Fix gellmann normalisation wrt Ket v0.8.0

Author: sebastiendesignolle

Project.toml

@@ -1,7 +1,7 @@
 name = "EntanglementDetection"
 uuid = "5e5e84d8-5f53-4fe3-9037-c06c4de5d74e"
 authors = ["Y.C. Liu <yechaoliu1994@outlook.com> and contributors"]
-version = "0.2.0"
+version = "0.2.1"
 
 [deps]
 FrankWolfe = "f55ce6ea-fdc5-4628-88c5-0087fe54bd30"
@@ -20,7 +20,7 @@ EntanglementDetectionTullio = "Tullio"
 [compat]
 DoubleFloats = "1.4.0"
 FrankWolfe = "0.6"
-Ket = "0.7"
+Ket = "0.8"
 LinearAlgebra = "1"
 Printf = "1"
 Quadmath = "0.5.13"

src/utils.jl

@@ -1,10 +1,7 @@
 # Ket does not normalise gellmann the same way we do, the first element of tensor should be treated differently
-function _gellmann(::Type{CT}, dims::NTuple{N, Int}) where {CT <: Number, N}
+function _gellmann(::Type{CT}, dims::NTuple{N, Int}; coeff = 1) where {CT <: Number, N}
     T = float(real(CT))
-    matrix_basis = broadcast.(Matrix{Complex{T}}, Ket.gellmann.(Complex{T}, dims))
-    for n in 1:N
-        matrix_basis[n][1] .*= sqrt(T(2)) / sqrt(T(dims[n]))
-    end
+    matrix_basis = broadcast.(Matrix{Complex{T}}, Ket.gellmann.(Complex{T}, dims; coeff))
     return matrix_basis
 end
 

test/unit.jl

@@ -26,8 +26,8 @@ end
             @test isa(lmo, EntanglementDetection.SeparableLMO{T, N})
             @test isa(lmo, EntanglementDetection.AlternatingSeparableLMO{T, N})
             @test lmo.dims == dims
-            @test lmo.matrix_basis[1][2:end] == Ket.gellmann.(CT, dims)[1][2:end]
-            @test lmo.matrix_basis[2][1] == Ket.gellmann.(CT, dims[2])[1] * sqrt(T(2)) / sqrt(T(dims[2]))
+            @test lmo.matrix_basis[1][2:end] == Ket.gellmann.(CT, dims; coeff = 1)[1][2:end]
+            @test lmo.matrix_basis[2][1] == Ket.gellmann.(CT, dims[2]; coeff = 1)[1]
             ρ = Matrix(Ket.proj(CT, 1, prod(dims)))
             v = FrankWolfe.compute_extreme_point(lmo, EntanglementDetection.correlation_tensor(LA.I / prod(dims) - ρ, dims))
             @test EntanglementDetection.density_matrix(v) ≈ ρ