Refactor

Project.toml

@@ -1,9 +1,10 @@
 name = "ITensorNumericalAnalysis"
 uuid = "666f501e-685d-4e36-ab44-ece85df6022b"
+version = "0.3.0"
 authors = ["Joseph Tindall <jtindall@flatironinstitute.org>", "Ryan Levy <rlevy@flatironinstitute.org>"]
-version = "0.2.1"
 
 [deps]
+Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4"
 Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
@@ -12,7 +13,10 @@ ITensorNetworks = "2919e153-833c-4bdc-8836-1ea460a35fc7"
 ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
 NamedGraphs = "678767b0-92e7-4007-89e4-4527a8725b19"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 SplitApplyCombine = "03a91e81-4c3e-53e1-a0a4-9c0c8f19dd66"
+TensorNetworkQuantumSimulator = "4de3b72a-362e-43dd-83ff-3f381eda9f9c"
+TensorOperations = "6aa20fa7-93e2-5fca-9bc0-fbd0db3c71a2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [weakdeps]
@@ -22,16 +26,20 @@ ITensorTCI = "23d98011-b9e5-4fd0-831d-c25c73611ef5"
 ITensorNumericalAnalysisTCIExt = "ITensorTCI"
 
 [compat]
+Adapt = "4.4.0"
 Dictionaries = "0.4.2"
 Glob = "1.3.1"
 Graphs = "1.9"
 ITensorMPS = "0.3.17"
-ITensorNetworks = "0.13"
+ITensorNetworks = "0.15.2"
 ITensorTCI = "0.0.1"
 ITensors = "0.9"
-NamedGraphs = "0.6"
+NamedGraphs = "0.7.0"
 Random = "1.8"
+Revise = "3.12.1"
 SplitApplyCombine = "1.2.3"
+TensorNetworkQuantumSimulator = "0.2.7"
+TensorOperations = "5.3.1"
 julia = "1.10"
 
 [extras]

examples/construct_multi_dimensional_function.jl

@@ -4,32 +4,33 @@ using Graphs: SimpleGraph, uniform_tree
 using NamedGraphs: NamedGraph
 using NamedGraphs.NamedGraphGenerators: named_comb_tree
 using ITensors: siteinds, inds
-using ITensorNetworks: maxlinkdim
+using TensorNetworkQuantumSimulator
 using Random: Random
 
 L = 4
 println(
-  "Constructing the 3D complex function f(z1,z2,z3) = z1³(z2 + z2²) + cosh(πz3)^2 as a tensor network on a comb tree with $L vertices",
+    "Constructing the 3D complex function f(z1,z2,z3) = z1³(z2 + z2²) + cosh(πz3)^2 as a tensor network on a comb tree with $L vertices",
 )
 Random.seed!(1234)
 g = named_comb_tree((3, L))
 real_dim_vertices = [[(j, i) for i in 1:L] for j in 1:3]
 imag_dim_vertices = [[(j, i) for i in L:-1:1] for j in 3:-1:1]
 s = complex_continuous_siteinds(g, real_dim_vertices, imag_dim_vertices)
-ψ_fz1 = poly_itn(s, [0.0, 0.0, 0.0, 1.0]; dim=1)
-ψ_fz2 = poly_itn(s, [0.0, 1.0, 1.0]; dim=2)
-ψ_fz3 = cosh_itn(s; k=Number(pi), dim=3)
+ψ_fz1 = poly_tnf(g, s, [0.0, 0.0, 0.0, 1.0]; dim = 1)
+ψ_fz2 = poly_tnf(g, s, [0.0, 1.0, 1.0]; dim = 2)
+ψ_fz3 = cosh_tnf(g, s; k = Number(pi), dim = 3)
 ψ_z = ψ_fz1 * ψ_fz2 + ψ_fz3 * ψ_fz3
 
-ψ_z = truncate(ψ_z; cutoff=1e-12)
-println("Maximum bond dimension of the network is $(maxlinkdim(ψ_z))")
+#TODO: Get working
+#ψ_z = truncate(ψ_z; cutoff=1e-12)
+println("Maximum bond dimension of the network is $(maxvirtualdim(ψ_z))")
 
 z1, z2, z3 = 0.125 + 0.5 * im, 0.625 + 0.875 * im, 0.5
 z = [z1, z2, z3]
 f_at_z = evaluate(ψ_z, z)
 println(
-  "Tensor network evaluates the function as $f_at_z at the co-ordinate: (z1,z2,z3) = ($z1, $z2, $z3)",
+    "Tensor network evaluates the function as $f_at_z at the co-ordinate: (z1,z2,z3) = ($z1, $z2, $z3)",
 )
 println(
-  "Actual value of the function is $(z1^3 * (z2  + z2^2) + cosh(pi * z3)^2) at the co-ordinate: (z1,z2,z3) =($z1, $z2, $z3)",
+    "Actual value of the function is $(z1^3 * (z2 + z2^2) + cosh(pi * z3)^2) at the co-ordinate: (z1,z2,z3) =($z1, $z2, $z3)",
 )

examples/fredholm_solver.jl

@@ -4,70 +4,73 @@ using Graphs: SimpleGraph, uniform_tree
 using NamedGraphs: NamedGraph, NamedEdge, rename_vertices, edges, vertices
 using NamedGraphs.NamedGraphGenerators: named_grid, named_comb_tree
 using ITensors:
-  ITensors,
-  ITensor,
-  Index,
-  siteinds,
-  dim,
-  tags,
-  replaceprime!,
-  MPO,
-  MPS,
-  inner,
-  Op,
-  @OpName_str,
-  @SiteType_str,
-  op
-using ITensorNetworks: ITensorNetwork, dmrg, ttn, maxlinkdim, siteinds, union_all_inds
-using Dictionaries: Dictionary
+    ITensors,
+    ITensor,
+    Index,
+    dim,
+    tags,
+    replaceprime!,
+    inner,
+    Op,
+    op
+using Dictionaries: Dictionary, set!
 using Random: seed!
+using TensorNetworkQuantumSimulator: setindex_preserve!, siteinds, tensors, tensornetwork, TensorNetwork, insert_virtualinds!
 
-using ITensorNumericalAnalysis: partial_integrate, reduced_indsnetworkmap
+function main()
 
-seed!(1234)
-L = 100
-g = named_comb_tree((2, L ÷ 2))
+    seed!(1234)
+    L = 100
+    g = named_comb_tree((2, L ÷ 2))
 
-println(
-  "########## Iteratively solve a inhomogeneous Fredholm equation of the second kind ##########",
-)
-println("solve f(x) = eˣ + ∫₀¹ (xy) f(y) dy")
-# solution: f(x) = 3x/2 + eˣ
+    println(
+        "########## Iteratively solve a inhomogeneous Fredholm equation of the second kind ##########",
+    )
+    println("solve f(x) = eˣ + ∫₀¹ (xy) f(y) dy")
+    # solution: f(x) = 3x/2 + eˣ
 
-# start f(x) = f(x)⊗1_y
-# 1. make g(x,y)
-# 2. f*g 
-# 3. apply operator I or |x>
-# 4. apply shift if any
+    # start f(x) = f(x)⊗1_y
+    # 1. make g(x,y)
+    # 2. f*g
+    # 3. apply operator I or |x>
+    # 4. apply shift if any
 
-s = continuous_siteinds(g, [[(i, j) for j in 1:(L ÷ 2)] for i in 1:2])
-dim_ψ = 2
-s1, s2 = reduced_indsnetworkmap(s, 1), reduced_indsnetworkmap(s, 2)
+    s = continuous_siteinds(g, [[(i, j) for j in 1:(L ÷ 2)] for i in 1:2])
+    dim_ψ = 2
+    s1, s2 = reduced_indexmap(s, 1), reduced_indexmap(s, 2)
 
-ψ = const_itn(s2) # f(x) = 1_x⊗1_y
+    ψ = const_tnf(g, s) # f(x) = 1_x⊗1_y
 
-# make g(x,y) = x*y
-g = poly_itn(s1, [0, 1]; dim=1) * poly_itn(s2, [0, 1]; dim=2)
+    # make g(x,y) = x*y
+    gxy = poly_tnf(g, s, [0, 1]; dim = 1) * poly_tnf(g, s, [0, 1]; dim = 2)
 
-c1, c2 = exp_itn(s1; dim=1), exp_itn(s2; dim=2)
+    c1, c2 = exp_tnf(g, s; dim = 1), exp_tnf(g, s; dim = 2)
 
-niter = 100
-for iter in 1:niter
-  global ψ = ψ * g
+    niter = 20
+    for iter in 1:niter
+        ψ = ψ * gxy
 
-  global ψ = partial_integrate(ψ, [dim_ψ])
+        ψ = partial_integrate(ψ, [dim_ψ])
 
-  global dim_ψ = dim_ψ == 1 ? 2 : 1
+        new_tensors = Dictionary(dimension_vertices(s, dim_ψ), [ITensors.ITensor([1, 1], only(siteinds(s)[v])) for v in dimension_vertices(s, dim_ψ)])
+        ψ = TensorNetwork(merge(new_tensors, tensors(tensornetwork(ψ))), g)
+        ψ = TensorNetworkFunction(ψ, s)
+        insert_virtualinds!(ψ)
 
-  local c = dim_ψ == 1 ? c1 : c2
+        dim_ψ = dim_ψ == 1 ? 2 : 1
 
-  global ψ = ψ + c
-end
+        c = dim_ψ == 1 ? c1 : c2
+
+        ψ = ψ + c
+    end
 
-n_grid = 100
-x_vals = grid_points(s, n_grid, 1)
-ψ_vals = [real(evaluate(ψ, x)) for x in x_vals]
-correct_vals = (3 / 2) * x_vals + exp.(x_vals)
+    n_grid = 100
+    x_vals = grid_points(s, n_grid, 1)
+    ψ_vals = dim_ψ == 1 ? [real(evaluate(ψ, [x, 0.5])) for x in x_vals] : [real(evaluate(ψ, [0.5, x])) for x in x_vals]
+    correct_vals = (3 / 2) * x_vals + exp.(x_vals)
+
+    avg_err = sum(abs.(correct_vals - ψ_vals)) / n_grid
+    return @show avg_err
+end
 
-avg_err = sum(abs.(correct_vals - ψ_vals)) / n_grid
-@show avg_err
+main()