Broadcasting Kets and Operators

.github/workflows/ci.yml

@@ -25,7 +25,7 @@ jobs:
         include:
           - os: ubuntu-latest
             arch: x64
-            version: '1.6'
+            version: '1.10'
     steps:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v2

Project.toml

@@ -13,6 +13,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 QuantumInterface = "5717a53b-5d69-4fa3-b976-0bf2f97ca1e5"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RandomMatrices = "2576dda1-a324-5b11-aa66-c48ed7e3c618"
+RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Strided = "5e0ebb24-38b0-5f93-81fe-25c709ecae67"
 UnsafeArrays = "c4a57d5a-5b31-53a6-b365-19f8c011fbd6"
@@ -28,7 +29,8 @@ LinearAlgebra = "1"
 QuantumInterface = "0.3.3"
 Random = "1"
 RandomMatrices = "0.5"
+RecursiveArrayTools = "3"
 SparseArrays = "1"
 Strided = "1, 2"
 UnsafeArrays = "1"
-julia = "1.6"
+julia = "1.10"

src/QuantumOpticsBase.jl

@@ -2,6 +2,7 @@ module QuantumOpticsBase
 
 using SparseArrays, LinearAlgebra, LRUCache, Strided, UnsafeArrays, FillArrays
 import LinearAlgebra: mul!, rmul!
+import RecursiveArrayTools
 
 import QuantumInterface: dagger, directsum, ⊕, dm, embed, nsubsystems, expect, identityoperator, identitysuperoperator,
         permutesystems, projector, ptrace, reduced, tensor, ⊗, variance, apply!, basis, AbstractSuperOperator

src/operators_dense.jl

@@ -420,37 +420,50 @@
 Broadcast.BroadcastStyle(::Type{<:Operator{BL,BR}}) where {BL,BR} = OperatorStyle{BL,BR}()
 Broadcast.BroadcastStyle(::OperatorStyle{B1,B2}, ::OperatorStyle{B3,B4}) where {B1,B2,B3,B4} = throw(IncompatibleBases())
 
+# Broadcast with scalars (of use in ODE solvers checking for tolerances, e.g. `.* reltol .+ abstol`)
+Broadcast.BroadcastStyle(::T, ::Broadcast.DefaultArrayStyle{0}) where {Bl<:Basis, Br<:Basis, T<:OperatorStyle{Bl,Br}} = T()
+
 # Out-of-place broadcasting
 @inline function Base.copy(bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {BL,BR,Style<:OperatorStyle{BL,BR},Axes,F,Args<:Tuple}
     bcf = Broadcast.flatten(bc)
     bl,br = find_basis(bcf.args)
-    bc_ = Broadcasted_restrict_f(bcf.f, bcf.args, axes(bcf))
-    return Operator{BL,BR}(bl, br, copy(bc_))
+    T = find_dType(bcf)
+    data = zeros(T, length(bl), length(br))
+    @inbounds @simd for I in eachindex(bcf)
+        data[I] = bcf[I]
+    end
+    return Operator{BL,BR}(bl, br, data)
 end
-find_basis(a::DataOperator, rest) = (a.basis_l, a.basis_r)
 
-const BasicMathFunc = Union{typeof(+),typeof(-),typeof(*)}
-function Broadcasted_restrict_f(f::BasicMathFunc, args::Tuple{Vararg{<:DataOperator}}, axes)
-    args_ = Tuple(a.data for a=args)
-    return Broadcast.Broadcasted(f, args_, axes)
-end
+find_basis(a::DataOperator, rest) = (a.basis_l, a.basis_r)
+find_dType(a::DataOperator, rest) = eltype(a)
+@inline Base.getindex(a::DataOperator, idx) = getindex(a.data, idx)
+Base.@propagate_inbounds Base.Broadcast._broadcast_getindex(x::DataOperator, i) = x.data[i]
+Base.iterate(a::DataOperator) = iterate(a.data)
+Base.iterate(a::DataOperator, idx) = iterate(a.data, idx)
 
 # In-place broadcasting
 @inline function Base.copyto!(dest::DataOperator{BL,BR}, bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {BL,BR,Style<:DataOperatorStyle{BL,BR},Axes,F,Args}
     axes(dest) == axes(bc) || Base.Broadcast.throwdm(axes(dest), axes(bc))
-    # Performance optimization: broadcast!(identity, dest, A) is equivalent to copyto!(dest, A) if indices match
-    if bc.f === identity && isa(bc.args, Tuple{<:DataOperator{BL,BR}}) # only a single input argument to broadcast!
-        A = bc.args[1]
-        if axes(dest) == axes(A)
-            return copyto!(dest, A)
-        end
+    bc′ = Base.Broadcast.preprocess(dest, bc)
+    dest′ = dest.data
+    @inbounds @simd for I in eachindex(bc′)
+        dest′[I] = bc′[I]
     end
-    # Get the underlying data fields of operators and broadcast them as arrays
-    bcf = Broadcast.flatten(bc)
-    bc_ = Broadcasted_restrict_f(bcf.f, bcf.args, axes(bcf))
-    copyto!(dest.data, bc_)
     return dest
 end
 @inline Base.copyto!(A::DataOperator{BL,BR},B::DataOperator{BL,BR}) where {BL,BR} = (copyto!(A.data,B.data); A)
 @inline Base.copyto!(dest::DataOperator{BL,BR}, bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {BL,BR,Style<:DataOperatorStyle,Axes,F,Args} =
     throw(IncompatibleBases())
+
+# A few more standard interfaces: These do not necessarily make sense for a StateVector, but enable transparent use of DifferentialEquations.jl
+Base.eltype(::Type{Operator{Bl,Br,A}}) where {Bl,Br,N,A<:AbstractMatrix{N}} = N # ODE init
+Base.any(f::Function, x::Operator; kwargs...) = any(f, x.data; kwargs...) # ODE nan checks
+Base.all(f::Function, x::Operator; kwargs...) = all(f, x.data; kwargs...)
+Base.fill!(x::Operator, a) = typeof(x)(x.basis_l, x.basis_r, fill!(x.data, a))
+Base.ndims(x::Type{Operator{Bl,Br,A}}) where {Bl,Br,N,A<:AbstractMatrix{N}} = ndims(A)
+Base.similar(x::Operator, t) = typeof(x)(x.basis_l, x.basis_r, copy(x.data))
+RecursiveArrayTools.recursivecopy!(dest::Operator{Bl,Br,A},src::Operator{Bl,Br,A}) where {Bl,Br,A} = copyto!(dest,src) # ODE in-place equations
+RecursiveArrayTools.recursivecopy(x::Operator) = copy(x)
+RecursiveArrayTools.recursivecopy(x::AbstractArray{T}) where {T<:Operator} = copy(x)
+RecursiveArrayTools.recursivefill!(x::Operator, a) = fill!(x, a)

src/states.jl

@@ -180,52 +180,51 @@
 Broadcast.BroadcastStyle(::KetStyle{B1}, ::KetStyle{B2}) where {B1,B2} = throw(IncompatibleBases())
 Broadcast.BroadcastStyle(::BraStyle{B1}, ::BraStyle{B2}) where {B1,B2} = throw(IncompatibleBases())
 
+# Broadcast with scalars (of use in ODE solvers checking for tolerances, e.g. `.* reltol .+ abstol`)
+Broadcast.BroadcastStyle(::T, ::Broadcast.DefaultArrayStyle{0}) where {B<:Basis, T<:KetStyle{B}} = T()
+Broadcast.BroadcastStyle(::T, ::Broadcast.DefaultArrayStyle{0}) where {B<:Basis, T<:BraStyle{B}} = T()
+
 # Out-of-place broadcasting
 @inline function Base.copy(bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {B,Style<:KetStyle{B},Axes,F,Args<:Tuple}
     bcf = Broadcast.flatten(bc)
-    bc_ = Broadcasted_restrict_f(bcf.f, bcf.args, axes(bcf))
     b = find_basis(bcf)
-    return Ket{B}(b, copy(bc_))
+    T = find_dType(bcf)
+    data = zeros(T, length(b))
+    @inbounds @simd for I in eachindex(bcf)
+        data[I] = bcf[I]
+    end
+    return Ket{B}(b, data)
 end
 @inline function Base.copy(bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {B,Style<:BraStyle{B},Axes,F,Args<:Tuple}
     bcf = Broadcast.flatten(bc)
-    bc_ = Broadcasted_restrict_f(bcf.f, bcf.args, axes(bcf))
     b = find_basis(bcf)
-    return Bra{B}(b, copy(bc_))
-end
-find_basis(bc::Broadcast.Broadcasted) = find_basis(bc.args)
-find_basis(args::Tuple) = find_basis(find_basis(args[1]), Base.tail(args))
-find_basis(x) = x
-find_basis(a::StateVector, rest) = a.basis
-find_basis(::Any, rest) = find_basis(rest)
-
-const BasicMathFunc = Union{typeof(+),typeof(-),typeof(*)}
-function Broadcasted_restrict_f(f::BasicMathFunc, args::NTuple{N,<:T}, axes) where {T<:StateVector,N}
-    args_ = Tuple(a.data for a=args)
-    return Broadcast.Broadcasted(f, args_, axes)
-end
-function Broadcasted_restrict_f(f, args::Tuple, axes)
-    error("Cannot broadcast function `$f` on $(typeof(args))")
+    T = find_dType(bcf)
+    data = zeros(T, length(b))
+    @inbounds @simd for I in eachindex(bcf)
+        data[I] = bcf[I]
+    end
+    return Bra{B}(b, data)
 end
-function Broadcasted_restrict_f(f::BasicMathFunc, args::Tuple{}, axes) # Defined to avoid method ambiguities
-    error("Cannot broadcast function `$f` on an empty set of arguments")
+for f ∈ [:find_basis,:find_dType]
+    @eval ($f)(bc::Broadcast.Broadcasted) = ($f)(bc.args)
+    @eval ($f)(args::Tuple) = ($f)(($f)(args[1]), Base.tail(args))
+    @eval ($f)(x) = x
+    @eval ($f)(::Any, rest) = ($f)(rest)
 end
 
+find_basis(x::T, rest) where {T<:Union{Ket, Bra}} = x.basis
+find_dType(x::T, rest) where {T<:Union{Ket, Bra}} = eltype(x)
+@inline Base.getindex(x::T, idx) where {T<:Union{Ket, Bra}} = getindex(x.data, idx)
+Base.@propagate_inbounds Base.Broadcast._broadcast_getindex(x::T, i) where {T<:Union{Ket, Bra}} = x.data[i]
+
 # In-place broadcasting for Kets
 @inline function Base.copyto!(dest::Ket{B}, bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {B,Style<:KetStyle{B},Axes,F,Args}
     axes(dest) == axes(bc) || Base.Broadcast.throwdm(axes(dest), axes(bc))
-    # Performance optimization: broadcast!(identity, dest, A) is equivalent to copyto!(dest, A) if indices match
-    if bc.f === identity && isa(bc.args, Tuple{<:Ket{B}}) # only a single input argument to broadcast!
-        A = bc.args[1]
-        if axes(dest) == axes(A)
-            return copyto!(dest, A)
-        end
+    bc′ = Base.Broadcast.preprocess(dest, bc)
+    dest′ = dest.data
+    @inbounds @simd for I in eachindex(bc′)
+        dest′[I] = bc′[I]
     end
-    # Get the underlying data fields of kets and broadcast them as arrays
-    bcf = Broadcast.flatten(bc)
-    args_ = Tuple(a.data for a=bcf.args)
-    bc_ = Broadcast.Broadcasted(bcf.f, args_, axes(bcf))
-    copyto!(dest.data, bc_)
     return dest
 end
 @inline Base.copyto!(dest::Ket{B1}, bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {B1,B2,Style<:KetStyle{B2},Axes,F,Args} =
@@ -234,20 +233,27 @@
 # In-place broadcasting for Bras
 @inline function Base.copyto!(dest::Bra{B}, bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {B,Style<:BraStyle{B},Axes,F,Args}
     axes(dest) == axes(bc) || Base.Broadcast.throwdm(axes(dest), axes(bc))
-    # Performance optimization: broadcast!(identity, dest, A) is equivalent to copyto!(dest, A) if indices match
-    if bc.f === identity && isa(bc.args, Tuple{<:Bra{B}}) # only a single input argument to broadcast!
-        A = bc.args[1]
-        if axes(dest) == axes(A)
-            return copyto!(dest, A)
-        end
+    bc′ = Base.Broadcast.preprocess(dest, bc)
+    dest′ = dest.data
+    @inbounds @simd for I in eachindex(bc′)
+        dest′[I] = bc′[I]
     end
-    # Get the underlying data fields of bras and broadcast them as arrays
-    bcf = Broadcast.flatten(bc)
-    bc_ = Broadcasted_restrict_f(bcf.f, bcf.args, axes(bcf))
-    copyto!(dest.data, bc_)
     return dest
 end
 @inline Base.copyto!(dest::Bra{B1}, bc::Broadcast.Broadcasted{Style,Axes,F,Args}) where {B1,B2,Style<:BraStyle{B2},Axes,F,Args} =
     throw(IncompatibleBases())
 
-@inline Base.copyto!(A::T,B::T) where T<:Union{Ket, Bra} = (copyto!(A.data,B.data); A) # Can not use T<:QuantumInterface.StateVector, because StateVector does not imply the existence of a data property
+@inline Base.copyto!(dest::T,src::T) where {T<:Union{Ket, Bra}} = (copyto!(dest.data,src.data); dest) # Can not use T<:QuantumInterface.StateVector, because StateVector does not imply the existence of a data property
+
+# A few more standard interfaces: These do not necessarily make sense for a StateVector, but enable transparent use of DifferentialEquations.jl
+Base.eltype(::Type{Ket{B,A}}) where {B,N,A<:AbstractVector{N}} = N # ODE init
+Base.eltype(::Type{Bra{B,A}}) where {B,N,A<:AbstractVector{N}} = N
+Base.any(f::Function, x::T; kwargs...) where {T<:Union{Ket, Bra}} = any(f, x.data; kwargs...) # ODE nan checks
+Base.all(f::Function, x::T; kwargs...) where {T<:Union{Ket, Bra}} = all(f, x.data; kwargs...)
+Base.fill!(x::T, a) where {T<:Union{Ket, Bra}} = typeof(x)(x.basis, fill!(x.data, a))
+Base.similar(x::T, t) where {T<:Union{Ket, Bra}} = typeof(x)(x.basis, similar(x.data))
+RecursiveArrayTools.recursivecopy!(dest::Ket{B,A},src::Ket{B,A}) where {B,A} = copyto!(dest, src) # ODE in-place equations
+RecursiveArrayTools.recursivecopy!(dest::Bra{B,A},src::Bra{B,A}) where {B,A} = copyto!(dest, src)
+RecursiveArrayTools.recursivecopy(x::T) where {T<:Union{Ket, Bra}} = copy(x)
+RecursiveArrayTools.recursivecopy(x::AbstractArray{T}) where {T<:Union{Ket, Bra}} = copy(x)
+RecursiveArrayTools.recursivefill!(x::T, a) where {T<:Union{Ket, Bra}} = fill!(x, a)

src/superoperators.jl

@@ -287,7 +287,7 @@ end
 # end
 find_basis(a::SuperOperator, rest) = (a.basis_l, a.basis_r)
 
-const BasicMathFunc = Union{typeof(+),typeof(-),typeof(*)}
+const BasicMathFunc = Union{typeof(+),typeof(-),typeof(*),typeof(/)}
 function Broadcasted_restrict_f(f::BasicMathFunc, args::Tuple{Vararg{<:SuperOperator}}, axes)
     args_ = Tuple(a.data for a=args)
     return Broadcast.Broadcasted(f, args_, axes)

test/Project.toml

@@ -7,7 +7,9 @@ FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 LRUCache = "8ac3fa9e-de4c-5943-b1dc-09c6b5f20637"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 QuantumInterface = "5717a53b-5d69-4fa3-b976-0bf2f97ca1e5"
+QuantumOptics = "6e0679c1-51ea-5a7c-ac74-d61b76210b0c"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RandomMatrices = "2576dda1-a324-5b11-aa66-c48ed7e3c618"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"

test/runtests.jl

@@ -22,6 +22,8 @@ names = [
     "test_subspace.jl",
     "test_state_definitions.jl",
 
+    "test_sciml_broadcast_interfaces.jl",
+
     "test_transformations.jl",
 
     "test_metrics.jl",

test/test_abstractdata.jl

@@ -340,7 +340,6 @@ op1 .= op1_ .+ 3 * op1_
 bf = FockBasis(3)
 op3 = randtestoperator(bf)
 @test_throws QuantumOpticsBase.IncompatibleBases op1 .+ op3
-@test_throws ErrorException cos.(op1)
 
 ####################
 # Test lazy tensor #

test/test_jet.jl

@@ -35,7 +35,7 @@ using LinearAlgebra, LRUCache, Strided, StridedViews, Dates, SparseArrays, Rando
                 AnyFrameModule(RandomMatrices))
             )
         @show rep
-        @test length(JET.get_reports(rep)) <= 24
+        @test length(JET.get_reports(rep)) <= 28
         @test_broken length(JET.get_reports(rep)) == 0
     end
 end # testset

test/test_operators_dense.jl

@@ -382,7 +382,6 @@ op1 .= op1_ .+ 3 * op1_
 bf = FockBasis(3)
 op3 = randoperator(bf)
 @test_throws QuantumOpticsBase.IncompatibleBases op1 .+ op3
-@test_throws ErrorException cos.(op1)
 
 # Dimension mismatches
 b1, b2, b3 = NLevelBasis.((2,3,4))  # N is not a type parameter

test/test_operators_sparse.jl

@@ -419,7 +419,6 @@ op3 = sprandop(FockBasis(1),FockBasis(2))
 op_ = copy(op1)
 op_ .+= op1
 @test op_ == 2*op1
-@test_throws ErrorException cos.(op_)
 
 # Dimension mismatches
 b1, b2, b3 = NLevelBasis.((2,3,4))  # N is not a type parameter

test/test_sciml_broadcast_interfaces.jl

@@ -0,0 +1,63 @@
+using Test
+using QuantumOptics
+using OrdinaryDiffEq
+
+@testset "sciml interface" begin
+
+# ket ODE problem
+ℋ = SpinBasis(1//2)
+↓ = spindown(ℋ)
+t₀, t₁ = (0.0, pi)
+σx = sigmax(ℋ)
+iσx = im*σx
+schrod!(dψ, ψ, p, t) = QuantumOptics.mul!(dψ, iσx, ψ)
+
+ix = iσx.data
+schrod_data!(dψ,ψ,p,t) = QuantumOptics.mul!(dψ, ix, ψ)
+u0 = (↓).data
+
+prob! = ODEProblem(schrod!, ↓, (t₀, t₁))
+prob_data! = ODEProblem(schrod_data!, u0, (t₀, t₁))
+sol = solve(prob!, DP5(); reltol = 1.0e-8, abstol = 1.0e-10, save_everystep=false)
+sol_data = solve(prob_data!, DP5(); reltol = 1.0e-8, abstol = 1.0e-10, save_everystep=false)
+
+@test sol[end].data ≈ sol_data[end] 
+
+# dense operator ODE problem
+σ₋ = sigmam(ℋ)
+σ₊ = σ₋'
+mhalfσ₊σ₋ = -σ₊*σ₋/2
+ρ0 = dm(↓)
+tmp = zero(ρ0)
+function lind!(dρ,ρ,p,t)
+	QuantumOptics.mul!(tmp, ρ, σ₊)
+	QuantumOptics.mul!(dρ, σ₋, ρ)
+	QuantumOptics.mul!(dρ,    ρ, mhalfσ₊σ₋, true, true)
+	QuantumOptics.mul!(dρ, mhalfσ₊σ₋,    ρ, true, true)
+	QuantumOptics.mul!(dρ,  iσx,    ρ, -ComplexF64(1),   ComplexF64(1))
+	QuantumOptics.mul!(dρ,    ρ,  iσx,  true,   true)
+	return dρ
+end
+m0 = ρ0.data
+σ₋d = σ₋.data
+σ₊d = σ₊.data
+mhalfσ₊σ₋d = mhalfσ₊σ₋.data
+tmpd = zero(m0)
+function lind_data!(dρ,ρ,p,t)
+    QuantumOptics.mul!(tmpd, ρ, σ₊d)
+    QuantumOptics.mul!(dρ, σ₋d, ρ)
+    QuantumOptics.mul!(dρ,  ρ, mhalfσ₊σ₋d, true, true)
+    QuantumOptics.mul!(dρ, mhalfσ₊σ₋d, ρ, true, true)
+    QuantumOptics.mul!(dρ,  ix,  ρ, -ComplexF64(1),   ComplexF64(1))
+    QuantumOptics.mul!(dρ,  ρ,  ix,  true,   true)
+    return dρ
+end
+
+prob! = ODEProblem(lind!, ρ0, (t₀, t₁))
+prob_data! = ODEProblem(lind_data!, m0, (t₀, t₁))
+sol = solve(prob!, DP5(); reltol = 1.0e-8, abstol = 1.0e-10, save_everystep=false)
+sol_data = solve(prob_data!, DP5(); reltol = 1.0e-8, abstol = 1.0e-10, save_everystep=false)
+
+@test sol[end].data ≈ sol_data[end]
+
+end

test/test_states.jl

@@ -166,8 +166,6 @@ psi_ .+= psi123
 bra_ = copy(bra123)
 bra_ .= 3*bra123
 @test bra_ == 3*dagger(psi123)
-@test_throws ErrorException cos.(psi_)
-@test_throws ErrorException cos.(bra_)
 
 end # testset
 

test/test_superoperators.jl

@@ -215,8 +215,6 @@ Ldense .+= Ldense
 Ldense .+= L
 @test isa(Ldense, DenseSuperOpType)
 @test isapprox(Ldense.data, 5*Ldense_.data)
-@test_throws ErrorException cos.(Ldense)
-@test_throws ErrorException cos.(L)
 
 b = FockBasis(20)
 L = liouvillian(identityoperator(b), [destroy(b)])