# Repository: https://gitlab.com/quantify-os/quantify-scheduler
# Licensed according to the LICENCE file on the main branch
"""Standard gateset for use with the quantify_scheduler."""
from __future__ import annotations
from typing import Literal, Optional, Tuple, Hashable
import numpy as np
from .operation import Operation
from ..enums import BinMode
[docs]
class Rxy(Operation):
r"""
A single qubit rotation around an axis in the equator of the Bloch sphere.
This operation can be represented by the following unitary as defined in
https://doi.org/10.1109/TQE.2020.2965810:
.. math::
\mathsf {R}_{xy} \left(\theta, \varphi\right) = \begin{bmatrix}
\textrm {cos}(\theta /2) & -ie^{-i\varphi }\textrm {sin}(\theta /2)
\\ -ie^{i\varphi }\textrm {sin}(\theta /2) & \textrm {cos}(\theta /2)
\end{bmatrix}
Parameters
----------
theta
Rotation angle in degrees, will be casted to the [-180, 180) domain.
phi
Phase of the rotation axis, will be casted to the [0, 360) domain.
qubit
The target qubit.
"""
def __init__(
self,
theta: float,
phi: float,
qubit: str,
):
if not isinstance(theta, float):
theta = float(theta)
if not isinstance(phi, float):
phi = float(phi)
# this solves an issue where different rotations with the same rotation angle
# modulo a full period are treated as distinct operations in the OperationDict
# Here we map [0,360[ onto ]-180,180] so that X180 has positive amplitude
theta = round(_modulo_360_with_mapping(theta), 8)
phi = round(phi % 360, 8)
tex = r"$R_{xy}^{" + f"{theta:.0f}, {phi:.0f}" + r"}$"
plot_func = (
"quantify_scheduler.schedules._visualization.circuit_diagram.gate_box"
)
theta_r = np.deg2rad(theta)
phi_r = np.deg2rad(phi)
# not all operations have a valid unitary description
# (e.g., measure and init)
unitary = np.array(
[
[
np.cos(theta_r / 2),
-1j * np.exp(-1j * phi_r) * np.sin(theta_r / 2),
],
[
-1j * np.exp(1j * phi_r) * np.sin(theta_r / 2),
np.cos(theta_r / 2),
],
]
)
super().__init__(f"Rxy({theta:.8g}, {phi:.8g}, '{qubit}')")
self.data["gate_info"] = {
"unitary": unitary,
"tex": tex,
"plot_func": plot_func,
"qubits": [qubit],
"operation_type": "Rxy",
"theta": theta,
"phi": phi,
}
self._update()
def __str__(self) -> str:
gate_info = self.data["gate_info"]
theta = gate_info["theta"]
phi = gate_info["phi"]
qubit = gate_info["qubits"][0]
return f"{self.__class__.__name__}({theta=:.8g}, {phi=:.8g}, qubit='{qubit}')"
[docs]
class X(Rxy):
r"""
A single qubit rotation of 180 degrees around the X-axis.
This operation can be represented by the following unitary:
.. math::
X180 = R_{X180} = \begin{bmatrix}
0 & -i \\
-i & 0 \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, qubit: str):
super().__init__(theta=180.0, phi=0, qubit=qubit)
self.data["name"] = f"X {qubit}"
self.data["gate_info"]["tex"] = r"$X_{\pi}$"
self._update()
def __str__(self) -> str:
qubit = self.data["gate_info"]["qubits"][0]
return f"{self.__class__.__name__}(qubit='{qubit}')"
[docs]
class X90(Rxy):
r"""
A single qubit rotation of 90 degrees around the X-axis.
It is identical to the Rxy gate with theta=90 and phi=0
Defined by the unitary:
.. math::
X90 = R_{X90} = \frac{1}{\sqrt{2}}\begin{bmatrix}
1 & -i \\
-i & 1 \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, qubit: str):
super().__init__(theta=90.0, phi=0.0, qubit=qubit)
self.qubit = qubit
self.data["name"] = f"X_90 {qubit}"
self.data["gate_info"]["tex"] = r"$X_{\pi/2}$"
self._update()
def __str__(self) -> str:
qubit = self.data["gate_info"]["qubits"][0]
return f"{self.__class__.__name__}(qubit='{qubit}')"
[docs]
class Y(Rxy):
r"""
A single qubit rotation of 180 degrees around the Y-axis.
It is identical to the Rxy gate with theta=180 and phi=90
Defined by the unitary:
.. math::
Y180 = R_{Y180} = \begin{bmatrix}
0 & -1 \\
1 & 0 \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, qubit: str):
super().__init__(theta=180.0, phi=90.0, qubit=qubit)
self.data["name"] = f"Y {qubit}"
self.data["gate_info"]["tex"] = r"$Y_{\pi}$"
self._update()
def __str__(self) -> str:
qubit = self.data["gate_info"]["qubits"][0]
return f"{self.__class__.__name__}(qubit='{qubit}')"
[docs]
class Y90(Rxy):
r"""
A single qubit rotation of 90 degrees around the Y-axis.
It is identical to the Rxy gate with theta=90 and phi=90
Defined by the unitary:
.. math::
Y90 = R_{Y90} = \frac{1}{\sqrt{2}}\begin{bmatrix}
1 & -1 \\
1 & 1 \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, qubit: str):
super().__init__(theta=90.0, phi=90.0, qubit=qubit)
self.data["name"] = f"Y_90 {qubit}"
self.data["gate_info"]["tex"] = r"$Y_{\pi/2}$"
self._update()
def __str__(self) -> str:
"""
Returns a unique, evaluable string for unchanged data.
Returns a concise string representation
which can be evaluated into a new instance
using :code:`eval(str(operation))` only when the
data dictionary has not been modified.
This representation is guaranteed to be
unique.
"""
qubit = self.data["gate_info"]["qubits"][0]
return f"{self.__class__.__name__}(qubit='{qubit}')"
[docs]
class Rz(Operation):
r"""
A single qubit rotation about the Z-axis of the Bloch sphere.
This operation can be represented by the following unitary as defined in
https://www.quantum-inspire.com/kbase/rz-gate/:
.. math::
\mathsf {R}_{z} \left(\theta\right) = \begin{bmatrix}
e^{-i\theta/2} & 0
\\ 0 & e^{i\theta/2} \end{bmatrix}
Parameters
----------
theta
Rotation angle in degrees, will be cast to the [-180, 180) domain.
qubit
The target qubit.
"""
def __init__(self, theta: float, qubit: str):
if not isinstance(theta, float):
theta = float(theta)
# this solves an issue where different rotations with the same rotation angle
# modulo a full period are treated as distinct operations in the OperationDict
# Here we map [0,360[ onto ]-180,180] so that X180 has positive amplitude
theta = _modulo_360_with_mapping(theta)
tex = r"$R_{z}^{" + f"{theta:.0f}" + r"}$"
plot_func = (
"quantify_scheduler.schedules._visualization.circuit_diagram.gate_box"
)
theta_r = np.deg2rad(theta)
# not all operations have a valid unitary description
# (e.g., measure and init)
unitary = np.array(
[
[np.exp(-1j * theta_r / 2), 0],
[0, np.exp(1j * theta_r / 2)],
]
)
super().__init__(f"Rz({theta:.8g}, '{qubit}')")
self.data["gate_info"] = {
"unitary": unitary,
"tex": tex,
"plot_func": plot_func,
"qubits": [qubit],
"operation_type": "Rz",
"theta": theta,
}
self._update()
def __str__(self) -> str:
gate_info = self.data["gate_info"]
theta = gate_info["theta"]
qubit = gate_info["qubits"][0]
return f"{self.__class__.__name__}({theta=:.8g}, qubit='{qubit}')"
[docs]
class Z(Rz):
r"""
A single qubit rotation of 180 degrees around the Z-axis.
Note that the gate implements :math:`R_z(\pi) = -iZ`, adding a global phase of :math:`-\pi/2`.
This operation can be represented by the following unitary:
.. math::
Z180 = R_{Z180} = -iZ = e^{-\frac{\pi}{2}}Z = \begin{bmatrix}
-i & 0 \\
0 & i \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, qubit: str):
super().__init__(theta=180.0, qubit=qubit)
self.data["name"] = f"Z {qubit}"
self.data["gate_info"]["tex"] = r"$Z_{\pi}$"
self._update()
def __str__(self) -> str:
qubit = self.data["gate_info"]["qubits"][0]
return f"{self.__class__.__name__}(qubit='{qubit}')"
[docs]
class Z90(Rz):
r"""
A single qubit rotation of 90 degrees around the Z-axis.
This operation can be represented by the following unitary:
.. math::
Z90 = R_{Z90} = e^{-\frac{\pi/2}{2}}S = e^{-\frac{\pi/2}{2}}\sqrt{Z} = \frac{1}{\sqrt{2}}\begin{bmatrix}
1-i & 0 \\
0 & 1+i \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, qubit: str):
super().__init__(theta=90.0, qubit=qubit)
self.data["name"] = f"Z_90 {qubit}"
self.data["gate_info"]["tex"] = r"$Z_{\pi/2}$"
self._update()
def __str__(self) -> str:
qubit = self.data["gate_info"]["qubits"][0]
return f"{self.__class__.__name__}(qubit='{qubit}')"
[docs]
class H(Operation):
r"""
A single qubit Hadamard gate.
Note that the gate uses :math:`R_z(\pi) = -iZ`, adding a global phase of :math:`-\pi/2`.
This operation can be represented by the following unitary:
.. math::
H = Y90 \cdot Z = \frac{-i}{\sqrt{2}}\begin{bmatrix}
1 & 1 \\
1 & -1 \\ \end{bmatrix}
Parameters
----------
qubit
The target qubit.
"""
def __init__(self, *qubits: str):
tex = r"$H$"
plot_func = (
"quantify_scheduler.schedules._visualization.circuit_diagram.gate_box"
)
unitary = -1j / np.sqrt(2) * np.array([[1, 1], [1, -1]], dtype=complex)
super().__init__(f"H, '{qubits}')")
self.data["gate_info"] = {
"unitary": unitary,
"tex": tex,
"plot_func": plot_func,
"qubits": list(qubits),
"operation_type": "H",
}
self._update()
def __str__(self) -> str:
qubits = map(lambda x: f"'{x}'", self.data["gate_info"]["qubits"])
return f'{self.__class__.__name__}({",".join(qubits)})'
[docs]
class CNOT(Operation):
r"""
Conditional-NOT gate, a common entangling gate.
Performs an X gate on the target qubit qT conditional on the state
of the control qubit qC.
This operation can be represented by the following unitary:
.. math::
\mathrm{CNOT} = \begin{bmatrix}
1 & 0 & 0 & 0 \\
0 & 1 & 0 & 0 \\
0 & 0 & 0 & 1 \\
0 & 0 & 1 & 0 \\ \end{bmatrix}
Parameters
----------
qC
The control qubit.
qT
The target qubit
"""
def __init__(self, qC: str, qT: str):
plot_func = "quantify_scheduler.schedules._visualization.circuit_diagram.cnot"
super().__init__(f"CNOT ({qC}, {qT})")
self.data.update(
{
"name": f"CNOT ({qC}, {qT})",
"gate_info": {
"unitary": np.array(
[[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 0]]
),
"tex": r"CNOT",
"plot_func": plot_func,
"qubits": [qC, qT],
"symmetric": False,
"operation_type": "CNOT",
},
}
)
self._update()
def __str__(self) -> str:
gate_info = self.data["gate_info"]
qC = gate_info["qubits"][0]
qT = gate_info["qubits"][1]
return f"{self.__class__.__name__}(qC='{qC}',qT='{qT}')"
[docs]
class CZ(Operation):
r"""
Conditional-phase gate, a common entangling gate.
Performs a Z gate on the target qubit qT conditional on the state
of the control qubit qC.
This operation can be represented by the following unitary:
.. math::
\mathrm{CZ} = \begin{bmatrix}
1 & 0 & 0 & 0 \\
0 & 1 & 0 & 0 \\
0 & 0 & 1 & 0 \\
0 & 0 & 0 & -1 \\ \end{bmatrix}
Parameters
----------
qC
The control qubit.
qT
The target qubit
"""
def __init__(self, qC: str, qT: str):
plot_func = "quantify_scheduler.schedules._visualization.circuit_diagram.cz"
super().__init__(f"CZ ({qC}, {qT})")
self.data.update(
{
"name": f"CZ ({qC}, {qT})",
"gate_info": {
"unitary": np.array(
[[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, -1]]
),
"tex": r"CZ",
"plot_func": plot_func,
"qubits": [qC, qT],
"symmetric": True,
"operation_type": "CZ",
},
}
)
self._update()
def __str__(self) -> str:
gate_info = self.data["gate_info"]
qC = gate_info["qubits"][0]
qT = gate_info["qubits"][1]
return f"{self.__class__.__name__}(qC='{qC}',qT='{qT}')"
[docs]
class Reset(Operation):
r"""
Reset a qubit to the :math:`|0\rangle` state.
The Reset gate is an idle operation that is used to initialize one or more qubits.
.. note::
Strictly speaking this is not a gate as it can not
be described by a unitary.
.. admonition:: Examples
:class: tip
The operation can be used in several ways:
.. jupyter-execute::
from quantify_scheduler.operations.gate_library import Reset
reset_1 = Reset("q0")
reset_2 = Reset("q1", "q2")
reset_3 = Reset(*[f"q{i}" for i in range(3, 6)])
Parameters
----------
qubits
The qubit(s) to reset. NB one or more qubits can be specified, e.g.,
:code:`Reset("q0")`, :code:`Reset("q0", "q1", "q2")`, etc..
"""
def __init__(self, *qubits: str):
super().__init__(f"Reset {', '.join(qubits)}")
plot_func = "quantify_scheduler.schedules._visualization.circuit_diagram.reset"
self.data.update(
{
"name": f"Reset {', '.join(qubits)}",
"gate_info": {
"unitary": None,
"tex": r"$|0\rangle$",
"plot_func": plot_func,
"qubits": list(qubits),
"operation_type": "reset",
},
}
)
self._update()
def __str__(self) -> str:
qubits = map(lambda x: f"'{x}'", self.data["gate_info"]["qubits"])
return f'{self.__class__.__name__}({",".join(qubits)})'
[docs]
class Measure(Operation):
"""
A projective measurement in the Z-basis.
The measurement is compiled according to the type of acquisition specified
in the device configuration.
.. note::
Strictly speaking this is not a gate as it can not
be described by a unitary.
Parameters
----------
qubits
The qubits you want to measure.
acq_channel
Only for special use cases.
By default (if None): the acquisition channel specified in the device element is used.
If set, this acquisition channel is used for this measurement.
acq_index
Index of the register where the measurement is stored. If None specified,
this defaults to writing the result of all qubits to acq_index 0. By default
None.
acq_protocol : "SSBIntegrationComplex" | "Trace" | "TriggerCount" | \
"NumericalSeparatedWeightedIntegration" | \
"NumericalWeightedIntegration" | None, optional
Acquisition protocols that are supported. If ``None`` is specified, the
default protocol is chosen based on the device and backend configuration. By
default None.
bin_mode
The binning mode that is to be used. If not None, it will overwrite the
binning mode used for Measurements in the circuit-to-device compilation
step. By default None.
feedback_trigger_label : str
The label corresponding to the feedback trigger, which is mapped by the
compiler to a feedback trigger address on hardware, by default None.
"""
def __init__(
self,
*qubits: str,
acq_channel: Hashable | None = None,
acq_index: Tuple[int, ...] | int | None = None,
# These are the currently supported acquisition protocols.
acq_protocol: Optional[
Literal[
"SSBIntegrationComplex",
"Trace",
"TriggerCount",
"NumericalSeparatedWeightedIntegration",
"NumericalWeightedIntegration",
"ThresholdedAcquisition",
]
] = None,
bin_mode: BinMode | None = None,
feedback_trigger_label: Optional[str] = None,
):
# this if else statement a workaround to support multiplexed measurements (#262)
# this snippet has some automatic behaviour that is error prone.
# see #262
if len(qubits) == 1:
if acq_index is None:
acq_index = 0
else:
if isinstance(acq_index, int):
acq_index = [
acq_index,
] * len(qubits)
elif acq_index is None:
# defaults to writing the result of all qubits to acq_index 0.
# note that this will result in averaging data together if multiple
# measurements are present in the same schedule (#262)
acq_index = list(0 for i in range(len(qubits)))
plot_func = "quantify_scheduler.schedules._visualization.circuit_diagram.meter"
super().__init__(f"Measure {', '.join(qubits)}")
self.data.update(
{
"name": f"Measure {', '.join(qubits)}",
"gate_info": {
"unitary": None,
"plot_func": plot_func,
"tex": r"$\langle0|$",
"qubits": list(qubits),
"acq_channel_override": acq_channel,
"acq_index": acq_index,
"acq_protocol": acq_protocol,
"bin_mode": bin_mode,
"operation_type": "measure",
"feedback_trigger_label": feedback_trigger_label,
},
}
)
self._update()
def __str__(self) -> str:
gate_info = self.data["gate_info"]
qubits = map(lambda x: f"'{x}'", gate_info["qubits"])
acq_channel = gate_info["acq_channel_override"]
acq_index = gate_info["acq_index"]
acq_protocol = gate_info["acq_protocol"]
bin_mode = gate_info["bin_mode"]
feedback_trigger_label = gate_info["feedback_trigger_label"]
return (
f'{self.__class__.__name__}({",".join(qubits)}, '
f"acq_channel={acq_channel}, "
f"acq_index={acq_index}, "
f'acq_protocol="{acq_protocol}", '
f"bin_mode={str(bin_mode)}, "
f"feedback_trigger_label={feedback_trigger_label})"
)
[docs]
def _modulo_360_with_mapping(theta: float) -> float:
"""
Maps an input angle ``theta`` (in degrees) onto the range ``]-180, 180]``.
By mapping the input angle to the range ``]-180, 180]`` (where -180 is
excluded), it ensures that the output amplitude is always minimized on the
hardware. This mapping should not have an effect on the qubit in general.
-180 degrees is excluded to ensure positive amplitudes in the gates like
X180 and Z180.
Note that an input of -180 degrees is remapped to 180 degrees to maintain
the positive amplitude constraint.
Parameters
----------
theta : float
The rotation angle in degrees. This angle will be mapped to the interval
``]-180, 180]``.
Returns
-------
float
The mapped angle in degrees, which will be in the range ``]-180, 180]``.
This mapping ensures the output amplitude is always minimized for
transmon operations.
Example
-------
```
>>> _modulo_360_with_mapping(360)
0.0
>>> _modulo_360_with_mapping(-180)
180.0
>>> _modulo_360_with_mapping(270)
-90.0
```
"""
mapped_theta = -((-theta - 180) % 360) + 180
return mapped_theta
