def test_estimates() -> None:
"""
Check that the resource estimator gives reasonable results.
"""
b = QsharpEstimatorBackend()
c = Circuit(3)
c.H(0)
c.CX(0, 1)
c.CCX(0, 1, 2)
c.Rx(0.3, 1)
c.Ry(0.4, 2)
c.Rz(1.1, 0)
c.S(1)
c.SWAP(0, 2)
c.T(1)
c.X(0)
c.Y(1)
c.Z(2)
pbox = PauliExpBox([Pauli.X, Pauli.I, Pauli.Z], 0.25)
c.add_pauliexpbox(pbox, [2, 0, 1])
b.compile_circuit(c, 0)
resources = b.get_resources(c)
assert resources["CNOT"] >= 1
assert resources["QubitClifford"] >= 1
assert resources["R"] >= 1
assert resources["T"] >= 1
assert resources["Depth"] >= 1
assert resources["Width"] == 3
assert resources["BorrowedWidth"] == 0
def test_convert() -> None:
c = Circuit(3)
c.H(0)
c.H(1)
c.CX(1, 0)
c.X(1)
pbox = PauliExpBox([Pauli.X, Pauli.Z, Pauli.X], 0.25)
c.add_pauliexpbox(pbox, [2, 0, 1])
qs = tk_to_qsharp(c)
assert "H(q[1]);" in qs
def h2_JW_sto3g_ansatz():
symbols = [Symbol("s0"), Symbol("s1"), Symbol("s2")]
ansatz = Circuit(4)
# Initialise in Hartree-Fock state
ansatz.X(0)
ansatz.X(1)
# Single excitations
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.X, Pauli.Z, Pauli.Y, Pauli.I], -symbols[0]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.Y, Pauli.Z, Pauli.X, Pauli.I], symbols[0]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.I, Pauli.X, Pauli.Z, Pauli.Y], -symbols[1]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.I, Pauli.Y, Pauli.Z, Pauli.X], symbols[1]), [0, 1, 2, 3]
)
# Double excitations
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.X, Pauli.X, Pauli.X, Pauli.Y], -symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.X, Pauli.X, Pauli.Y, Pauli.X], -symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.X, Pauli.Y, Pauli.X, Pauli.X], symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.Y, Pauli.X, Pauli.X, Pauli.X], symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.X, Pauli.Y, Pauli.Y, Pauli.Y], -symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.Y, Pauli.X, Pauli.Y, Pauli.Y], -symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.Y, Pauli.Y, Pauli.X, Pauli.Y], symbols[2]), [0, 1, 2, 3]
)
ansatz.add_pauliexpbox(
PauliExpBox([Pauli.Y, Pauli.Y, Pauli.Y, Pauli.X], symbols[2]), [0, 1, 2, 3]
)
# Synthesise structures into primitive gates
DecomposeBoxes().apply(ansatz)
return ansatz, symbols
m2 = np.asarray([[0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0]])
m2box = Unitary2qBox(m2)
boxycirc.add_unitary2qbox(m2box, 1, 2)
# Add an `ExpBox`:
A = np.asarray([[1, 2, 3, 4 + 1j], [2, 0, 1j, -1], [3, -1j, 2, 1j],
[4 - 1j, -1, -1j, 1]])
ebox = ExpBox(A, 0.5)
boxycirc.add_expbox(ebox, 0, 1)
# Add a `PauliExpBox`:
pbox = PauliExpBox([Pauli.X, Pauli.Z, Pauli.X], 0.75)
boxycirc.add_pauliexpbox(pbox, [0, 1, 2])
print(boxycirc.get_commands())
# The `get_circuit()` method is available for all box types, and returns a `Circuit` object. For example:
print(pbox.get_circuit().get_commands())
# ## Circuit composition
# Circuits can be composed either serially, whereby wires are joined together, or in parallel, using the `append()` command.
#
# For a simple illustration of serial composition, let's create two circuits with compatible set of wires, and append the second to the first:
c = Circuit(2)
c.CX(0, 1)
step_size = 0.01
n_qubits = [5, 10, 20, 30, 40, 50]
n_runs = 10
for nb_qubits in n_qubits:
data = []
for run_id in range(n_runs):
# Start timer
start = time.time()
circ = Circuit(nb_qubits)
h = 1.0
Jz = 1.0
for i in range(nb_steps):
# Using Heisenberg Hamiltonian:
for q in range(nb_qubits):
circ.add_pauliexpbox(PauliExpBox([Pauli.X], -h * step_size),
[q])
for q in range(nb_qubits - 1):
circ.add_pauliexpbox(
PauliExpBox([Pauli.Z, Pauli.Z], -Jz * step_size),
[q, q + 1])
# Compile to gates
backend = AerStateBackend()
circ = backend.get_compiled_circuit(circ)
# Apply optimization
FullPeepholeOptimise().apply(circ)
end = time.time()
data.append(end - start)
