Fix expect method with LazyTensor and LazyKets

src/states_lazyket.jl

@@ -68,11 +68,16 @@ function expect(op::LazyTensor{B, B}, state::LazyKet{B}) where B <: Basis
 
     T = promote_type(eltype(op), eltype(state))
     exp_val = convert(T, op.factor)
+
+    # loop over all operators and match with corresponding kets
+    for (i, op_) in enumerate(op.operators)
+        exp_val *= expect(op_, kets[inds[i]])
+    end
+
+    # loop over remaining kets and just add the norm (should be one for normalized ones, but hey, who knows..)
     for i in 1:length(kets)
-        if i ∈ inds
-            exp_val *= expect(ops[i], kets[i])
-        else
-            exp_val *= dot(kets[i], kets[i])
+        if i ∉ inds
+            exp_val *= dot(kets[i].data, kets[i].data)
         end
     end
 

test/test_states.jl

@@ -220,4 +220,8 @@ op_prod = rand(ComplexF64) * LazyProduct(op, op)
 op_nested = rand(ComplexF64) * LazySum(op_prod, op)
 @test expect(op_nested, ψ) ≈ expect(dense(op_prod), Ket(ψ)) * op_nested.factors[1] + expect(dense(op), Ket(ψ)) * op_nested.factors[2]
 
+# test lazytensor with missing indices
+op = rand(ComplexF64) * LazyTensor(b, b, (1, 3), (op1, op3))
+@test expect(op, ψ) ≈ expect(sparse(op), Ket(ψ))
+
 end