rydopt.characterization

analyze_gate(gate, pulse, params, tol=1e-15)[source]

Function that analyzes the performance of a gate pulse using JAX.

It determines the gate infidelity, the gate infidelity in the absence of Rydberg state decay, and the Rydberg time.

Example

>>> import rydopt as ro
>>> import numpy as np
>>> gate = ro.gates.TwoQubitGate(
...     phi=None,
...     theta=np.pi,
...     Vnn=float("inf"),
...     decay=0.0001,
... )
>>> pulse = ro.pulses.SinglePhotonPulseAnsatz(
...     detuning_ansatz=ro.pulses.Const(),
...     phase_ansatz=ro.pulses.SinCrab(2),
... )
>>> params = ro.pulses.PulseParams(7.61140652, [0.07842706], [1.80300902, -0.61792703], [])
>>> infid, infid_no_decay, ryd_time = analyze_gate(gate, pulse, params)
Parameters:

  • gate (GateSystem) – Target gate.

  • pulse (PulseAnsatz) – Ansatz of the gate pulse.

  • params (ParamsFloatLike) – Pulse parameters.

  • tol (float) – Precision of the ODE solver, default is 1e-15.

Returns:

Gate infidelity, Gate infidelity without decay, Rydberg time.

Return type:

tuple[float | None, float | None, float | None]

analyze_gate_qutip(gate, pulse, params)[source]

Function that analyzes the performance of a gate pulse using QuTiP.

It determines the gate infidelity, the gate infidelity in the absence of Rydberg state decay, and the Rydberg time.

Example

>>> import rydopt as ro
>>> import numpy as np
>>> gate = ro.gates.TwoQubitGate(
...     phi=None,
...     theta=np.pi,
...     Vnn=float("inf"),
...     decay=0.0001,
... )
>>> pulse = ro.pulses.SinglePhotonPulseAnsatz(
...     detuning_ansatz=ro.pulses.Const(),
...     phase_ansatz=ro.pulses.SinCrab(2),
... )
>>> params = ro.pulses.PulseParams(7.61140652, [0.07842706], [1.80300902, -0.61792703], [])
>>> infid, infid_no_decay, ryd_time = analyze_gate_qutip(gate, pulse, params)
Parameters:
Returns:

Gate infidelity, Gate infidelity without decay, Rydberg time.

Return type:

tuple[float | None, float | None, float | None]

plot_pulse(pulse, params, *, plot_detuning=True, plot_phase=True, plot_rabi=True, subtract_phase_offset=False, num_points=1024, ax=None)[source]

Function that plots a pulse, given the pulse ansatz and the pulse parameters.

Example

>>> import rydopt as ro
>>> pulse = ro.pulses.SinglePhotonPulseAnsatz(
...     detuning_ansatz=ro.pulses.Const(),
...     phase_ansatz=ro.pulses.SinCrab(2),
... )
>>> params = ro.pulses.PulseParams(7.6, [-0.1], [1.8, -0.6], [])
>>> ro.characterization.plot_pulse(pulse, params)
(<Figure ...
Parameters:

  • pulse (PulseAnsatz) – Ansatz of the gate pulse.

  • params (ParamsFloatLike) – Pulse parameters.

  • plot_detuning (bool) – Whether to plot the detuning pulse, default is True.

  • plot_phase (bool) – Whether to plot the phase pulse, default is True.

  • plot_rabi (bool) – Whether to plot the rabi pulse, default is True.

  • subtract_phase_offset (bool) – Whether the phase pulse begins at 0, default is False.

  • num_points (int) – Number of sampling points in the time interval.

  • ax (Axes | None) – Optional matplotlib.axes.Axes to draw on; if None, a new one is created.

Returns:

A tuple of (fig, ax) where ax is the axes used for the pulse plot.

Return type:

tuple[Figure, Axes]

plot_pulse_family(pulse_family, family_params, gate_family, *, plot_detuning=True, plot_phase=True, plot_rabi=True, subtract_phase_offset=False, num_points=1024, ax=None)[source]

Function that plots a set of pulses, given the pulse family ansatz, the pulse family parameters and the gate family.

Parameters:

  • pulse_family (PulseFamilyAnsatz) – Ansatz of the pulse family

  • family_params (ParamsFloatLike) – Pulse family parameters.

  • gate_family (GateFamily) – an instance of the GateFamily

  • plot_detuning (bool) – Whether to plot the detuning pulse, default is True.

  • plot_phase (bool) – Whether to plot the phase pulse, default is True.

  • plot_rabi (bool) – Whether to plot the rabi pulse, default is True.

  • subtract_phase_offset (bool) – Whether the phase pulse begins at 0, default is False.

  • num_points (int) – Number of sampling points in the time interval.

  • ax (Axes | None) – Optional matplotlib.axes.Axes to draw on; if None, a new one is created.

Returns:

A tuple of (fig, ax, cmap, norm) where ax is the axes used for the pulse plot, cmap is the colormap, and norm is the normalization used for the colormap.

Return type:

tuple[Figure, Axes, Colormap, Normalize]

plot_spectrum(pulse, params, *, plot_detuning=True, plot_phase=True, plot_rabi=True, num_points=256, pad_factor=1024, tapered=True, xlim=None, ylim=None, ax=None)[source]

Function that plots the spectrum of a pulse, given the pulse ansatz and the pulse parameters.

Example

>>> import rydopt as ro
>>> pulse = ro.pulses.SinglePhotonPulseAnsatz(
...     detuning_ansatz=ro.pulses.Const(),
...     phase_ansatz=ro.pulses.SinCrab(2),
... )
>>> params = ro.pulses.PulseParams(7.6, [-0.1], [1.8, -0.6], [])
>>> ro.characterization.plot_spectrum(pulse, params)
(<Figure ...
Parameters:

  • pulse (PulseAnsatz) – Ansatz of the gate pulse.

  • params (ParamsFloatLike) – Pulse parameters.

  • plot_detuning (bool) – Whether to plot the detuning pulse, default is True.

  • plot_phase (bool) – Whether to plot the phase pulse, default is True.

  • plot_rabi (bool) – Whether to plot the rabi pulse, default is True.

  • num_points (int) – Number of sampling points in the time interval.

  • pad_factor (int) – Factor by which the time array is padded.

  • tapered (bool) – If True, applies a Tukey window in the padded region.

  • xlim (tuple[float, float] | None) – Optional x-axis (frequency) limits; if None, chosen automatically.

  • ylim (tuple[float, float] | None) – Optional y-axis (dB) limits; if None, chosen automatically.

  • ax (Axes | None) – Optional matplotlib.axes.Axes to draw on; if None, a new one is created.

Returns:

A tuple of (fig, ax) where ax is the axes used for the spectrum plot.

Return type:

tuple[Figure, Axes]

plot_optimization_history(optimization_result, *, xlim_step=None, xlim_duration=None, ylim=None, ax1=None, ax2=None)[source]

Function that plots the optimization history.

Example

>>> import rydopt as ro
>>> import numpy as np
>>> gate = ro.gates.TwoQubitGate(
...     phi=None,
...     theta=np.pi,
...     Vnn=float("inf"),
...     decay=0,
... )
>>> pulse = ro.pulses.SinglePhotonPulseAnsatz(
...     detuning_ansatz=ro.pulses.Const(),
...     phase_ansatz=ro.pulses.SinCrab(2),
... )
>>> initial_params = ro.pulses.PulseParams(7.6, [-0.1], [1.8, -0.6], [])
>>> result = ro.optimization.optimize(
...     gate,
...     pulse,
...     initial_params,
...     num_steps=200,
...     tol=1e-7,
...     return_history=True,
... )
Started optimization ...
>>> plot_optimization_history(result)
(<Figure ...
Parameters:

  • optimization_result (OptimizationResult) – OptimizationResult object.

  • xlim_step (tuple[float, float] | None) – Optional x-axis (optimization steps) limits; if None, chosen automatically.

  • xlim_duration (tuple[float, float] | None) – Optional x-axis (gate duration) limits; if None, chosen automatically.

  • ylim (tuple[float, float] | None) – Optional y-axis (infidelity) limits; if None, chosen automatically.

  • ax1 (Axes | None) – Optional matplotlib.axes.Axes to draw the infidelity as a function of the optimization step; if None and ax2 is also None, a new one is created.

  • ax2 (Axes | None) – Optional matplotlib.axes.Axes to draw the infidelity as a function of the gate duration; if None and ax1 is also None, a new one is created.

Returns:

A tuple (fig, (ax1, ax2)) where ax1 and ax2 are the axes used for the two plots.

Return type:

tuple[Figure, tuple[Axes | None, Axes | None]]