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Feb 13, 2025
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Improve ensemble generation of ssesolve and change parameters on stochastic processes #403

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d03eed5
Simply structure of parameters in smesolve
albertomercurio Feb 13, 2025
b01ecb5
Improve ensemble generation of ssesolve
albertomercurio Feb 13, 2025
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Add changelog
albertomercurio Feb 13, 2025
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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Fix `smesolve` for specifying initial state as density matrix. ([#395])
- Add more generic solver for `steadystate_floquet` to allow more linear solvers. ([#396])
- Fix time evolution output when using `saveat` keyword argument. ([#398])
- Improve ensemble generation of `ssesolve` and change parameters handling on stochastic processes. ([#403])

## [v0.26.0]
Release date: 2025-02-09
Expand Down Expand Up @@ -128,3 +129,4 @@ Release date: 2024-11-13
[#395]: https://github.com/qutip/QuantumToolbox.jl/issues/395
[#396]: https://github.com/qutip/QuantumToolbox.jl/issues/396
[#398]: https://github.com/qutip/QuantumToolbox.jl/issues/398
[#403]: https://github.com/qutip/QuantumToolbox.jl/issues/403
39 changes: 23 additions & 16 deletions src/time_evolution/smesolve.jl
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Expand Up @@ -17,7 +17,7 @@ _smesolve_ScalarOperator(op_vec) =
c_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
sc_ops::Union{Nothing,AbstractVector,Tuple} = nothing;
e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
params::NamedTuple = NamedTuple(),
params = NullParameters(),
rng::AbstractRNG = default_rng(),
progress_bar::Union{Val,Bool} = Val(true),
kwargs...,
Expand Down Expand Up @@ -51,7 +51,7 @@ Above, ``\hat{C}_i`` represent the collapse operators related to pure dissipatio
- `c_ops`: List of collapse operators ``\{\hat{C}_i\}_i``. It can be either a `Vector` or a `Tuple`.
- `sc_ops`: List of stochastic collapse operators ``\{\hat{S}_n\}_n``. It can be either a `Vector` or a `Tuple`.
- `e_ops`: List of operators for which to calculate expectation values. It can be either a `Vector` or a `Tuple`.
- `params`: `NamedTuple` of parameters to pass to the solver.
- `params`: `NullParameters` of parameters to pass to the solver.
- `rng`: Random number generator for reproducibility.
- `progress_bar`: Whether to show the progress bar. Using non-`Val` types might lead to type instabilities.
- `kwargs`: The keyword arguments for the ODEProblem.
Expand All @@ -74,7 +74,7 @@ function smesolveProblem(
c_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
sc_ops::Union{Nothing,AbstractVector,Tuple} = nothing;
e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
params::NamedTuple = NamedTuple(),
params = NullParameters(),
rng::AbstractRNG = default_rng(),
progress_bar::Union{Val,Bool} = Val(true),
kwargs...,
Expand Down Expand Up @@ -110,16 +110,23 @@ function smesolveProblem(
end
D = DiffusionOperator(D_l)

p = (progr = progr, times = tlist, Hdims = dims, n_sc_ops = length(sc_ops), params...)

kwargs2 = _merge_saveat(tlist, e_ops, DEFAULT_SDE_SOLVER_OPTIONS; kwargs...)
kwargs3 = _generate_se_me_kwargs(e_ops, makeVal(progress_bar), tlist, kwargs2, SaveFuncMESolve)

tspan = (tlist[1], tlist[end])
noise =
RealWienerProcess!(tlist[1], zeros(length(sc_ops)), zeros(length(sc_ops)), save_everystep = false, rng = rng)
noise_rate_prototype = similar(ρ0, length(ρ0), length(sc_ops))
prob = SDEProblem{true}(K, D, ρ0, tspan, p; noise_rate_prototype = noise_rate_prototype, noise = noise, kwargs3...)
prob = SDEProblem{true}(
K,
D,
ρ0,
tspan,
params;
noise_rate_prototype = noise_rate_prototype,
noise = noise,
kwargs3...,
)

return TimeEvolutionProblem(prob, tlist, dims)
end
Expand All @@ -132,7 +139,7 @@ end
c_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
sc_ops::Union{Nothing,AbstractVector,Tuple} = nothing;
e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
params::NamedTuple = NamedTuple(),
params = NullParameters(),
rng::AbstractRNG = default_rng(),
ntraj::Int = 1,
ensemble_method = EnsembleThreads(),
Expand Down Expand Up @@ -170,11 +177,11 @@ Above, ``\hat{C}_i`` represent the collapse operators related to pure dissipatio
- `c_ops`: List of collapse operators ``\{\hat{C}_i\}_i``. It can be either a `Vector` or a `Tuple`.
- `sc_ops`: List of stochastic collapse operators ``\{\hat{S}_n\}_n``. It can be either a `Vector` or a `Tuple`.
- `e_ops`: List of operators for which to calculate expectation values. It can be either a `Vector` or a `Tuple`.
- `params`: `NamedTuple` of parameters to pass to the solver.
- `params`: `NullParameters` of parameters to pass to the solver.
- `rng`: Random number generator for reproducibility.
- `ntraj`: Number of trajectories to use.
- `ensemble_method`: Ensemble method to use. Default to `EnsembleThreads()`.
- `prob_func`: Function to use for generating the ODEProblem.
- `prob_func`: Function to use for generating the SDEProblem.
- `output_func`: a `Tuple` containing the `Function` to use for generating the output of a single trajectory, the (optional) `ProgressBar` object, and the (optional) `RemoteChannel` object.
- `progress_bar`: Whether to show the progress bar. Using non-`Val` types might lead to type instabilities.
- `kwargs`: The keyword arguments for the ODEProblem.
Expand All @@ -197,7 +204,7 @@ function smesolveEnsembleProblem(
c_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
sc_ops::Union{Nothing,AbstractVector,Tuple} = nothing;
e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
params::NamedTuple = NamedTuple(),
params = NullParameters(),
rng::AbstractRNG = default_rng(),
ntraj::Int = 1,
ensemble_method = EnsembleThreads(),
Expand All @@ -207,7 +214,8 @@ function smesolveEnsembleProblem(
kwargs...,
) where {StateOpType<:Union{KetQuantumObject,OperatorQuantumObject}}
_prob_func =
isnothing(prob_func) ? _ensemble_dispatch_prob_func(rng, ntraj, tlist, _stochastic_prob_func) : prob_func
isnothing(prob_func) ?
_ensemble_dispatch_prob_func(rng, ntraj, tlist, _stochastic_prob_func; n_sc_ops = length(sc_ops)) : prob_func
_output_func =
output_func isa Nothing ?
_ensemble_dispatch_output_func(ensemble_method, progress_bar, ntraj, _stochastic_output_func) : output_func
Expand Down Expand Up @@ -244,7 +252,7 @@ end
sc_ops::Union{Nothing,AbstractVector,Tuple} = nothing;
alg::StochasticDiffEqAlgorithm = SRA1(),
e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
params::NamedTuple = NamedTuple(),
params = NullParameters(),
rng::AbstractRNG = default_rng(),
ntraj::Int = 1,
ensemble_method = EnsembleThreads(),
Expand Down Expand Up @@ -283,11 +291,11 @@ Above, ``\hat{C}_i`` represent the collapse operators related to pure dissipatio
- `sc_ops`: List of stochastic collapse operators ``\{\hat{S}_n\}_n``. It can be either a `Vector` or a `Tuple`.
- `alg`: The algorithm to use for the stochastic differential equation. Default is `SRA1()`.
- `e_ops`: List of operators for which to calculate expectation values. It can be either a `Vector` or a `Tuple`.
- `params`: `NamedTuple` of parameters to pass to the solver.
- `params`: `NullParameters` of parameters to pass to the solver.
- `rng`: Random number generator for reproducibility.
- `ntraj`: Number of trajectories to use.
- `ensemble_method`: Ensemble method to use. Default to `EnsembleThreads()`.
- `prob_func`: Function to use for generating the ODEProblem.
- `prob_func`: Function to use for generating the SDEProblem.
- `output_func`: a `Tuple` containing the `Function` to use for generating the output of a single trajectory, the (optional) `ProgressBar` object, and the (optional) `RemoteChannel` object.
- `progress_bar`: Whether to show the progress bar. Using non-`Val` types might lead to type instabilities.
- `kwargs`: The keyword arguments for the ODEProblem.
Expand All @@ -311,7 +319,7 @@ function smesolve(
sc_ops::Union{Nothing,AbstractVector,Tuple} = nothing;
alg::StochasticDiffEqAlgorithm = SRA1(),
e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
params::NamedTuple = NamedTuple(),
params = NullParameters(),
rng::AbstractRNG = default_rng(),
ntraj::Int = 1,
ensemble_method = EnsembleThreads(),
Expand Down Expand Up @@ -351,7 +359,6 @@ function smesolve(
_sol_1 = sol[:, 1]
_expvals_sol_1 = _se_me_sse_get_expvals(_sol_1)

normalize_states = Val(false)
dims = ens_prob.dimensions
_expvals_all = _expvals_sol_1 isa Nothing ? nothing : map(i -> _se_me_sse_get_expvals(sol[:, i]), eachindex(sol))
expvals_all = _expvals_all isa Nothing ? nothing : stack(_expvals_all)
Expand Down
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