qml.resource¶
The resource module provides classes and functionality to estimate the quantum resources
(number of qubits, circuit depth, etc.) required to implement advanced quantum algorithms.
Expectation Value Functions¶
|
Estimate the error in computing an expectation value with a given number of measurements. |
|
Estimate the number of measurements required to compute an expectation value with a target error. |
Quantum Phase Estimation Resources¶
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Estimate the number of non-Clifford gates and logical qubits for a quantum phase estimation algorithm in first quantization using a plane-wave basis. |
|
Estimate the number of non-Clifford gates and logical qubits for a quantum phase estimation algorithm in second quantization with a double-factorized Hamiltonian. |
Resource Classes¶
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Contains attributes which store key resources such as number of gates, number of wires, shots, depth and gate types. |
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Base class that represents quantum gates or channels applied to quantum states and stores the resource requirements of the quantum gate. |
Tracking Resources for Custom Operations¶
We can use the null.qubit device with the qml.Tracker to track the resources
used in a quantum circuit with custom operations without execution.
class MyCustomAlgorithm(ResourcesOperation):
num_wires = 2
def resources(self):
return Resources(
num_wires=self.num_wires,
num_gates=5,
gate_types={"Hadamard": 2, "CNOT": 1, "PauliZ": 2},
gate_sizes={1: 4, 2: 1},
depth=3,
)
dev = qml.device("null.qubit", wires=[0, 1, 2], shots=100)
@qml.qnode(dev)
def circuit(theta):
qml.RZ(theta, wires=0)
qml.CNOT(wires=[0,1])
MyCustomAlgorithm(wires=[1, 2])
return qml.expval(qml.PauliZ(wires=1))
x = np.array(1.23, requires_grad=True)
with qml.Tracker(dev) as tracker:
circuit(x)
We can examine the resources by accessing the resources key:
>>> resources_lst = tracker.history['resources']
>>> print(resources_lst[0])
wires: 3
gates: 7
depth: 5
shots: Shots(None)
gate_types:
{"RZ": 1, "CNOT": 2, "Hadamard": 2, "PauliZ": 2}
gate_sizes:
{1: 5, 2: 2}