Minor changes

Author: albertomercurio

src/QuantumToolbox.jl

@@ -34,12 +34,12 @@ import DiffEqBase: get_tstops
 import DiffEqCallbacks: PeriodicCallback, PresetTimeCallback, TerminateSteadyState
 import OrdinaryDiffEqCore: OrdinaryDiffEqAlgorithm
 import OrdinaryDiffEqTsit5: Tsit5
-
-using StochasticDiffEq
+import SciMLBase: SDEProblem # add this one above
+import StochasticDiffEq: StochasticDiffEqAlgorithm, SRA1
+import DiffEqNoiseProcess: RealWienerProcess, RealWienerProcess!
 
 # other dependencies (in alphabetical order)
 import ArrayInterface: allowed_getindex, allowed_setindex!
-import DiffEqNoiseProcess: RealWienerProcess, RealWienerProcess!
 import FFTW: fft, fftshift
 import Graphs: connected_components, DiGraph
 import IncompleteLU: ilu

src/time_evolution/ssesolve.jl

@@ -66,7 +66,7 @@ end
         ψ0::QuantumObject,
         tlist::AbstractVector;
         sc_ops::Union{Nothing,AbstractVector}=nothing;
-        alg::StochasticDiffEq.StochasticDiffEqAlgorithm=SRA1()
+        alg::StochasticDiffEqAlgorithm=SRA1()
         e_ops::Union{Nothing,AbstractVector} = nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
@@ -100,18 +100,20 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `ψ0::QuantumObject`: The initial state of the system ``|\psi(0)\rangle``.
 - `tlist::AbstractVector`: The time list of the evolution.
 - `sc_ops::Union{Nothing,AbstractVector}=nothing`: List of stochastic collapse operators ``\{\hat{C}_n\}_n``.
-- `alg::StochasticDiffEq.StochasticDiffEqAlgorithm`: The algorithm used for the time evolution.
+- `alg::StochasticDiffEqAlgorithm`: The algorithm used for the time evolution.
 - `e_ops::Union{Nothing,AbstractVector}=nothing`: The list of operators to be evaluated during the evolution.
 - `H_t::Union{Nothing,Function,TimeDependentOperatorSum}`: The time-dependent Hamiltonian of the system. If `nothing`, the Hamiltonian is time-independent.
 - `params::NamedTuple`: The parameters of the system.
 - `progress_bar::Union{Val,Bool}`: Whether to show the progress bar. Using non-`Val` types might lead to type instabilities.
-- `kwargs...`: The keyword arguments passed to the `ODEProblem` constructor.
+- `kwargs...`: The keyword arguments passed to the `SDEProblem` constructor.
 
 # Notes
 
 - The states will be saved depend on the keyword argument `saveat` in `kwargs`.
 - If `e_ops` is specified, the default value of `saveat=[tlist[end]]` (only save the final state), otherwise, `saveat=tlist` (saving the states corresponding to `tlist`). You can also specify `e_ops` and `saveat` separately.
-- For more details about `alg` and extra `kwargs`, please refer to [`DifferentialEquations.jl`](https://diffeq.sciml.ai/stable/)
+- The default tolerances in `kwargs` are given as `reltol=1e-2` and `abstol=1e-2`.
+- For more details about `alg` please refer to [`DifferentialEquations.jl` (ODE Solvers)](https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/)
+- For more details about `kwargs` please refer to [`DifferentialEquations.jl` (Keyword Arguments)](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/)
 
 # Returns
 
@@ -122,7 +124,7 @@ function ssesolveProblem(
     ψ0::QuantumObject{<:AbstractArray{T2},KetQuantumObject},
     tlist::AbstractVector,
     sc_ops::Union{Nothing,AbstractVector} = nothing;
-    alg::StochasticDiffEq.StochasticDiffEqAlgorithm = SRA1(),
+    alg::StochasticDiffEqAlgorithm = SRA1(),
     e_ops::Union{Nothing,AbstractVector} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
@@ -205,7 +207,7 @@ end
         ψ0::QuantumObject,
         tlist::AbstractVector;
         sc_ops::Union{Nothing,AbstractVector} = nothing;
-        alg::StochasticDiffEq.StochasticDiffEqAlgorithm=SRA1()
+        alg::StochasticDiffEqAlgorithm=SRA1()
         e_ops::Union{Nothing,AbstractVector} = nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
@@ -240,19 +242,21 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `ψ0::QuantumObject`: The initial state of the system ``|\psi(0)\rangle``.
 - `tlist::AbstractVector`: The time list of the evolution.
 - `sc_ops::Union{Nothing,AbstractVector}=nothing`: List of stochastic collapse operators ``\{\hat{C}_n\}_n``.
-- `alg::StochasticDiffEq.StochasticDiffEqAlgorithm`: The algorithm used for the time evolution.
+- `alg::StochasticDiffEqAlgorithm`: The algorithm used for the time evolution.
 - `e_ops::Union{Nothing,AbstractVector}=nothing`: The list of operators to be evaluated during the evolution.
 - `H_t::Union{Nothing,Function,TimeDependentOperatorSum}`: The time-dependent Hamiltonian of the system. If `nothing`, the Hamiltonian is time-independent.
 - `params::NamedTuple`: The parameters of the system.
 - `prob_func::Function`: Function to use for generating the SDEProblem.
 - `output_func::Function`: Function to use for generating the output of a single trajectory.
-- `kwargs...`: The keyword arguments passed to the `ODEProblem` constructor.
+- `kwargs...`: The keyword arguments passed to the `SDEProblem` constructor.
 
 # Notes
 
 - The states will be saved depend on the keyword argument `saveat` in `kwargs`.
 - If `e_ops` is specified, the default value of `saveat=[tlist[end]]` (only save the final state), otherwise, `saveat=tlist` (saving the states corresponding to `tlist`). You can also specify `e_ops` and `saveat` separately.
-- For more details about `alg` and extra `kwargs`, please refer to [`DifferentialEquations.jl`](https://diffeq.sciml.ai/stable/)
+- The default tolerances in `kwargs` are given as `reltol=1e-2` and `abstol=1e-2`.
+- For more details about `alg` please refer to [`DifferentialEquations.jl` (SDE Solvers)](https://docs.sciml.ai/DiffEqDocs/stable/solvers/sde_solve/)
+- For more details about `kwargs` please refer to [`DifferentialEquations.jl` (Keyword Arguments)](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/)
 
 # Returns
 
@@ -263,7 +267,7 @@ function ssesolveEnsembleProblem(
     ψ0::QuantumObject{<:AbstractArray{T2},KetQuantumObject},
     tlist::AbstractVector,
     sc_ops::Union{Nothing,AbstractVector} = nothing;
-    alg::StochasticDiffEq.StochasticDiffEqAlgorithm = SRA1(),
+    alg::StochasticDiffEqAlgorithm = SRA1(),
     e_ops::Union{Nothing,AbstractVector} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
@@ -283,7 +287,7 @@ end
         ψ0::QuantumObject{<:AbstractArray{T2},KetQuantumObject},
         tlist::AbstractVector,
         sc_ops::Union{Nothing, AbstractVector}=nothing;
-        alg::StochasticDiffEq.StochasticDiffEqAlgorithm=SRA1(),
+        alg::StochasticDiffEqAlgorithm=SRA1(),
         e_ops::Union{Nothing,AbstractVector}=nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
@@ -323,7 +327,7 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `ψ0::QuantumObject`: Initial state of the system ``|\psi(0)\rangle``.
 - `tlist::AbstractVector`: List of times at which to save the state of the system.
 - `sc_ops::Union{Nothing,AbstractVector}=nothing`: List of stochastic collapse operators ``\{\hat{C}_n\}_n``.
-- `alg::StochasticDiffEq.StochasticDiffEqAlgorithm`: Algorithm to use for the time evolution.
+- `alg::StochasticDiffEqAlgorithm`: Algorithm to use for the time evolution.
 - `e_ops::Union{Nothing,AbstractVector}`: List of operators for which to calculate expectation values.
 - `H_t::Union{Nothing,Function,TimeDependentOperatorSum}`: Time-dependent part of the Hamiltonian.
 - `params::NamedTuple`: Dictionary of parameters to pass to the solver.
@@ -339,8 +343,9 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `ensemble_method` can be one of `EnsembleThreads()`, `EnsembleSerial()`, `EnsembleDistributed()`
 - The states will be saved depend on the keyword argument `saveat` in `kwargs`.
 - If `e_ops` is specified, the default value of `saveat=[tlist[end]]` (only save the final state), otherwise, `saveat=tlist` (saving the states corresponding to `tlist`). You can also specify `e_ops` and `saveat` separately.
-- The default tolerances in `kwargs` are given as `reltol=1e-6` and `abstol=1e-8`.
-- For more details about `alg` and extra `kwargs`, please refer to [`DifferentialEquations.jl`](https://diffeq.sciml.ai/stable/)
+- The default tolerances in `kwargs` are given as `reltol=1e-2` and `abstol=1e-2`.
+- For more details about `alg` please refer to [`DifferentialEquations.jl` (SDE Solvers)](https://docs.sciml.ai/DiffEqDocs/stable/solvers/sde_solve/)
+- For more details about `kwargs` please refer to [`DifferentialEquations.jl` (Keyword Arguments)](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/)
 
 # Returns
 
@@ -351,7 +356,7 @@ function ssesolve(
     ψ0::QuantumObject{<:AbstractArray{T2},KetQuantumObject},
     tlist::AbstractVector,
     sc_ops::Union{Nothing,AbstractVector} = nothing;
-    alg::StochasticDiffEq.StochasticDiffEqAlgorithm = SRA1(),
+    alg::StochasticDiffEqAlgorithm = SRA1(),
     e_ops::Union{Nothing,AbstractVector} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
@@ -380,7 +385,7 @@ end
 
 function ssesolve(
     ens_prob::EnsembleProblem;
-    alg::StochasticDiffEq.StochasticDiffEqAlgorithm = SRA1(),
+    alg::StochasticDiffEqAlgorithm = SRA1(),
     n_traj::Int = 1,
     ensemble_method = EnsembleThreads(),
 )

src/time_evolution/time_evolution.jl

@@ -124,7 +124,7 @@ struct TimeEvolutionSSESol{
     expect::TE
     expect_all::TEA
     converged::Bool
-    alg::StochasticDiffEq.StochasticDiffEqAlgorithm
+    alg::StochasticDiffEqAlgorithm
     abstol::T1
     reltol::T2
 end

test/core-test/time_evolution.jl

@@ -130,19 +130,17 @@
         end
 
         @testset "Type Inference ssesolve" begin
-            if VERSION >= v"1.10"
-                @inferred ssesolveEnsembleProblem(
-                    H,
-                    psi0,
-                    t_l,
-                    c_ops,
-                    n_traj = 500,
-                    e_ops = e_ops,
-                    progress_bar = Val(false),
-                )
-                @inferred ssesolve(H, psi0, t_l, c_ops, n_traj = 500, e_ops = e_ops, progress_bar = Val(false))
-                @inferred ssesolve(H, psi0, t_l, c_ops, n_traj = 500, progress_bar = Val(true))
-            end
+            @inferred ssesolveEnsembleProblem(
+                H,
+                psi0,
+                t_l,
+                c_ops,
+                n_traj = 500,
+                e_ops = e_ops,
+                progress_bar = Val(false),
+            )
+            @inferred ssesolve(H, psi0, t_l, c_ops, n_traj = 500, e_ops = e_ops, progress_bar = Val(false))
+            @inferred ssesolve(H, psi0, t_l, c_ops, n_traj = 500, progress_bar = Val(true))
         end
     end