def compute_players(self): self.measure_players() simulator = Simulator() for player in self.players: result = '' if player.next_qubit1 != 0 or player.next_qubit2 != 0: result = simulator.run(player.circuit) res = str(result) bits1 = '' bits2 = '' bit = '' for i in range(len(res)): if res[i] == '=': bit = bit + str(res[i + 1]) if player.next_qubit1 > 0: bits1 = bit[:player.next_qubit1] if player.next_qubit2 > 0: bits2 = bit[player.next_qubit1:] if len(player.card1) > 1: player.card1 = [player.card1.pop(int(bits1, 2))] if len(player.card2) > 1: player.card2 = [player.card2.pop(int(bits2, 2))]
def find_y(N,
a,
q,
reps=5
): # Uses the order finding algorithm to give possible values for y
simulator = Simulator() # Sets up simulator
circuit = cirq.Circuit()
number_qubits = q # Sets up all qubits to be used.
m_qubits = [cirq.GridQubit(i, 0) for i in range(2 * number_qubits)]
x_qubits = [
cirq.GridQubit(i, 0)
for i in range(2 * number_qubits, 3 * number_qubits)
]
b_qubits = [
cirq.GridQubit(i, 0)
for i in range(3 * number_qubits, 4 * number_qubits + 1)
]
zero_qubit = cirq.GridQubit(4 * number_qubits + 1, 0)
print('Number of qubits: {}'.format(4 * number_qubits + 5))
circuit.append(order_find(a, N, b_qubits, x_qubits, zero_qubit, m_qubits),
strategy=InsertStrategy.NEW) # Runs the simulation.
return simulator.run(circuit, repetitions=reps).histogram(
key='q') # Returns a dictionary of the measurment results.
sqrt_x = cirq.X**0.5
yield sqrt_x(q0), sqrt_x(q1)
yield cirq.CZ(q0, q1)
yield sqrt_x(q0), sqrt_x(q1)
if meas:
yield cirq.measure(q0, key='q0'), cirq.measure(q1, key='q1')
circuit = cirq.Circuit()
circuit.append(basic_circuit())
print(circuit)
from cirq import Simulator
simq = Simulator()
result = simq.run(circuit)
print(result)
#Ciruit Stepping
circuit = cirq.Circuit()
circuit.append(basic_circuit())
for i, step in enumerate(simq.simulate_moment_steps(circuit)):
print('state at step %d: %s' % (i, np.around(step.state_vector(), 3)))
#monte carlo noise
q = cirq.NamedQubit('a')
circuit = cirq.Circuit.from_ops(cirq.bit_flip(p=0.2)(q),
cirq.measure(q)) #PauliXGate
simq = cirq.Simulator()
q1 = cirq.GridQubit(1, 0)
def basic_circuit(meas=True):
sqrt_x = cirq.X**0.5
yield sqrt_x(q0), sqrt_x(q1)
yield cirq.CZ(q0, q1)
yield sqrt_x(q0), sqrt_x(q1)
if meas:
yield cirq.measure(q0, key='q0'), cirq.measure(q1, key='q1')
circuit = cirq.Circuit()
circuit.append(basic_circuit())
print(circuit)
simulator = Simulator()
result = simulator.run(circuit)
print(result)
# Circuit :
# (0, 0): ───X^0.5───@───X^0.5───M('q0')───
# │
# (1, 0): ───X^0.5───@───X^0.5───M('q1')───
# Result
# q0=0
# q1=1
for _ in range(number_of_iterations):
circuit.append(oracle)
circuit.append(self.diffusion)
return circuit
def make_oracle(qubits):
circuit = cirq.Circuit()
controllee= []
for i in range(length - 1):
controllee.append(qubits[i])
circuit.append(cirq.X(qubits[i]) for i in [1,3,4])
circuit.append(cirq.control(cirq.Z, controllee)(qubits[-1]))
circuit.append(cirq.X(qubits[i]) for i in [1,3,4])
return circuit
grover = Grover(qubits)
oracle = make_oracle(qubits)
circuit = cirq.Circuit()
circuit.append(cirq.H(q) for q in qubits)
grover.run(circuit, oracle, number_of_expected_results)
circuit.append(cirq.measure(*qubits))
print(circuit)
from cirq import Simulator
simulator = Simulator()
result = simulator.run(circuit, repetitions=int(sys.argv[2]))
print(result)
def basic_circuit(m=True):
sqrt_x = cirq.X**0.5
yield sqrt_x(q0), sqrt_x(q1)
yield cirq.CZ(q0, q1)
yield sqrt_x(q0), sqrt_x(q1)
if (m):
yield cirq.measure(q0, key='alpha'), cirq.measure(q1, key='beta')
circuit = cirq.Circuit()
circuit.append(basic_circuit())
print(circuit)
# run the simulator
sim = Simulator()
res = sim.run(circuit)
print(res)
def main():
qft_circuit = generate_2x2_grid()
print("circuit:")
print(qft_circuit)
sim = Simulator()
res = sim.simulate(qft_circuit)
print('\nfinal state:')
print(np.around(res.final_state, 3))
def cz_swap(q0, q1, rot):
yield cirq.CZ(q0, q1)**rot
n = 4
length = n + 1
num_reps = 200
a, subset = choose_subset(n)
circuit = cirq.Circuit()
b = np.random.randint(0, high=2, size=n)
l_z = subset_parity(subset, b, n)
print(a, b)
qubits = [cirq.GridQubit(i, 0) for i in range(length - 1)]
readout = cirq.GridQubit(length - 1, 0)
circuit.append([prepare_initial_state(b, qubits, n)])
circuit.append([cirq.Rx(-np.pi / 2)(readout)])
for i in range(n):
cX = cirq.ControlledGate(cirq.Rx(-np.pi * a[i]))
circuit.append([cX(qubits[i], readout)])
circuit.append([measure_Y(readout), cirq.measure(readout, key='demo')])
print(circuit)
results = simulator.run(circuit, repetitions=num_reps)
estimate = compute_est(results.histogram, num_reps, 'demo')
print("computed Value of function", estimate)