# Post selection error **URL:** \ **Category:** PennyLane Help\ **Created:** [January 16, 2024, 7:18am UTC](https://discuss.pennylane.ai/t/post-selection-error/3903 "2024-01-16T07:18:07Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![Aaqib\_Ali](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/aaqib_ali/32/1771_2.png) [@Aaqib\_Ali](https://discuss.pennylane.ai/u/Aaqib_Ali)\ **Post date:** [January 16, 2024, 7:18am UTC](https://discuss.pennylane.ai/t/post-selection-error/3903/1 "2024-01-16T07:18:07Z")
I aim to perform post-selection on the first outcome of the third qubit. Subsequently, I wish to execute a partial trace on this third subsystem. However, I am facing a limitation: post-selection is only feasible with default.qubit, which, unfortunately, does not support the use of noisy channels. How can I effectively carry out post-selection with ‘‘default.mixed’’?’ ```auto import pennylane as qml from pennylane import numpy as np dev=qml.device('default.mixed',wires=3) p=0.1 def circuit1(params): qml.Hadamard(wires=0) qml.CNOT(wires=[0,1]) qml.U3(params[0],params[1],params[2],wires=1) qml.U3(params[3],params[4],params[5],wires=2) qml.CNOT(wires=[2,1]) qml.RZ(params[6],wires=1) qml.RY(params[7],wires=2) qml.CNOT(wires=[1,2]) qml.RY(params[8],wires=2) qml.CNOT(wires=[2,1]) qml.U3(params[9],params[10],params[11],wires=1) qml.U3(params[12],params[13],params[14],wires=2) qml.PhaseDamping(p,wires=1) qml.PhaseDamping(p,wires=2) qml.adjoint(qml.U3(params[12],params[13],params[14],wires=2)) qml.adjoint(qml.U3(params[9],params[10],params[11],wires=1)) qml.adjoint(qml.CNOT(wires=[2,1])) qml.adjoint(qml.RY(params[8],wires=2)) qml.adjoint(qml.CNOT(wires=[1,2])) qml.adjoint(qml.RY(params[7],wires=2)) qml.adjoint(qml.RZ(params[6],wires=1)) qml.adjoint(qml.CNOT(wires=[2,1])) qml.adjoint(qml.U3(params[3],params[4],params[5],wires=2)) qml.adjoint(qml.U3(params[0],params[1],params[2],wires=1)) params = np.array(range(0, 15)) circuit_drawer = qml.draw_mpl(circuit1)(params) pr = np.kron(np.eye(4), np.array([[1, 0], [0, 0]])) @qml.qnode(dev) def circuit2(params): np.dot(np.dot(pr.conj().T,circuit1(params)), pr)#Post selection return qml.density_matrix(wires=[0,1]) ``` error message ```auto --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Cell In[13], line 1 ----> 1 print(circuit2(params)) File ~\anaconda3\Lib\site-packages\pennylane\qnode.py:976, in QNode. __call__ (self, *args, **kwargs) 973 kwargs["shots"] = _get_device_shots(self._original_device) 975 # construct the tape --> 976 self.construct(args, kwargs) 978 cache = self.execute_kwargs.get("cache", False) 979 using_custom_cache = ( 980 hasattr(cache, " __getitem__") 981 and hasattr(cache, " __setitem__") 982 and hasattr(cache, " __delitem__") 983 ) File ~\anaconda3\Lib\site-packages\pennylane\qnode.py:862, in QNode.construct(self, args, kwargs) 859 self.interface = qml.math.get_interface(*args, *list(kwargs.values())) 861 with qml.queuing.AnnotatedQueue() as q: --> 862 self._qfunc_output = self.func(*args, **kwargs) 864 self._tape = QuantumScript.from_queue(q, shots) 866 params = self.tape.get_parameters(trainable_only=False) Cell In[12], line 3, in circuit2(params) 1 @qml.qnode(dev) 2 def circuit2(params): ----> 3 np.dot(np.dot(pr.conj().T,circuit1(params)), pr) 4 return qml.density_matrix(wires=[0,1]) File ~\anaconda3\Lib\site-packages\pennylane\numpy\wrapper.py:117, in tensor_wrapper.._wrapped(*args, **kwargs) 114 tensor_kwargs["requires_grad"] = _np.any([i.requires_grad for i in tensor_args]) 116 # evaluate the original object --> 117 res = obj(*args, **kwargs) 119 if isinstance(res, _np.ndarray): 120 # only if the output of the object is a ndarray, 121 # then convert to a PennyLane tensor 122 res = tensor(res, **tensor_kwargs) File ~\anaconda3\Lib\site-packages\autograd\tracer.py:48, in primitive..f_wrapped(*args, **kwargs) 46 return new_box(ans, trace, node) 47 else: ---> 48 return f_raw(*args, **kwargs) File < __array_function__ internals>:180, in dot(*args, **kwargs) File ~\anaconda3\Lib\site-packages\pennylane\numpy\tensor.py:155, in tensor. __array_ufunc__ (self, ufunc, method, *inputs, **kwargs) 151 args = [i.unwrap() if hasattr(i, "unwrap") else i for i in inputs] 153 # call the ndarray. __array_ufunc__ method to compute the result 154 # of the vectorized ufunc --> 155 res = super(). __array_ufunc__ (ufunc, method, *args, **kwargs) 157 if isinstance(res, Operator): 158 return res TypeError: unsupported operand type(s) for *: 'float' and 'DensityMatrixMP' ``` ---
**Author:** ![isaacdevlugt](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/isaacdevlugt/32/1159_2.png) [@isaacdevlugt](https://discuss.pennylane.ai/u/isaacdevlugt)\ **Post date:** [January 18, 2024, 1:25am UTC](https://discuss.pennylane.ai/t/post-selection-error/3903/2 "2024-01-18T01:25:53Z")
Hey @Aaqib_Ali, welcome to the forum! The problem is with this line: > [@Aaqib\_Ali](#): > > `np.dot(np.dot(pr.conj().T,circuit1(params)), pr)` QNodes in PennyLane can’t have mathematical operations like this. Also, calling `circuit1(params)` here returns nothing because it’s just a quantum function with operations in it. Generally, how circuits work in PennyLane is by defining functions that have _quantum_ operations/instructions in them, return a measurement (like any of these: [Measurements — PennyLane 0.34.0 documentation](https://docs.pennylane.ai/en/stable/introduction/measurements.html)), and by decorating the function with `@qml.qnode`. What you want to do is something like this: ```auto @qml.qnode(dev) def circuit2(params): circuit1(params) # makes circuit2 have all of your operations in circuit1 qml.Projector(...) # some instance of a projector operator based on your desired output return qml.density_matrix(wires=[0,1]) ``` Here, you might be able to accomplish what you want to do via `qml.Projector` ([qml.Projector — PennyLane 0.34.0 documentation](https://docs.pennylane.ai/en/stable/code/api/pennylane.Projector.html?highlight=qml%20projector#pennylane.Projector)) or `qml.QubitUnitary` ([qml.QubitUnitary — PennyLane 0.34.0 documentation](https://docs.pennylane.ai/en/stable/code/api/pennylane.QubitUnitary.html?highlight=qml%20qubitunitary#pennylane.QubitUnitary)). You might also be able to accomplish post-selection more elegantly with `qml.measure`: [qml.measure — PennyLane 0.34.0 documentation](https://docs.pennylane.ai/en/stable/code/api/pennylane.measure.html?highlight=qml%20measure#pennylane.measure). Just use the `postselect` keyword argument 🙂. Let me know if this helps!