Implement KrausOperators, conversions, is_trace_preserving, is_valid_…

…channel

src/QuantumOpticsBase.jl

@@ -36,7 +36,7 @@ export Basis, GenericBasis, CompositeBasis, basis,
         #superoperators
                 SuperOperator, DenseSuperOperator, DenseSuperOpType,
                 SparseSuperOperator, SparseSuperOpType,
-                ChoiState,
+                ChoiState, KrausOperators, is_trace_preserving, is_valid_channel,
                 spre, spost, sprepost, liouvillian, identitysuperoperator,
         #fock
                 FockBasis, number, destroy, create,

src/superoperators.jl

@@ -11,8 +11,9 @@ mutable struct SuperOperator{B1,B2,T} <: AbstractSuperOperator{B1,B2}
     basis_r::B2
     data::T
     function SuperOperator{BL,BR,T}(basis_l::BL, basis_r::BR, data::T) where {BL,BR,T}
-        if length(basis_l[1])*length(basis_l[2]) != size(data, 1) ||
-           length(basis_r[1])*length(basis_r[2]) != size(data, 2)
+        if (length(basis_l) != 2 || length(basis_r) != 2 ||
+            length(basis_l[1])*length(basis_l[2]) != size(data, 1) ||
+            length(basis_r[1])*length(basis_r[2]) != size(data, 2))
             throw(DimensionMismatch("Tried to assign data of size $(size(data)) to Hilbert spaces of sizes $(length.(basis_l)), $(length.(basis_r))"))
         end
         new(basis_l, basis_r, data)
@@ -318,26 +319,72 @@ end
 end
 
 # TODO should all of PauliTransferMatrix, ChiMatrix, ChoiState, and KrausOperators subclass AbstractSuperOperator?
+
 """
-    Base class for the Choi representation of superoperators.
+    KrausOperators(B1, B2, data)
+
+Superoperator represented as a list of Kraus operators.
+Note unlike the SuperOperator or ChoiState types where
+its possible to have basis_l[1] != basis_l[2] and basis_r[1] != basis_r[2]
+which allows representations of maps between general linear operators defined on H_A \to H_B,
+a quantum channel can only act on valid density operators which live in H_A \to H_A.
+Thus the Kraus representation is only defined for quantum channels which map
+(H_A \to H_A) \to (H_B \to H_B).
+    """
+mutable struct KrausOperators{B1,B2,T} <: AbstractSuperOperator{B1,B2}
+    basis_l::B1
+    basis_r::B2
+    data::T
+    function KrausOperators{BL,BR,T}(basis_l::BL, basis_r::BR, data::T) where {BL,BR,T}
+        if (any(!samebases(basis_r, M.basis_r) for M in data) ||
+            any(!samebases(basis_l, M.basis_l) for M in data))
+            throw(DimensionMismatch("Tried to assign data with incompatible bases"))
+        end
+
+        new(basis_l, basis_r, data)
+    end
+end
+KrausOperators{BL,BR}(b1::BL,b2::BR,data::T) where {BL,BR,T} = KrausOperators{BL,BR,T}(b1,b2,data)
+KrausOperators(b1::BL,b2::BR,data::T) where {BL,BR,T} = KrausOperators{BL,BR,T}(b1,b2,data)
+KrausOperators(b,data) = KrausOperators(b,b,data)
+
+function is_trace_preserving(kraus::KrausOperators; tol=1e-9)
+    m = I(length(kraus.basis_r)) - sum(dagger(M)*M for M in kraus.data).data
+    m[abs.(m) .< tol] .= 0
+    return iszero(m)
+end
+
+function is_valid_channel(kraus::KrausOperators; tol=1e-9)
+    m = I(length(kraus.basis_r)) - sum(dagger(M)*M for M in kraus.data).data
+    eigs = eigvals(Matrix(m))
+    eigs[@. abs(eigs) < tol || eigs > 0] .= 0
+    return iszero(eigs)
+end
+
 """
+    ChoiState(B1, B2, data)
 
+Superoperator represented as a choi state stored as a sparse or dense matrix.
+"""
 mutable struct ChoiState{B1,B2,T} <: AbstractSuperOperator{B1,B2}
     basis_l::B1
     basis_r::B2
     data::T
-    function ChoiState{BL,BR,T}(basis_l::BL, basis_r::BR, data::T) where {BL,BR,T}
+    function ChoiState{BL,BR,T}(basis_l::BL, basis_r::BR, data::T; tol=1e-9) where {BL,BR,T}
         if (length(basis_l) != 2 || length(basis_r) != 2 ||
             length(basis_l[1])*length(basis_l[2]) != size(data, 1) ||
             length(basis_r[1])*length(basis_r[2]) != size(data, 2))
             throw(DimensionMismatch("Tried to assign data of size $(size(data)) to Hilbert spaces of sizes $(length.(basis_l)), $(length.(basis_r))"))
         end
-        new(basis_l, basis_r, data)
+        if any(abs.(data - data') .> tol)
+            @warn "Trying to construct ChoiState from non-hermitian data"
+        end
+        new(basis_l, basis_r, Hermitian(data))
     end
 end
-ChoiState{BL,BR}(b1::BL,b2::BR,data::T) where {BL,BR,T} = ChoiState{BL,BR,T}(b1,b2,data)
-ChoiState(b1::BL,b2::BR,data::T) where {BL,BR,T} = ChoiState{BL,BR,T}(b1,b2,data)
-ChoiState(b,data) = ChoiState(b,b,data)
+ChoiState{BL,BR}(b1::BL,b2::BR,data::T; tol=1e-9) where {BL,BR,T} = ChoiState{BL,BR,T}(b1,b2,data;tol=tol)
+ChoiState(b1::BL,b2::BR,data::T; tol=1e-9) where {BL,BR,T} = ChoiState{BL,BR,T}(b1,b2,data; tol=tol)
+ChoiState(b,data; tol=tol) = ChoiState(b,b,data; tol=tol)
 
 # TODO: document why we have super_to_choi return non-trace one density matrices.
 # https://forest-benchmarking.readthedocs.io/en/latest/superoperator_representations.html
@@ -367,5 +414,29 @@ function _super_choi((r2, l2), (r1, l1), data::SparseMatrixCSC)
     return (l1, l2), (r1, r2), sparse(data)
 end
 
-ChoiState(op::SuperOperator) = ChoiState(_super_choi(op.basis_l, op.basis_r, op.data)...)
+ChoiState(op::SuperOperator; tol=1e-9) = ChoiState(_super_choi(op.basis_l, op.basis_r, op.data)...; tol=tol)
+SuperOperator(kraus::KrausOperators) =
+    SuperOperator((kraus.basis_l, kraus.basis_l), (kraus.basis_r, kraus.basis_r),
+                  (sum(conj(op)⊗op for op in kraus.data)).data)
+
 SuperOperator(op::ChoiState) = SuperOperator(_super_choi(op.basis_l, op.basis_r, op.data)...)
+ChoiState(kraus::KrausOperators) = ChoiState(SuperOperator(kraus))
+
+function KrausOperators(choi::ChoiState; tol=1e-9)
+    if (!samebases(choi.basis_l[1], choi.basis_l[2]) ||
+        !samebases(choi.basis_r[1], choi.basis_r[2]))
+        throw(DimensionMismatch("Tried to convert choi state of something that isn't a quantum channel mapping density operators to density operators"))
+    end
+    bl, br = choi.basis_l[1], choi.basis_r[1]
+    #ishermitian(choi.data) || @warn "ChoiState is not hermitian"
+    # TODO: figure out how to do this with sparse matrices using e.g. Arpack.jl or ArnoldiMethod.jl
+    vals, vecs = eigen(Hermitian(Matrix(choi.data)))
+    for val in vals
+        (abs(val) > tol && val < 0) && @warn "eigval $(val) < 0 but abs(eigval) > tol=$(tol)"
+    end
+    ops = [Operator(bl, br, sqrt(val)*reshape(vecs[:,i], length(bl), length(br)))
+           for (i, val) in enumerate(vals) if abs(val) > tol && val > 0]
+    return KrausOperators(bl, br, ops)
+end
+
+KrausOperators(op::SuperOperator; tol=1e-9) = KrausOperators(ChoiState(op; tol=tol); tol=tol)