Improve random number generation on mcsolve and ssesolve (#263)

src/QuantumToolbox.jl

@@ -47,7 +47,7 @@ import FFTW: fft, fftshift
 import Graphs: connected_components, DiGraph
 import IncompleteLU: ilu
 import Pkg
-import Random
+import Random: AbstractRNG, default_rng, seed!
 import SpecialFunctions: loggamma
 import StaticArraysCore: MVector
 

src/time_evolution/mcsolve.jl

@@ -29,21 +29,20 @@ function LindbladJumpAffect!(integrator)
     random_n = internal_params.random_n
     jump_times = internal_params.jump_times
     jump_which = internal_params.jump_which
+    traj_rng = internal_params.traj_rng
     ψ = integrator.u
 
     @inbounds for i in eachindex(weights_mc)
         mul!(cache_mc, c_ops[i], ψ)
         weights_mc[i] = real(dot(cache_mc, cache_mc))
     end
     cumsum!(cumsum_weights_mc, weights_mc)
-    collaps_idx = getindex(1:length(weights_mc), findfirst(>(rand() * sum(weights_mc)), cumsum_weights_mc))
+    collaps_idx = getindex(1:length(weights_mc), findfirst(>(rand(traj_rng) * sum(weights_mc)), cumsum_weights_mc))
     mul!(cache_mc, c_ops[collaps_idx], ψ)
     normalize!(cache_mc)
     copyto!(integrator.u, cache_mc)
 
-    # push!(jump_times, integrator.t)
-    # push!(jump_which, collaps_idx)
-    random_n[] = rand()
+    random_n[] = rand(traj_rng)
     jump_times[internal_params.jump_times_which_idx[]] = integrator.t
     jump_which[internal_params.jump_times_which_idx[]] = collaps_idx
     internal_params.jump_times_which_idx[] += 1
@@ -59,8 +58,11 @@ LindbladJumpDiscreteCondition(u, t, integrator) = real(dot(u, u)) < integrator.p
 
 function _mcsolve_prob_func(prob, i, repeat)
     internal_params = prob.p
-    seeds = internal_params.seeds
-    !isnothing(seeds) && Random.seed!(seeds[i])
+
+    global_rng = internal_params.global_rng
+    seed = internal_params.seeds[i]
+    traj_rng = typeof(global_rng)()
+    seed!(traj_rng, seed)
 
     prm = merge(
         internal_params,
@@ -69,7 +71,8 @@ function _mcsolve_prob_func(prob, i, repeat)
             cache_mc = similar(internal_params.cache_mc),
             weights_mc = similar(internal_params.weights_mc),
             cumsum_weights_mc = similar(internal_params.weights_mc),
-            random_n = Ref(rand()),
+            traj_rng = traj_rng,
+            random_n = Ref(rand(traj_rng)),
             progr_mc = ProgressBar(size(internal_params.expvals, 2), enable = false),
             jump_times_which_idx = Ref(1),
             jump_times = similar(internal_params.jump_times),
@@ -122,6 +125,7 @@ end
         e_ops::Union{Nothing,AbstractVector,Tuple}=nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
+        rng::AbstractRNG=default_rng(),
         jump_callback::TJC=ContinuousLindbladJumpCallback(),
         kwargs...)
 
@@ -169,7 +173,7 @@ If the environmental measurements register a quantum jump, the wave function und
 - `e_ops::Union{Nothing,AbstractVector,Tuple}`: 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.
-- `seeds::Union{Nothing, Vector{Int}}`: List of seeds for the random number generator. Length must be equal to the number of trajectories provided.
+- `rng::AbstractRNG`: Random number generator for reproducibility.
 - `jump_callback::LindbladJumpCallbackType`: The Jump Callback type: Discrete or Continuous.
 - `kwargs...`: Additional keyword arguments to pass to the solver.
 
@@ -194,7 +198,7 @@ function mcsolveProblem(
     e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
-    seeds::Union{Nothing,Vector{Int}} = nothing,
+    rng::AbstractRNG = default_rng(),
     jump_callback::TJC = ContinuousLindbladJumpCallback(),
     kwargs...,
 ) where {MT1<:AbstractMatrix,TJC<:LindbladJumpCallbackType}
@@ -238,8 +242,7 @@ function mcsolveProblem(
         e_ops_mc = e_ops2,
         is_empty_e_ops_mc = is_empty_e_ops_mc,
         progr_mc = ProgressBar(length(t_l), enable = false),
-        seeds = seeds,
-        random_n = Ref(rand()),
+        traj_rng = rng,
         c_ops = get_data.(c_ops),
         cache_mc = cache_mc,
         weights_mc = weights_mc,
@@ -361,7 +364,7 @@ If the environmental measurements register a quantum jump, the wave function und
 - `e_ops::Union{Nothing,AbstractVector,Tuple}`: 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.
-- `seeds::Union{Nothing, Vector{Int}}`: List of seeds for the random number generator. Length must be equal to the number of trajectories provided.
+- `rng::AbstractRNG`: Random number generator for reproducibility.
 - `ntraj::Int`: Number of trajectories to use.
 - `ensemble_method`: Ensemble method to use.
 - `jump_callback::LindbladJumpCallbackType`: The Jump Callback type: Discrete or Continuous.
@@ -391,10 +394,10 @@ function mcsolveEnsembleProblem(
     e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
+    rng::AbstractRNG = default_rng(),
     ntraj::Int = 1,
     ensemble_method = EnsembleThreads(),
     jump_callback::TJC = ContinuousLindbladJumpCallback(),
-    seeds::Union{Nothing,Vector{Int}} = nothing,
     prob_func::Function = _mcsolve_prob_func,
     output_func::Function = _mcsolve_dispatch_output_func(ensemble_method),
     progress_bar::Union{Val,Bool} = Val(true),
@@ -413,6 +416,7 @@ function mcsolveEnsembleProblem(
 
     # Stop the async task if an error occurs
     try
+        seeds = map(i -> rand(rng, UInt64), 1:ntraj)
         prob_mc = mcsolveProblem(
             H,
             ψ0,
@@ -421,8 +425,8 @@ function mcsolveEnsembleProblem(
             alg = alg,
             e_ops = e_ops,
             H_t = H_t,
-            params = params,
-            seeds = seeds,
+            params = merge(params, (global_rng = rng, seeds = seeds)),
+            rng = rng,
             jump_callback = jump_callback,
             kwargs...,
         )
@@ -447,7 +451,7 @@ end
         e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
         params::NamedTuple = NamedTuple(),
-        seeds::Union{Nothing,Vector{Int}} = nothing,
+        rng::AbstractRNG = default_rng(),
         ntraj::Int = 1,
         ensemble_method = EnsembleThreads(),
         jump_callback::TJC = ContinuousLindbladJumpCallback(),
@@ -501,7 +505,7 @@ If the environmental measurements register a quantum jump, the wave function und
 - `e_ops::Union{Nothing,AbstractVector,Tuple}`: 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.
-- `seeds::Union{Nothing, Vector{Int}}`: List of seeds for the random number generator. Length must be equal to the number of trajectories provided.
+- `rng::AbstractRNG`: Random number generator for reproducibility.
 - `ntraj::Int`: Number of trajectories to use.
 - `ensemble_method`: Ensemble method to use.
 - `jump_callback::LindbladJumpCallbackType`: The Jump Callback type: Discrete or Continuous.
@@ -532,7 +536,7 @@ function mcsolve(
     e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
-    seeds::Union{Nothing,Vector{Int}} = nothing,
+    rng::AbstractRNG = default_rng(),
     ntraj::Int = 1,
     ensemble_method = EnsembleThreads(),
     jump_callback::TJC = ContinuousLindbladJumpCallback(),
@@ -541,10 +545,6 @@ function mcsolve(
     progress_bar::Union{Val,Bool} = Val(true),
     kwargs...,
 ) where {MT1<:AbstractMatrix,T2,TJC<:LindbladJumpCallbackType}
-    if !isnothing(seeds) && length(seeds) != ntraj
-        throw(ArgumentError("Length of seeds must match ntraj ($ntraj), but got $(length(seeds))"))
-    end
-
     ens_prob_mc = mcsolveEnsembleProblem(
         H,
         ψ0,
@@ -554,7 +554,7 @@ function mcsolve(
         e_ops = e_ops,
         H_t = H_t,
         params = params,
-        seeds = seeds,
+        rng = rng,
         ntraj = ntraj,
         ensemble_method = ensemble_method,
         jump_callback = jump_callback,

src/time_evolution/ssesolve.jl

@@ -32,11 +32,17 @@ end
 function _ssesolve_prob_func(prob, i, repeat)
     internal_params = prob.p
 
+    global_rng = internal_params.global_rng
+    seed = internal_params.seeds[i]
+    traj_rng = typeof(global_rng)()
+    seed!(traj_rng, seed)
+
     noise = RealWienerProcess(
         prob.tspan[1],
         zeros(length(internal_params.sc_ops)),
         zeros(length(internal_params.sc_ops)),
         save_everystep = false,
+        rng = traj_rng,
     )
 
     noise_rate_prototype = similar(prob.u0, length(prob.u0), length(internal_params.sc_ops))
@@ -49,7 +55,7 @@ function _ssesolve_prob_func(prob, i, repeat)
         ),
     )
 
-    return remake(prob, p = prm, noise = noise, noise_rate_prototype = noise_rate_prototype)
+    return remake(prob, p = prm, noise = noise, noise_rate_prototype = noise_rate_prototype, seed = seed)
 end
 
 # Standard output function
@@ -89,6 +95,7 @@ end
         e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
+        rng::AbstractRNG=default_rng(),
         kwargs...)
 
 Generates the SDEProblem for the Stochastic Schrödinger time evolution of a quantum system. This is defined by the following stochastic differential equation:
@@ -122,6 +129,7 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `e_ops::Union{Nothing,AbstractVector,Tuple}=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.
+- `rng::AbstractRNG`: The random number generator for reproducibility.
 - `kwargs...`: The keyword arguments passed to the `SDEProblem` constructor.
 
 # Notes
@@ -145,6 +153,7 @@ function ssesolveProblem(
     e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
+    rng::AbstractRNG = default_rng(),
     kwargs...,
 ) where {MT1<:AbstractMatrix,T2}
     H.dims != ψ0.dims && throw(DimensionMismatch("The two quantum objects are not of the same Hilbert dimension."))
@@ -200,7 +209,7 @@ function ssesolveProblem(
     kwargs3 = _generate_sesolve_kwargs(e_ops, Val(false), t_l, kwargs2)
 
     tspan = (t_l[1], t_l[end])
-    noise = RealWienerProcess(t_l[1], zeros(length(sc_ops)), zeros(length(sc_ops)), save_everystep = false)
+    noise = RealWienerProcess(t_l[1], zeros(length(sc_ops)), zeros(length(sc_ops)), save_everystep = false, rng = rng)
     noise_rate_prototype = similar(ϕ0, length(ϕ0), length(sc_ops))
     return SDEProblem{true}(
         ssesolve_drift!,
@@ -223,6 +232,7 @@ end
         e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
+        rng::AbstractRNG=default_rng(),
         ntraj::Int=1,
         ensemble_method=EnsembleThreads(),
         prob_func::Function=_mcsolve_prob_func,
@@ -261,6 +271,7 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `e_ops::Union{Nothing,AbstractVector,Tuple}=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.
+- `rng::AbstractRNG`: The random number generator for reproducibility.
 - `ntraj::Int`: Number of trajectories to use.
 - `ensemble_method`: Ensemble method to use.
 - `prob_func::Function`: Function to use for generating the SDEProblem.
@@ -289,6 +300,7 @@ function ssesolveEnsembleProblem(
     e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
+    rng::AbstractRNG = default_rng(),
     ntraj::Int = 1,
     ensemble_method = EnsembleThreads(),
     prob_func::Function = _ssesolve_prob_func,
@@ -309,10 +321,21 @@ function ssesolveEnsembleProblem(
 
     # Stop the async task if an error occurs
     try
-        prob_sse =
-            ssesolveProblem(H, ψ0, tlist, sc_ops; alg = alg, e_ops = e_ops, H_t = H_t, params = params, kwargs...)
+        seeds = map(i -> rand(rng, UInt64), 1:ntraj)
+        prob_sse = ssesolveProblem(
+            H,
+            ψ0,
+            tlist,
+            sc_ops;
+            alg = alg,
+            e_ops = e_ops,
+            H_t = H_t,
+            params = merge(params, (global_rng = rng, seeds = seeds)),
+            rng = rng,
+            kwargs...,
+        )
 
-        ensemble_prob = EnsembleProblem(prob_sse, prob_func = prob_func, output_func = output_func, safetycopy = false)
+        ensemble_prob = EnsembleProblem(prob_sse, prob_func = prob_func, output_func = output_func, safetycopy = true)
 
         return ensemble_prob
     catch e
@@ -332,6 +355,7 @@ end
         e_ops::Union{Nothing,AbstractVector,Tuple}=nothing,
         H_t::Union{Nothing,Function,TimeDependentOperatorSum}=nothing,
         params::NamedTuple=NamedTuple(),
+        rng::AbstractRNG=default_rng(),
         ntraj::Int=1,
         ensemble_method=EnsembleThreads(),
         prob_func::Function=_ssesolve_prob_func,
@@ -373,7 +397,7 @@ Above, `C_n` is the `n`-th collapse operator and  `dW_j(t)` is the real Wiener i
 - `e_ops::Union{Nothing,AbstractVector,Tuple}`: 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.
-- `seeds::Union{Nothing, Vector{Int}}`: List of seeds for the random number generator. Length must be equal to the number of trajectories provided.
+- `rng::AbstractRNG`: Random number generator for reproducibility.
 - `ntraj::Int`: Number of trajectories to use.
 - `ensemble_method`: Ensemble method to use.
 - `prob_func::Function`: Function to use for generating the SDEProblem.
@@ -403,6 +427,7 @@ function ssesolve(
     e_ops::Union{Nothing,AbstractVector,Tuple} = nothing,
     H_t::Union{Nothing,Function,TimeDependentOperatorSum} = nothing,
     params::NamedTuple = NamedTuple(),
+    rng::AbstractRNG = default_rng(),
     ntraj::Int = 1,
     ensemble_method = EnsembleThreads(),
     prob_func::Function = _ssesolve_prob_func,
@@ -425,6 +450,7 @@ function ssesolve(
         e_ops = e_ops,
         H_t = H_t,
         params = params,
+        rng = rng,
         ntraj = ntraj,
         ensemble_method = ensemble_method,
         prob_func = prob_func,

test/core-test/time_evolution.jl

@@ -149,6 +149,50 @@
             @inferred ssesolve(H, psi0, t_l, c_ops, ntraj = 500, e_ops = e_ops, progress_bar = Val(false))
             @inferred ssesolve(H, psi0, t_l, c_ops, ntraj = 500, progress_bar = Val(true))
         end
+
+        @testset "mcsolve and ssesolve reproducibility" begin
+            N = 10
+            a = tensor(destroy(N), qeye(2))
+            σm = tensor(qeye(N), sigmam())
+            σp = σm'
+            σz = tensor(qeye(N), sigmaz())
+
+            ω = 1.0
+            g = 0.1
+            γ = 0.01
+            nth = 0.1
+
+            H = ω * a' * a + ω * σz / 2 + g * (a' * σm + a * σp)
+            c_ops = [sqrt(γ * (1 + nth)) * a, sqrt(γ * nth) * a', sqrt(γ * (1 + nth)) * σm, sqrt(γ * nth) * σp]
+            e_ops = [a' * a, σz]
+
+            psi0 = tensor(basis(N, 0), basis(2, 0))
+            tlist = range(0, 20 / γ, 1000)
+
+            rng = MersenneTwister(1234)
+            sleep(0.1) # If we don't sleep, we get an error (why?)
+            sol_mc1 = mcsolve(H, psi0, tlist, c_ops, ntraj = 500, e_ops = e_ops, progress_bar = Val(false), rng = rng)
+            sol_sse1 = ssesolve(H, psi0, tlist, c_ops, ntraj = 50, e_ops = e_ops, progress_bar = Val(false), rng = rng)
+
+            rng = MersenneTwister(1234)
+            sleep(0.1)
+            sol_mc2 = mcsolve(H, psi0, tlist, c_ops, ntraj = 500, e_ops = e_ops, progress_bar = Val(false), rng = rng)
+            sol_sse2 = ssesolve(H, psi0, tlist, c_ops, ntraj = 50, e_ops = e_ops, progress_bar = Val(false), rng = rng)
+
+            rng = MersenneTwister(1234)
+            sleep(0.1)
+            sol_mc3 = mcsolve(H, psi0, tlist, c_ops, ntraj = 510, e_ops = e_ops, progress_bar = Val(false), rng = rng)
+
+            @test sol_mc1.expect ≈ sol_mc2.expect atol = 1e-10
+            @test sol_mc1.expect_all ≈ sol_mc2.expect_all atol = 1e-10
+            @test sol_mc1.jump_times ≈ sol_mc2.jump_times atol = 1e-10
+            @test sol_mc1.jump_which ≈ sol_mc2.jump_which atol = 1e-10
+
+            @test sol_mc1.expect_all ≈ sol_mc3.expect_all[1:500, :, :] atol = 1e-10
+
+            @test sol_sse1.expect ≈ sol_sse2.expect atol = 1e-10
+            @test sol_sse1.expect_all ≈ sol_sse2.expect_all atol = 1e-10
+        end
     end
 
     @testset "exceptions" begin

test/runtests.jl

@@ -2,6 +2,7 @@ using Test
 using Pkg
 using QuantumToolbox
 using QuantumToolbox: position, momentum
+using Random
 
 const GROUP = get(ENV, "GROUP", "All")