Update benchmarks to include non-abelian symmetries

Author: lkdvos

benchmark/TensorKitBenchmarks/TensorKitBenchmarks.jl

@@ -4,7 +4,7 @@ using BenchmarkTools
 using TensorKit
 using TOML
 
-BenchmarkTools.DEFAULT_PARAMETERS.seconds = 1.0
+BenchmarkTools.DEFAULT_PARAMETERS.seconds = 20.0
 BenchmarkTools.DEFAULT_PARAMETERS.samples = 10000
 BenchmarkTools.DEFAULT_PARAMETERS.time_tolerance = 0.15
 BenchmarkTools.DEFAULT_PARAMETERS.memory_tolerance = 0.01

benchmark/TensorKitBenchmarks/tensornetworks/TensorNetworkBenchmarks.jl

@@ -45,9 +45,8 @@ function benchmark_mpo!(bench; sigmas=nothing, T="Float64", I="Trivial", dims)
 end
 
 if haskey(all_parameters, "mpo")
-    g = addgroup!(SUITE, "mpo")
     for params in all_parameters["mpo"]
-        benchmark_mpo!(g, params)
+        benchmark_mpo!(SUITE, params)
     end
 end
 
@@ -90,9 +89,8 @@ function benchmark_pepo!(bench; sigmas=nothing, T="Float64", I="Trivial", dims)
 end
 
 if haskey(all_parameters, "pepo")
-    g = addgroup!(SUITE, "pepo")
     for params in all_parameters["pepo"]
-        benchmark_pepo!(g, params)
+        benchmark_pepo!(SUITE, params)
     end
 end
 
@@ -136,9 +134,8 @@ function benchmark_mera!(bench; sigmas=nothing, T="Float64", I="Trivial", dims)
 end
 
 if haskey(all_parameters, "mera")
-    g = addgroup!(SUITE, "mera")
     for params in all_parameters["mera"]
-        benchmark_mera!(g, params)
+        benchmark_mera!(SUITE, params)
     end
 end
 

benchmark/TensorKitBenchmarks/tensornetworks/benchparams.toml

@@ -19,6 +19,12 @@ I = "U1Irrep"
 dims = [[40, 5, 3], [160, 5, 3], [640, 5, 3], [2560, 5, 3], [6120, 5, 3], [200, 20, 20], [400, 20, 20], [400, 40, 40]]
 sigmas = [0.5, 0.5, 0.5]
 
+[[mpo]]
+T = ["Float64"]
+I = "SU2Irrep"
+dims = [[40, 5, 3], [160, 5, 3], [640, 5, 3], [2560, 5, 3], [6120, 5, 3], [200, 20, 20], [400, 20, 20], [400, 40, 40]]
+sigmas = [2, 2, 2]
+
 # PEPO
 # ----
 # dims = [peps, pepo, phys, env]
@@ -40,6 +46,12 @@ I = "U1Irrep"
 dims = [[4, 2, 2, 100], [4, 4, 4, 200], [6, 2, 2, 100], [6, 3, 4, 200], [8, 2, 2, 100], [8, 2, 4, 200], [10, 2, 2, 50], [10, 3, 2, 100]]
 sigmas = [0.5, 0.5, 0.5, 0.5]
 
+[[pepo]]
+T = ["Float64"]
+I = "SU2Irrep"
+dims = [[4, 2, 2, 100], [4, 4, 4, 200], [6, 2, 2, 100], [6, 3, 4, 200], [8, 2, 2, 100], [8, 2, 4, 200], [10, 2, 2, 50], [10, 3, 2, 100]]
+sigmas = [2.0, 2.0, 2.0, 2.0]
+
 # MERA
 # ----
 # dims = mera
@@ -60,3 +72,9 @@ T = ["Float64"]
 I = "U1Irrep"
 dims = [4, 8, 12, 16, 22, 28]
 sigmas = [0.5]
+
+[[mera]]
+T = ["Float64"]
+I = "SU2Irrep"
+dims = [4, 8, 12, 16, 22, 28]
+sigmas = [2.0]

benchmark/TensorKitBenchmarks/utils/BenchUtils.jl

@@ -55,13 +55,15 @@ function generate_space(::Type{U1Irrep}, D::Int, sigma::Real=0.5)
     return U1Space((s => d for (s, d) in zip(sectors, dims))...)
 end
 function generate_space(::Type{SU2Irrep}, D::Int, sigma::Real=0.5)
-    poisson_pdf(x) = ceil(Int, D * exp(-sigma) * sigma^x / factorial(x + 1))
+    normal_pdf = let D = D
+        x -> D * exp(-0.5 * (x / sigma)^2) / (sigma * sqrt(2π))
+    end
 
     sectors = SU2Irrep[]
     dims = Int[]
 
     for sector in values(SU2Irrep)
-        d = poisson_pdf(Int(sector.j * 2))
+        d = ceil(Int, normal_pdf(sector.j) / dim(sector))
         push!(sectors, sector)
         push!(dims, d)
         D -= d * dim(sector)