
+nextindex() = Tenet.letter(Threads.atomic_add!(__indexcounter, 1))