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revert changes and add gates properly
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@renatomello
renatomello committed Feb 10, 2024
1 parent 457cb71 commit 15c707d
Showing 1 changed file with 216 additions and 30 deletions.
246 changes: 216 additions & 30 deletions src/qibo/backends/tensorflow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,87 +20,273 @@ def __init__(self, dtype):
self.tf = tf
self.np = tnp

def _get_numpy_gate(self, name, params):
matrix = getattr(NumpyMatrices(self.dtype), name)(*params)
return self.tf.cast(matrix, dtype=self.dtype)

def RX(self, theta):
return self._get_numpy_gate("RX", [theta])
cos = self.np.cos(theta / 2.0) + 0j
isin = -1j * self.np.sin(theta / 2.0)
return self.tf.cast([[cos, isin], [isin, cos]], dtype=self.dtype)

def RY(self, theta):
return self._get_numpy_gate("RY", [theta])
cos = self.np.cos(theta / 2.0) + 0j
sin = self.np.sin(theta / 2.0) + 0j
return self.tf.cast([[cos, -sin], [sin, cos]], dtype=self.dtype)

def RZ(self, theta):
return self._get_numpy_gate("RZ", [theta])
phase = self.np.exp(0.5j * theta)
return self.tf.cast([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype)

def GPI(self, phi):
return self._get_numpy_gate("GPI", [phi])
phase = self.np.exp(1.0j * phi)
return self.tf.cast([[0, self.np.conj(phase)], [phase, 0]], dtype=self.dtype)

def GPI2(self, phi):
return self._get_numpy_gate("GPI2", [phi])
phase = self.np.exp(1.0j * phi)
return self.tf.cast(
[[1, -1.0j * self.np.conj(phase)], [-1.0j * phase, 1]], dtype=self.dtype
) / self.np.sqrt(2)

def U1(self, theta):
return self._get_numpy_gate("U1", [theta])
phase = self.np.exp(1j * theta)
return self.tf.cast([[1, 0], [0, phase]], dtype=self.dtype)

def U2(self, phi, lam):
return self._get_numpy_gate("U2", [phi, lam])
eplus = self.np.exp(1j * (phi + lam) / 2.0)
eminus = self.np.exp(1j * (phi - lam) / 2.0)
return self.tf.cast(
[[self.np.conj(eplus), -self.np.conj(eminus)], [eminus, eplus]],
dtype=self.dtype,
) / self.np.sqrt(2)

def U3(self, theta, phi, lam):
return self._get_numpy_gate("U3", [theta, phi, lam])
cost = self.np.cos(theta / 2)
sint = self.np.sin(theta / 2)
eplus = self.np.exp(1j * (phi + lam) / 2.0)
eminus = self.np.exp(1j * (phi - lam) / 2.0)
return self.tf.cast(
[
[self.np.conj(eplus) * cost, -self.np.conj(eminus) * sint],
[eminus * sint, eplus * cost],
],
dtype=self.dtype,
)

def U1q(self, theta, phi):
return self._get_numpy_gate("U1q", [theta, phi])
return self.U3(theta, phi - self.np.pi / 2, self.np.pi / 2 - phi)

def CRX(self, theta):
return self._get_numpy_gate("CRX", [theta])
r = self.RX(theta)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, r[0, 0], r[0, 1]],
[0, 0, r[1, 0], r[1, 1]],
],
dtype=self.dtype,
)

def CRY(self, theta):
return self._get_numpy_gate("CRY", [theta])
r = self.RY(theta)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, r[0, 0], r[0, 1]],
[0, 0, r[1, 0], r[1, 1]],
],
dtype=self.dtype,
)

def CRZ(self, theta):
return self._get_numpy_gate("CRZ", [theta])
r = self.RZ(theta)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, r[0, 0], r[0, 1]],
[0, 0, r[1, 0], r[1, 1]],
],
dtype=self.dtype,
)

def CU1(self, theta):
return self._get_numpy_gate("CU1", [theta])
r = self.U1(theta)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, r[0, 0], r[0, 1]],
[0, 0, r[1, 0], r[1, 1]],
],
dtype=self.dtype,
)

def CU2(self, phi, lam):
return self._get_numpy_gate("CU2", [phi, lam])
r = self.U2(phi, lam)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, r[0, 0], r[0, 1]],
[0, 0, r[1, 0], r[1, 1]],
],
dtype=self.dtype,
)

def CU3(self, theta, phi, lam):
return self._get_numpy_gate("CU3", [theta, phi, lam])
r = self.U3(theta, phi, lam)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, r[0, 0], r[0, 1]],
[0, 0, r[1, 0], r[1, 1]],
],
dtype=self.dtype,
)

def fSim(self, theta, phi):
return self._get_numpy_gate("fSim", [theta, phi])
cost = self.np.cos(theta) + 0j
isint = -1j * self.np.sin(theta)
phase = self.np.exp(-1j * phi)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, cost, isint, 0],
[0, isint, cost, 0],
[0, 0, 0, phase],
],
dtype=self.dtype,
)

def GeneralizedfSim(self, u, phi):
return self._get_numpy_gate("GeneralizedfSim", [u, phi])
phase = self.np.exp(-1j * phi)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, u[0, 0], u[0, 1], 0],
[0, u[1, 0], u[1, 1], 0],
[0, 0, 0, phase],
],
dtype=self.dtype,
)

def RXX(self, theta):
return self._get_numpy_gate("RXX", [theta])
cos = self.np.cos(theta / 2.0) + 0j
isin = -1j * self.np.sin(theta / 2.0)
return self.tf.cast(
[
[cos, 0, 0, isin],
[0, cos, isin, 0],
[0, isin, cos, 0],
[isin, 0, 0, cos],
],
dtype=self.dtype,
)

def RYY(self, theta):
return self._get_numpy_gate("RYY", [theta])
cos = self.np.cos(theta / 2.0) + 0j
isin = -1j * self.np.sin(theta / 2.0)
return self.tf.cast(
[
[cos, 0, 0, -isin],
[0, cos, isin, 0],
[0, isin, cos, 0],
[-isin, 0, 0, cos],
],
dtype=self.dtype,
)

def RZZ(self, theta):
return self._get_numpy_gate("RZZ", [theta])
phase = self.np.exp(0.5j * theta)
return self.tf.cast(
[
[self.np.conj(phase), 0, 0, 0],
[0, phase, 0, 0],
[0, 0, phase, 0],
[0, 0, 0, self.np.conj(phase)],
],
dtype=self.dtype,
)

def RZX(self, theta):
return self._get_numpy_gate("RZX", [theta])
cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2)
return self.tf.cast(
[
[cos, -1j * sin, 0, 0],
[-1j * sin, cos, 0, 0],
[0, 0, cos, 1j * sin],
[0, 0, 1j * sin, cos],
],
dtype=self.dtype,
)

def RXXYY(self, theta):
return self._get_numpy_gate("RXXYY", [theta])
cos, sin = self.np.cos(theta / 2), self.np.sin(theta / 2)
return self.tf.cast(
[
[1, 0, 0, 0],
[0, cos, -1j * sin, 0],
[0, -1j * sin, cos, 0],
[0, 0, 0, 1],
],
dtype=self.dtype,
)

def MS(self, phi0, phi1, theta):
return self._get_numpy_gate("MS", [phi0, phi1, theta])
plus = self.np.exp(1.0j * (phi0 + phi1))
minus = self.np.exp(1.0j * (phi0 - phi1))

return self.tf.cast(
[
[
self.np.cos(theta / 2),
0,
0,
-1.0j * self.np.conj(plus) * self.np.sin(theta / 2),
],
[
0,
self.np.cos(theta / 2),
-1.0j * self.np.conj(minus) * self.np.sin(theta / 2),
0,
],
[0, -1.0j * minus * self.np.sin(theta / 2), self.np.cos(theta / 2), 0],
[-1.0j * plus * self.np.sin(theta / 2), 0, 0, self.np.cos(theta / 2)],
],
dtype=self.dtype,
)

def GIVENS(self, theta):
return self._get_numpy_gate("GIVENS", [theta])
return self.tf.cast(
[
[1, 0, 0, 0],
[0, self.np.cos(theta), -self.np.sin(theta), 0],
[0, self.np.sin(theta), self.np.cos(theta), 0],
[0, 0, 0, 1],
],
dtype=self.dtype,
)

def RBS(self, theta):
return self._get_numpy_gate("RBS", [theta])
return self.GIVENS(-theta)

def DEUTSCH(self, theta):
return self._get_numpy_gate("DEUTSCH", [theta])
sin = self.np.sin(theta) + 0j # 0j necessary for right tensorflow dtype
cos = self.np.cos(theta)
return self.tf.cast(
[
[1, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 1j * cos, sin],
[0, 0, 0, 0, 0, 0, sin, 1j * cos],
],
dtype=self.dtype,
)


def Unitary(self, u):
return self.tf.cast(u, dtype=self.dtype)
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