remove typing on control bounds

src/problem_templates/quantum_state_sampling_problem.jl

@@ -21,9 +21,9 @@ function QuantumStateSamplingProblem(
     a_bounds=fill(a_bound, systems[1].n_drives),
     a_guess::Union{Matrix{Float64},Nothing}=nothing,
     da_bound::Float64=Inf,
-    da_bounds::Vector{Float64}=fill(da_bound, systems[1].n_drives),
+    da_bounds=fill(da_bound, systems[1].n_drives),
     dda_bound::Float64=1.0,
-    dda_bounds::Vector{Float64}=fill(dda_bound, systems[1].n_drives),
+    dda_bounds=fill(dda_bound, systems[1].n_drives),
     Δt_min::Float64=0.5 * minimum(Δt),
     Δt_max::Float64=2.0 * maximum(Δt),
     Q::Float64=100.0,

src/problem_templates/quantum_state_smooth_pulse_problem.jl

@@ -32,12 +32,12 @@ with
 - `timestep_name::Symbol=:Δt`: The name of the timestep variable.
 - `init_trajectory::Union{NamedTrajectory, Nothing}=nothing`: The initial trajectory.
 - `a_bound::Float64=1.0`: The bound on the control pulse.
-- `a_bounds::Vector{Float64}=fill(a_bound, length(system.G_drives))`: The bounds on the control pulse.
+- `a_bounds=fill(a_bound, length(system.G_drives))`: The bounds on the control pulse.
 - `a_guess::Union{Matrix{Float64}, Nothing}=nothing`: The initial guess for the control pulse.
 - `da_bound::Float64=Inf`: The bound on the first derivative of the control pulse.
-- `da_bounds::Vector{Float64}=fill(da_bound, length(system.G_drives))`: The bounds on the first derivative of the control pulse.
+- `da_bounds=fill(da_bound, length(system.G_drives))`: The bounds on the first derivative of the control pulse.
 - `dda_bound::Float64=1.0`: The bound on the second derivative of the control pulse.
-- `dda_bounds::Vector{Float64}=fill(dda_bound, length(system.G_drives))`: The bounds on the second derivative of the control pulse.
+- `dda_bounds=fill(dda_bound, length(system.G_drives))`: The bounds on the second derivative of the control pulse.
 - `Δt_min::Float64=0.5 * Δt`: The minimum timestep size.
 - `Δt_max::Float64=1.5 * Δt`: The maximum timestep size.
 - `drive_derivative_σ::Float64=0.01`: The standard deviation of the drive derivative random initialization.
@@ -63,12 +63,12 @@ function QuantumStateSmoothPulseProblem(
     timestep_name::Symbol=:Δt,
     init_trajectory::Union{NamedTrajectory, Nothing}=nothing,
     a_bound::Float64=1.0,
-    a_bounds::Vector{Float64}=fill(a_bound, sys.n_drives),
+    a_bounds=fill(a_bound, sys.n_drives),
     a_guess::Union{AbstractMatrix{Float64}, Nothing}=nothing,
     da_bound::Float64=Inf,
-    da_bounds::Vector{Float64}=fill(da_bound, sys.n_drives),
+    da_bounds=fill(da_bound, sys.n_drives),
     dda_bound::Float64=1.0,
-    dda_bounds::Vector{Float64}=fill(dda_bound, sys.n_drives),
+    dda_bounds=fill(dda_bound, sys.n_drives),
     Δt_min::Float64=0.5 * minimum(Δt),
     Δt_max::Float64=2.0 * maximum(Δt),
     Q::Float64=100.0,

src/problem_templates/unitary_sampling_problem.jl

@@ -25,12 +25,12 @@ robust solution by including multiple systems reflecting the problem uncertainty
 - `timestep_name::Symbol = :Δt`: The name of the timestep variable.
 - `constraints::Vector{<:AbstractConstraint} = AbstractConstraint[]`: The constraints.
 - `a_bound::Float64 = 1.0`: The bound for the control amplitudes.
-- `a_bounds::Vector{Float64} = fill(a_bound, length(systems[1].G_drives))`: The bounds for the control amplitudes.
+- `a_bounds = fill(a_bound, length(systems[1].G_drives))`: The bounds for the control amplitudes.
 - `a_guess::Union{Matrix{Float64}, Nothing} = nothing`: The initial guess for the control amplitudes.
 - `da_bound::Float64 = Inf`: The bound for the control first derivatives.
-- `da_bounds::Vector{Float64} = fill(da_bound, length(systems[1].G_drives))`: The bounds for the control first derivatives.
+- `da_bounds = fill(da_bound, length(systems[1].G_drives))`: The bounds for the control first derivatives.
 - `dda_bound::Float64 = 1.0`: The bound for the control second derivatives.
-- `dda_bounds::Vector{Float64} = fill(dda_bound, length(systems[1].G_drives))`: The bounds for the control second derivatives.
+- `dda_bounds = fill(dda_bound, length(systems[1].G_drives))`: The bounds for the control second derivatives.
 - `Δt_min::Float64 = 0.5 * Δt`: The minimum time step size.
 - `Δt_max::Float64 = 1.5 * Δt`: The maximum time step size.
 - `Q::Float64 = 100.0`: The fidelity weight.
@@ -58,9 +58,9 @@ function UnitarySamplingProblem(
     a_bounds=fill(a_bound, systems[1].n_drives),
     a_guess::Union{Matrix{Float64},Nothing}=nothing,
     da_bound::Float64=Inf,
-    da_bounds::Vector{Float64}=fill(da_bound, systems[1].n_drives),
+    da_bounds=fill(da_bound, systems[1].n_drives),
     dda_bound::Float64=1.0,
-    dda_bounds::Vector{Float64}=fill(dda_bound, systems[1].n_drives),
+    dda_bounds=fill(dda_bound, systems[1].n_drives),
     Δt_min::Float64=0.5 * minimum(Δt),
     Δt_max::Float64=2.0 * maximum(Δt),
     Q::Float64=100.0,

src/problem_templates/unitary_smooth_pulse_problem.jl

@@ -48,11 +48,11 @@ with
 - `init_trajectory::Union{NamedTrajectory, Nothing}=nothing`: an initial trajectory to use
 - `a_guess::Union{Matrix{Float64}, Nothing}=nothing`: an initial guess for the control pulses
 - `a_bound::Float64=1.0`: the bound on the control pulse
-- `a_bounds::Vector{Float64}=fill(a_bound, length(system.G_drives))`: the bounds on the control pulses, one for each drive
+- `a_bounds=fill(a_bound, length(system.G_drives))`: the bounds on the control pulses, one for each drive
 - `da_bound::Float64=Inf`: the bound on the control pulse derivative
-- `da_bounds::Vector{Float64}=fill(da_bound, length(system.G_drives))`: the bounds on the control pulse derivatives, one for each drive
+- `da_bounds=fill(da_bound, length(system.G_drives))`: the bounds on the control pulse derivatives, one for each drive
 - `dda_bound::Float64=1.0`: the bound on the control pulse second derivative
-- `dda_bounds::Vector{Float64}=fill(dda_bound, length(system.G_drives))`: the bounds on the control pulse second derivatives, one for each drive
+- `dda_bounds=fill(dda_bound, length(system.G_drives))`: the bounds on the control pulse second derivatives, one for each drive
 - `Δt_min::Float64=Δt isa Float64 ? 0.5 * Δt : 0.5 * mean(Δt)`: the minimum time step size
 - `Δt_max::Float64=Δt isa Float64 ? 1.5 * Δt : 1.5 * mean(Δt)`: the maximum time step size
 - `Q::Float64=100.0`: the weight on the infidelity objective
@@ -79,9 +79,9 @@ function UnitarySmoothPulseProblem(
     a_bound::Float64=1.0,
     a_bounds=fill(a_bound, system.n_drives),
     da_bound::Float64=Inf,
-    da_bounds::Vector{Float64}=fill(da_bound, system.n_drives),
+    da_bounds=fill(da_bound, system.n_drives),
     dda_bound::Float64=1.0,
-    dda_bounds::Vector{Float64}=fill(dda_bound, system.n_drives),
+    dda_bounds=fill(dda_bound, system.n_drives),
     Δt_min::Float64=0.5 * minimum(Δt),
     Δt_max::Float64=2.0 * maximum(Δt),
     Q::Float64=100.0,

src/problem_templates/unitary_variational_problem.jl

@@ -33,11 +33,11 @@ Constructs a unitary variational problem for optimizing quantum control trajecto
 - `timestep_name::Symbol`: The name of the timestep variable (default: `:Δt`).
 - `init_trajectory::Union{NamedTrajectory, Nothing}`: An optional initial trajectory to start optimization.
 - `a_bound::Float64`: The bound for the control variable `a` (default: `1.0`).
-- `a_bounds::Vector`: Bounds for each control variable (default: filled with `a_bound`).
+- `a_bounds`: Bounds for each control variable (default: filled with `a_bound`).
 - `da_bound::Float64`: The bound for the derivative of the control variable (default: `Inf`).
-- `da_bounds::Vector`: Bounds for each derivative of the control variable.
+- `da_bounds`: Bounds for each derivative of the control variable.
 - `dda_bound::Float64`: The bound for the second derivative of the control variable (default: `1.0`).
-- `dda_bounds::Vector`: Bounds for each second derivative of the control variable.
+- `dda_bounds`: Bounds for each second derivative of the control variable.
 - `Δt_min::Float64`: Minimum allowed timestep duration.
 - `Δt_max::Float64`: Maximum allowed timestep duration.
 - `Q::Float64`: Weight for the unitary infidelity objective (default: `100.0`).
@@ -78,9 +78,9 @@ function UnitaryVariationalProblem(
     a_bound::Float64=1.0,
     a_bounds=fill(a_bound, system.n_drives),
     da_bound::Float64=Inf,
-    da_bounds::Vector{Float64}=fill(da_bound, system.n_drives),
+    da_bounds=fill(da_bound, system.n_drives),
     dda_bound::Float64=1.0,
-    dda_bounds::Vector{Float64}=fill(dda_bound, system.n_drives),
+    dda_bounds=fill(dda_bound, system.n_drives),
     Δt_min::Float64=0.5 * minimum(Δt),
     Δt_max::Float64=2.0 * maximum(Δt),
     Q::Float64=100.0,