def estimate_gradient(f_h, precision, n_measurements=50, cxn=False):
""" Estimate the gradient from point of evaluation
to point of perturbation, h
:param float f_h: Oracle output at perturbation h.
:param int precision: Bit precision of gradient.
:param Connection cxn: connection to the QPU or QVM
:param int n_measurements: Number of times to measure system.
"""
# enumerate input and ancilla qubits
input_qubits = list(range(precision))
ancilla_qubit = precision
# generate gradient program
perturbation_sign = np.sign(f_h)
p_gradient = gradient_estimator(abs(f_h), ancilla_qubit)
# run gradient program
if not cxn:
from pyquil.api import SyncConnection
cxn = SyncConnection()
measurements = cxn.run(p_gradient, input_qubits, n_measurements)
# summarize measurements
bf_estimate = perturbation_sign * measurements_to_bf(measurements)
bf_explicit = '{0:.16f}'.format(bf_estimate)
deci_estimate = binary_to_real(bf_explicit)
return deci_estimate
def test_binary_to_real():
precision = 9
decimal_rep = 0.345703125
binary_rep = 0.010110001
decimal_convert = binary_to_real(binary_rep)
assert (np.isclose(decimal_rep, decimal_convert))
def test_binary_to_real():
for sign in [1, -1]:
decimal_rep = sign * 0.345703125
binary_rep = str(sign * 0.010110001)
decimal_convert = binary_to_real(binary_rep)
assert (np.isclose(decimal_rep, decimal_convert))
def estimate_gradient(f_h,
precision,
gradient_max=1,
n_measurements=50,
cxn=None):
"""Estimate the gradient using function evaluation at perturbation, h
:param float f_h: Oracle output at perturbation h.
:param int precision: Bit precision of gradient.
:param int gradient_max: OOM estimate of largest gradient value
:param int n_measurements: Number of times to measure system.
:param Connection cxn: Connection to the QPU or QVM.
:return: Decimal estimate of gradient.
:rtype: float
"""
# scale f_h by range of values gradient can take on
f_h *= 1. / gradient_max
# generate gradient program
perturbation_sign = np.sign(f_h)
p_gradient = gradient_program(f_h, precision)
# run gradient program
if cxn is None:
from pyquil.api import QVMConnection
cxn = QVMConnection()
measured_qubits = list(range(precision + 1))
measurements = cxn.run(p_gradient, measured_qubits, n_measurements)
# summarize measurements
bf_estimate = perturbation_sign * measurements_to_bf(measurements)
bf_explicit = '{0:.16f}'.format(bf_estimate)
deci_estimate = binary_to_real(bf_explicit)
# rescale gradient
deci_estimate *= gradient_max
return deci_estimate