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Merged
goerz merged 1 commit into from
Apr 16, 2026
Merged

Implement flat matrix-vector multiplication #22

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31 changes: 31 additions & 0 deletions src/linalg.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,37 @@ function LinearAlgebra.mul!(Φ::GradVector, G::GradgenOperator, Ψ::GradVector)
end


# Flat-vector dispatch used by ExponentialUtilities' Arnoldi iteration, which
# builds its Krylov matrix via similar(b, T, (n, m+1)) → plain Matrix{T} and
# then calls mul!(view(V,:,j+1), A, view(V,:,j)). The GradVector is treated as
# a packed flat vector: blocks [grad_1 | grad_2 | … | state], each of length N.
function LinearAlgebra.mul!(
Φ::AbstractVector,
G::GradgenOperator{num_controls,GT,CGT},
Ψ::AbstractVector,
α,
β
) where {num_controls,GT,CGT}
N = size(G.G, 1)
L = num_controls
Ψ_state = view(Ψ, (L*N+1):((L+1)*N))
for i = 1:L
Φ_grad_i = view(Φ, ((i-1)*N+1):(i*N))
Ψ_grad_i = view(Ψ, ((i-1)*N+1):(i*N))
LinearAlgebra.mul!(Φ_grad_i, G.G, Ψ_grad_i, α, β)
LinearAlgebra.mul!(Φ_grad_i, G.control_deriv_ops[i], Ψ_state, α, 1)
end
Φ_state = view(Φ, (L*N+1):((L+1)*N))
LinearAlgebra.mul!(Φ_state, G.G, Ψ_state, α, β)
return Φ
end


function LinearAlgebra.mul!(Φ::AbstractVector, G::GradgenOperator, Ψ::AbstractVector)
return LinearAlgebra.mul!(Φ, G, Ψ, true, false)
end


function LinearAlgebra.lmul!(c, Ψ::GradVector)
LinearAlgebra.lmul!(c, Ψ.state)
for i ∈ eachindex(Ψ.grad_states)
Expand Down
88 changes: 69 additions & 19 deletions test/test_interface.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -8,12 +8,14 @@ using QuantumPropagators.Interfaces:
using QuantumGradientGenerators: GradGenerator, GradVector, GradgenOperator
using StaticArrays: SVector, SMatrix, MVector
using LinearAlgebra: norm, dot, mul!, I
using StableRNGs: StableRNG


@testset "GradVector Interface" begin

rng = StableRNG(1179926107)
N = 10
Ψ = random_state_vector(N)
Ψ = random_state_vector(N; rng)
Ψ̃ = GradVector(Ψ, 2)
@test check_state(Ψ̃)

Expand All @@ -24,8 +26,9 @@ end

@testset "GradVector Interface (Static)" begin

rng = StableRNG(2188051723)
N = 10
Ψ = SVector{N,ComplexF64}(random_state_vector(N))
Ψ = SVector{N,ComplexF64}(random_state_vector(N; rng))
Ψ̃ = GradVector(Ψ, 2)
@test check_state(Ψ̃)

Expand All @@ -48,10 +51,11 @@ end

@testset "GradGenerator Interface" begin

rng = StableRNG(3031820470)
N = 10
Ĥ₀ = random_matrix(N, hermitian = true)
Ĥ₁ = random_matrix(N, hermitian = true)
Ĥ₂ = random_matrix(N, hermitian = true)
Ĥ₀ = random_matrix(N; hermitian = true, rng)
Ĥ₁ = random_matrix(N; hermitian = true, rng)
Ĥ₂ = random_matrix(N; hermitian = true, rng)
ϵ₁(t) = 1.0
ϵ₂(t) = 1.0
Ĥ_of_t = hamiltonian(Ĥ₀, (Ĥ₁, ϵ₁), (Ĥ₂, ϵ₂))
Expand All @@ -60,7 +64,7 @@ end

G̃_of_t = GradGenerator(Ĥ_of_t)

Ψ = random_state_vector(N)
Ψ = random_state_vector(N; rng)
Ψ̃ = GradVector(Ψ, length(get_controls(G̃_of_t)))

@test check_generator(G̃_of_t; state = Ψ̃, tlist, for_gradient_optimization = false)
Expand All @@ -70,10 +74,11 @@ end

@testset "GradGenerator Interface (Static)" begin

rng = StableRNG(1911203795)
N = 10
Ĥ₀ = SMatrix{N,N,ComplexF64}(random_matrix(N, hermitian = true))
Ĥ₁ = SMatrix{N,N,ComplexF64}(random_matrix(N, hermitian = true))
Ĥ₂ = SMatrix{N,N,ComplexF64}(random_matrix(N, hermitian = true))
Ĥ₀ = SMatrix{N,N,ComplexF64}(random_matrix(N; hermitian = true, rng))
Ĥ₁ = SMatrix{N,N,ComplexF64}(random_matrix(N; hermitian = true, rng))
Ĥ₂ = SMatrix{N,N,ComplexF64}(random_matrix(N; hermitian = true, rng))
ϵ₁(t) = 1.0
ϵ₂(t) = 1.0
Ĥ_of_t = hamiltonian(Ĥ₀, (Ĥ₁, ϵ₁), (Ĥ₂, ϵ₂))
Expand All @@ -82,7 +87,7 @@ end

G̃_of_t = GradGenerator(Ĥ_of_t)

Ψ = SVector{N,ComplexF64}(random_state_vector(N))
Ψ = SVector{N,ComplexF64}(random_state_vector(N; rng))
Ψ̃ = GradVector(Ψ, length(get_controls(G̃_of_t)))

@test check_generator(G̃_of_t; state = Ψ̃, tlist, for_gradient_optimization = false)
Expand All @@ -92,12 +97,13 @@ end

@testset "GradgenOperator Matrix Interface" begin

rng = StableRNG(3317751223)
N = 5
L = 2
G = Matrix{ComplexF64}(I, N, N)
mu = [rand(ComplexF64, N, N) for _ = 1:L]
mu = [rand(rng, ComplexF64, N, N) for _ = 1:L]
op = GradgenOperator{L,Matrix{ComplexF64},Matrix{ComplexF64}}(G, mu)
state = GradVector(rand(ComplexF64, N), L)
state = GradVector(rand(rng, ComplexF64, N), L)

# supports_matrix_interface reports true for matrix-backed GradgenOperator
@test supports_matrix_interface(typeof(op))
Expand All @@ -116,15 +122,15 @@ end
@test all(collect(op) .≈ vec(dense))

# 3-arg mul! agrees with 5-arg mul!(Phi, G, Psi, true, false)
Psi = GradVector(rand(ComplexF64, N), L)
Psi = GradVector(rand(rng, ComplexF64, N), L)
Phi1 = GradVector(zeros(ComplexF64, N), L)
Phi2 = GradVector(zeros(ComplexF64, N), L)
mul!(Phi1, op, Psi)
mul!(Phi2, op, Psi, true, false)
@test norm(Phi1 - Phi2) < 1e-14

# 3-arg dot(Psi, op, Phi) matches dot(Psi, op * Phi)
Psi2 = GradVector(rand(ComplexF64, N), L)
Psi2 = GradVector(rand(rng, ComplexF64, N), L)
@test dot(state, op, Psi2) ≈ dot(state, op * Psi2)

# similar(op) returns a dense Array of the same eltype and size (matching Operator pattern)
Expand All @@ -147,11 +153,52 @@ end
end


@testset "GradgenOperator flat-vector mul!" begin

rng = StableRNG(1602052280)
N = 5
L = 2
G = rand(rng, ComplexF64, N, N)
mu = [rand(rng, ComplexF64, N, N) for _ = 1:L]
op = GradgenOperator{L,Matrix{ComplexF64},Matrix{ComplexF64}}(G, mu)
dense = Array(op)

# Flat-vector layout: [grad_1 | grad_2 | ... | grad_L | state]
Ψ_flat = rand(rng, ComplexF64, N * (L + 1))
Φ_ref = dense * Ψ_flat

# 3-arg mul! agrees with the dense matrix-vector product
Φ1 = zeros(ComplexF64, N * (L + 1))
mul!(Φ1, op, Ψ_flat)
@test norm(Φ1 - Φ_ref) < 1e-14

# 5-arg mul! with α=true, β=false matches the 3-arg result
Φ2 = zeros(ComplexF64, N * (L + 1))
mul!(Φ2, op, Ψ_flat, true, false)
@test norm(Φ2 - Φ_ref) < 1e-14

# 5-arg mul! with non-trivial α, β: Φ ← α * G * Ψ + β * Φ
α = 2.3 + 0.7im
β = 1.5 - 0.3im
Φ3 = rand(rng, ComplexF64, N * (L + 1))
Φ3_init = copy(Φ3)
mul!(Φ3, op, Ψ_flat, α, β)
@test norm(Φ3 - (α * Φ_ref + β * Φ3_init)) < 1e-14

# works with views (the actual ExponentialUtilities use case)
V = rand(rng, ComplexF64, N * (L + 1), 4)
mul!(view(V, :, 2), op, view(V, :, 1))
@test norm(view(V, :, 2) - dense * view(V, :, 1)) < 1e-14

end


@testset "GradVector Vector Interface" begin

rng = StableRNG(2618946253)
N = 5
L = 2
Psi = rand(ComplexF64, N)
Psi = rand(rng, ComplexF64, N)
gradvec = GradVector(Psi, L)

# supports_vector_interface is true for Vector-backed GradVector
Expand Down Expand Up @@ -192,9 +239,10 @@ end

@testset "GradVector Vector Interface (Static)" begin

rng = StableRNG(167987434)
N = 5
L = 2
Psi = SVector{N,ComplexF64}(rand(ComplexF64, N))
Psi = SVector{N,ComplexF64}(rand(rng, ComplexF64, N))
gradvec = GradVector(Psi, L)

# SVector-backed GradVector: supports_vector_interface follows the component type
Expand All @@ -212,10 +260,11 @@ end

@testset "GradVector without Vector Interface" begin

rng = StableRNG(4252840018)
N = 5
L = 2
# Matrix is not an AbstractVector, so supports_vector_interface returns false
Psi = rand(ComplexF64, N, N)
Psi = rand(rng, ComplexF64, N, N)
gradvec = GradVector(Psi, L)

@test !supports_vector_interface(typeof(gradvec))
Expand All @@ -241,10 +290,11 @@ end

@testset "GradgenOperator without Matrix Interface" begin

rng = StableRNG(1276996367)
N = 5
L = 2
G = NonMatrixOp(rand(ComplexF64, N, N))
mu = [NonMatrixOp(rand(ComplexF64, N, N)) for _ = 1:L]
G = NonMatrixOp(rand(rng, ComplexF64, N, N))
mu = [NonMatrixOp(rand(rng, ComplexF64, N, N)) for _ = 1:L]
op = GradgenOperator{L,NonMatrixOp,NonMatrixOp}(G, mu)

@test !supports_matrix_interface(typeof(op))
Expand Down
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