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Added multiplication of LazyOperators #108

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Added multiplication of LazyOperators #108

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38 changes: 38 additions & 0 deletions src/operators_lazysum.jl
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Expand Up @@ -104,6 +104,44 @@ end
-(a::O1, b::O2) where {O1<:LazyOperator,O2<:LazyOperator} = LazySum(a) - LazySum(b)


#*(a::LazySum{B1,B2}, b::AbstractOperator{B2,B3}) where {B1,B2,B3} = LazySum(a.basis_l, a.basis_r, a.factors, a.operators .* b)
#*(a::AbstractOperator{B1,B2}, b::LazySum{B2,B3}) where {B1,B2,B3} = LazySum(a.basis_l, b.basis_r, b.factors, a.operators .* b)

#*(a::Operator{B1,B2}, b::LazySum{B2,B3}) where {B1,B2,B3} = LazySum(a.basis_l, b.basis_r, b.factors, a.operators .* b)
#*(a::LazySum{B1,B2}, b::Operator{B2,B3}) where {B1,B2,B3} = LazySum(a.basis_l, b.basis_r, a.factors, a.operators .* b)


function Base.:*(a::LazySum{B1,B2}, b::O2) where {B1,B2,O2<:LazyOperator}
c = Array{AbstractOperator}(undef,length(a.operators))
for i in eachindex(a.operators)
c[i] = LazyProduct(a.operators[i]) * b
end
LazySum(a.basis_l, b.basis_r, a.factors, (c...,))
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You have an array typed to AbstractOperator. If your array is already meant to contain abstract types, there is not much reason to do anything more specific than Any, especially given that it would be slightly more readable code.

More importantly though, here you create a temporary array and then you immediately destroy it. It is a bit wasteful (causing unnecessary allocations). It might be a bit simpler to just use a "generator" (a "lazy" object that does not actually compute the content until it is queried):

julia> generator = (i for i in 1:10)
Base.Generator{UnitRange{Int64}, typeof(identity)}(identity, 1:10)

julia> tuple = (generator...,)
(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

So your code can be simplified to something like LazySum(bl, br, a.factors, ((LazyProduct(op)*b for op in a.operators)...,))

end

function Base.:*(a::O1, b::LazySum{B1,B2}) where {B1,B2,O1<:LazyOperator}
c = Array{AbstractOperator}(undef,length(b.operators))
for i in eachindex(b.operators)
c[i] = a * LazyProduct(b.operators[i])
end
LazySum(a.basis_l, b.basis_r, b.factors, (c...,))
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same simplificaiton here

end


function Base.:*(a::O1, b::O2) where {O1<:LazySum,O2<:LazySum}
c = Array{AbstractOperator}(undef,length(a.operators)*length(b.operators))
factors = similar(a.factors,length(a.operators)*length(b.operators))
k = 1
for i in eachindex(a.operators)
for j in eachindex(b.operators)
factors[k] = a.factors[i] * b.factors[j]
c[k] = a.operators[i] * b.operators[j]
k += 1
end
end
LazySum(a.basis_l, b.basis_r, factors, (c...,))
end

function *(a::LazySum, b::Number)
factors = b*a.factors
@samebases LazySum(a.basis_l, a.basis_r, factors, a.operators)
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9 changes: 9 additions & 0 deletions src/operators_lazytensor.jl
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Expand Up @@ -161,6 +161,15 @@ function *(a::DenseOpType{B1,B2}, b::LazyTensor{B2,B3}) where {B1,B2,B3}
result
end

*(a::LazyTensor{B1,B2}, b::LazyProduct{B2,B3}) where {B1,B2,B3} = LazyProduct(a) * b
*(a::LazyProduct{B1,B2}, b::LazyTensor{B2,B3}) where {B1,B2,B3} = a * LazyProduct(b)

#*(a::LazyTensor{B1,B2}, b::AbstractOperator{B2,B3}) where {B1,B2,B3} = LazyProduct((a, b), 1)
#*(a::AbstractOperator{B1,B2}, b::LazyTensor{B2,B3}) where {B1,B2,B3} = LazyProduct((a, b), 1)
#*(a::LazyTensor{B1,B2}, b::Operator{B2,B3}) where {B1,B2,B3} = LazyProduct((a, b), 1)
#*(a::Operator{B1,B2}, b::LazyTensor{B2,B3}) where {B1,B2,B3} = LazyProduct((a, b), 1)


/(a::LazyTensor, b::Number) = LazyTensor(a, a.factor/b)


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12 changes: 11 additions & 1 deletion test/test_operators_lazysum.jl
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Expand Up @@ -68,12 +68,15 @@ op1b = randoperator(b_l, b_r)
op2a = randoperator(b_l, b_r)
op2b = randoperator(b_l, b_r)
op3a = randoperator(b_l, b_r)
op4a = randoperator(b_r, b_l)
op1 = LazySum([0.1, 0.3], (op1a, sparse(op1b)))
op1_ = 0.1*op1a + 0.3*op1b
op2 = LazySum([0.7, 0.9], [sparse(op2a), op2b])
op2_ = 0.7*op2a + 0.9*op2b
op3 = LazySum(op3a)
op3_ = op3a
op4 = LazySum(op4a)
op4_ = op4a

x1 = Ket(b_r, rand(ComplexF64, length(b_r)))
x2 = Ket(b_r, rand(ComplexF64, length(b_r)))
Expand All @@ -94,14 +97,21 @@ xbra1 = Bra(b_l, rand(ComplexF64, length(b_l)))
@test 1e-14 > D(op1 + (-1*op2), op1_ - op2_)

# Test multiplication
@test_throws ArgumentError op1*op2
@test_throws DimensionMismatch op1*op2
@test LazySum([0.1, 0.1], (op1a, op2a)) == LazySum(op1a, op2a)*0.1
@test LazySum([0.1, 0.1], (op1a, op2a)) == 0.1*LazySum(op1a, op2a)
@test 1e-11 > D(op1*(x1 + 0.3*x2), op1_*(x1 + 0.3*x2))
@test 1e-11 > D(op1*x1 + 0.3*op1*x2, op1_*x1 + 0.3*op1_*x2)
@test 1e-11 > D((op1+op2)*(x1+0.3*x2), (op1_+op2_)*(x1+0.3*x2))
@test 1e-12 > D(dagger(x1)*dagger(0.3*op2), dagger(x1)*dagger(0.3*op2_))


@test 1e-12 > D(op1*op4,op1_*op4_)
@test 1e-12 > D(op4*op1,op4_*op1_)

@test 1e-12 > D(LazyProduct(op1_)*op4,op1_*op4_)
@test 1e-12 > D(op4*LazyProduct(op1_),op4_*op1_)

## Test multiplication with LazySum that has no elements
@test iszero( LazySum(b_r, b_l) * op1a )
@test iszero( op1a * LazySum(b_r, b_l) )
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10 changes: 10 additions & 0 deletions test/test_operators_lazytensor.jl
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Expand Up @@ -105,6 +105,11 @@ op3_ = 0.3*I1 ⊗ I2 ⊗ subop3
op4 = 0.4*LazyTensor(b_l, b_r, 2, subop2)
op4_ = 0.4*I1 ⊗ subop2 ⊗ I3

subop4 = randoperator(b2b, b2a)
op5 = 0.3*LazyTensor(b_r, b_l, 2, subop4)
op5_ = 0.3*identityoperator(b1b,b1a) ⊗ subop4 ⊗ identityoperator(b3b,b3a)


x1 = Ket(b_r, rand(ComplexF64, length(b_r)))
x2 = Ket(b_r, rand(ComplexF64, length(b_r)))
xbra1 = Bra(b_l, rand(ComplexF64, length(b_l)))
Expand Down Expand Up @@ -158,6 +163,11 @@ op2_tensor_ = op1_ ⊗ subop1
@test 1e-12 > D(dagger(0.3*op2)*op1_, dagger(0.3*op2_)*op1_)
@test 1e-12 > D(dagger(0.3*op2)*op1, dagger(0.3*op2_)*op1_)

@test 1e-12 > D(op5*LazySum(op1_,op2_), op5_*(op1_+op2_))
@test 1e-12 > D(LazySum(op1_,op2_)*op5, (op1_+op2_)*op5_)
@test 1e-12 > D(op5*LazyProduct(op1_), op5_*op1_)
@test 1e-12 > D(LazyProduct(op1_)*op5, op1_*op5_)


# Test division
@test 1e-14 > D(op1/7, op1_/7)
Expand Down