Restruct

src/algorithm/algorithm.jl → src/algorithm.jl

@@ -1 +1,2 @@
 abstract type AbstractAlgorithm end
+

src/dynamics/dynamics.jl → src/dynamics.jl

@@ -12,6 +12,7 @@ abstract type noisy <: AbstractNoise end
 abstract type AbstractCtrl end
 abstract type free <: AbstractCtrl end
 abstract type controlled <: AbstractCtrl end
+abstract type timedepend <: AbstractCtrl end
 
 # check if the dynamics are with noise
 isNoisy(::noiseless) = false
@@ -21,5 +22,7 @@ isNoisy(dynamics::AbstractDynamics) = dynamics.noise_type|>eval|>isNoisy
 # check if the dynamics are in control
 isCtrl(::free) = false
 isCtrl(::controlled) = true
-isCtrl(dynamics::AbstractDynamics) = dynamcs.ctrl_type|>eval|>isCtrl
+isCtrl(dynamics::AbstractDynamics) = dynamics.ctrl_type|>eval|>isCtrl
 
+include("dynamics/Lindblad.jl")
+include("dynamics/Kraus.jl")

src/dynamics/Kraus.jl

@@ -21,3 +21,22 @@ end
 # Constructor for Kraus dynamics
 Kraus(K::AbstractVector, dK::AbstractVector, ρ::AbstractMatrix) = Kraus{dm}(Kraus_data(K,dK,ρ), :noiseless, :free, :dm)
 Kraus(K::AbstractVector, dK::AbstractVector, ψ::AbstractVector) = Kraus{ket}(Kraus_data(K,dK,ψ), :noiseless, :free, :ket)
+
+#### evolution of pure states under time-independent Hamiltonian without noise and controls ####
+function evolve(dynamics::Kraus{noiseless, free, ket})
+    (K, dK, ψ₀) = dynamics
+    ρ₀ = ψ₀*ψ₀'
+    ρ = [K*ρ₀*K' for K in K]|>sum
+    dρ = [[dK*ρ₀*K' + K*ρ₀*dK']|>sum for dK in dK]
+
+    ρ, dρ
+end
+
+#### evolution of density matrix under time-independent Hamiltonian without noise and controls ####
+function evolve(dynamics::Kraus{noiseless, free, dm})
+    (K, dK, ρ₀) = dynamics
+    ρ = [K*ρ₀*K' for K in K]|>sum
+    dρ = [[dK*ρ₀*K' + K*ρ₀*dK']|>sum for dK in dK]
+
+    ρ, dρ
+end

src/objective.jl

@@ -0,0 +1,6 @@
+abstract type AbstractObj end
+abstract type AbstractObjData end
+
+
+include("AsymptoticBound/CramerRao.jl")
+include("AsymptoticBound/Holevo")