Merge pull request #832 from qiboteam/average

Add average option to spectroscopy experiments

doc/source/protocols/resonator_spectroscopy.rst

@@ -29,7 +29,7 @@ The bare resonator frequency can be found setting a large value for the amplitud
 
     platform: <platform_name>
 
-    qubits: [0]
+    targets: [0]
 
     actions:
 
@@ -44,6 +44,17 @@ The bare resonator frequency can be found setting a large value for the amplitud
             nshots: 1024
             relaxation_time: 100000
 
+.. note::
+    The resonator spectroscopy experiment will be performed by computing
+    the average on hardware. If the user wants to retrieve all the shots
+    and perform the average afterwards it can be done by specifying the
+    entry `hardware_average: false` in the experiment parameters. In this
+    case the fitting procedure will take into account errors and error bands
+    will be included in the plot.
+
+    .. image:: resonator_spectroscopy_error_bars.png
+
+
 .. image:: resonator_spectroscopy_high.png
 
 Lowering the amplitude we can see a shift in the peak, e.g.:
@@ -52,7 +63,7 @@ Lowering the amplitude we can see a shift in the peak, e.g.:
 
     platform: <platform_name>
 
-    qubits: [0]
+    targets: [0]
 
     actions:
 
@@ -130,8 +141,7 @@ and also here:
         single_qubit:
             0:
                 bare_resonator_frequency: <high_power_resonator_frequency>
-                readout_frequency: 5_227_920_060
-                drive_frequency: <low_power_resonator_frequency>
+                readout_frequency: <low_power_resonator_frequency>
 
 .. rubric:: References
 

pyproject.toml

@@ -18,7 +18,7 @@ classifiers = [
 [tool.poetry.dependencies]
 python = ">=3.9,<3.12"
 qibolab = { git = "https://github.com/qiboteam/qibolab.git"}
-qibo = "^0.2.7"
+qibo ="^0.2.6"
 numpy = "^1.26.4"
 scipy = "^1.10.1"
 pandas = "^1.4.3"
@@ -30,7 +30,7 @@ dash = "^2.6.0"
 skops = "^0.6.0"
 scikit-learn = "^1.2.1"
 # Explicit dependency required to cope for dash: https://github.com/plotly/dash/issues/2557
-setuptools = "^69.0.0"
+setuptools = "^67.8.0"
 matplotlib = { version = "^3.7.0", optional = true }
 seaborn = { version = "^0.12.2", optional = true }
 pydot = { version = "^1.4.2", optional = true }

src/qibocal/auto/operation.py

@@ -9,6 +9,7 @@
 
 import numpy as np
 import numpy.typing as npt
+from qibolab import AcquisitionType, AveragingMode, ExecutionParameters
 from qibolab.platform import Platform
 from qibolab.qubits import Qubit, QubitId, QubitPair, QubitPairId
 
@@ -71,6 +72,10 @@ class Parameters:
     """Number of executions on hardware"""
     relaxation_time: float
     """Wait time for the qubit to decohere back to the `gnd` state"""
+    hardware_average: bool = False
+    """By default hardware average will be performed."""
+    classify: bool = False
+    """By default qubit state classification will not be performed."""
 
     @classmethod
     def load(cls, input_parameters):
@@ -96,6 +101,24 @@ def load(cls, input_parameters):
             setattr(instantiated_class, parameter, value)
         return instantiated_class
 
+    @property
+    def execution_parameters(self):
+        """Default execution parameters."""
+        averaging_mode = (
+            AveragingMode.CYCLIC if self.hardware_average else AveragingMode.SINGLESHOT
+        )
+        acquisition_type = (
+            AcquisitionType.DISCRIMINATION
+            if self.classify
+            else AcquisitionType.INTEGRATION
+        )
+        return ExecutionParameters(
+            nshots=self.nshots,
+            relaxation_time=self.relaxation_time,
+            acquisition_type=acquisition_type,
+            averaging_mode=averaging_mode,
+        )
+
 
 class AbstractData:
     """Abstract data class."""
@@ -197,9 +220,10 @@ def register_qubit(self, dtype, data_keys, data_dict):
             the values are the related arrays.
         """
         # to be able to handle the non-sweeper case
-        ar = np.empty(np.shape(data_dict[list(data_dict.keys())[0]]), dtype=dtype)
+        ar = np.empty(np.shape(data_dict[list(data_dict)[0]]), dtype=dtype)
         for key, value in data_dict.items():
             ar[key] = value
+
         if data_keys in self.data:
             self.data[data_keys] = np.rec.array(
                 np.concatenate((self.data[data_keys], ar))

src/qibocal/protocols/dispersive_shift.py

@@ -138,19 +138,14 @@ def _acquisition(
 
     results_1 = platform.sweep(
         sequence_1,
-        ExecutionParameters(
-            nshots=params.nshots,
-            relaxation_time=params.relaxation_time,
-            acquisition_type=AcquisitionType.INTEGRATION,
-            averaging_mode=AveragingMode.CYCLIC,
-        ),
+        params.execution_parameters,
         sweeper,
     )
 
     # retrieve the results for every qubit
     for qubit in targets:
         for i, results in enumerate([results_0, results_1]):
-            result = results[ro_pulses[qubit].serial]
+            result = results[ro_pulses[qubit].serial].average
             # store the results
             data.register_qubit(
                 DispersiveShiftType,

src/qibocal/protocols/dispersive_shift_qutrit.py

@@ -130,7 +130,7 @@ def _acquisition(
         )
 
         for qubit in targets:
-            result = results[qubit]
+            result = results[qubit].average
             # store the results
             data.register_qubit(
                 ResSpecType,

src/qibocal/protocols/qubit_spectroscopy.py

@@ -2,7 +2,6 @@
 from typing import Optional
 
 import numpy as np
-from qibolab import AcquisitionType, AveragingMode, ExecutionParameters
 from qibolab.platform import Platform
 from qibolab.pulses import PulseSequence
 from qibolab.qubits import QubitId
@@ -27,6 +26,8 @@ class QubitSpectroscopyParameters(Parameters):
     """Drive pulse duration [ns]. Same for all qubits."""
     drive_amplitude: Optional[float] = None
     """Drive pulse amplitude (optional). Same for all qubits."""
+    hardware_average: bool = True
+    """By default hardware average will be performed."""
 
 
 @dataclass
@@ -96,12 +97,7 @@ def _acquisition(
 
     results = platform.sweep(
         sequence,
-        ExecutionParameters(
-            nshots=params.nshots,
-            relaxation_time=params.relaxation_time,
-            acquisition_type=AcquisitionType.INTEGRATION,
-            averaging_mode=AveragingMode.SINGLESHOT,
-        ),
+        params.execution_parameters,
         sweeper,
     )
 
@@ -113,11 +109,11 @@ def _acquisition(
             ResSpecType,
             (qubit),
             dict(
-                signal=np.abs(result.average.voltage),
-                phase=np.mean(result.phase, axis=0),
+                signal=result.average.magnitude,
+                phase=result.average.phase,
                 freq=delta_frequency_range + qd_pulses[qubit].frequency,
                 error_signal=result.average.std,
-                error_phase=np.std(result.phase, axis=0, ddof=1),
+                error_phase=result.phase_std,
             ),
         )
     return data

src/qibocal/protocols/qubit_spectroscopy_ef.py

@@ -1,7 +1,6 @@
 from dataclasses import asdict, dataclass, field
 
 import numpy as np
-from qibolab import AcquisitionType, AveragingMode, ExecutionParameters
 from qibolab.platform import Platform
 from qibolab.pulses import PulseSequence
 from qibolab.qubits import QubitId
@@ -124,12 +123,7 @@ def _acquisition(
 
     results = platform.sweep(
         sequence,
-        ExecutionParameters(
-            nshots=params.nshots,
-            relaxation_time=params.relaxation_time,
-            acquisition_type=AcquisitionType.INTEGRATION,
-            averaging_mode=AveragingMode.SINGLESHOT,
-        ),
+        params.execution_parameters,
         sweeper,
     )
 
@@ -141,11 +135,11 @@ def _acquisition(
             ResSpecType,
             (qubit),
             dict(
-                signal=np.abs(result.average.voltage),
-                phase=np.mean(result.phase, axis=0),
+                signal=result.average.magnitude,
+                phase=result.average.phase,
                 freq=delta_frequency_range + qd_pulses[qubit].frequency,
                 error_signal=result.average.std,
-                error_phase=np.std(result.phase, axis=0, ddof=1),
+                error_phase=result.phase_std,
             ),
         )
     return data
@@ -156,25 +150,44 @@ def _plot(
 ):
     """Plotting function for QubitSpectroscopy."""
     figures, report = spectroscopy_plot(data, target, fit)
+    show_error_bars = not np.isnan(data[target].error_signal).any()
     if fit is not None:
-        report = table_html(
-            table_dict(
-                target,
-                [
-                    "Frequency 1->2 [Hz]",
-                    "Amplitude [a.u.]",
-                    "Anharmonicity [Hz]",
-                    "Chi2",
-                ],
-                [
-                    (fit.frequency[target], fit.error_fit_pars[target][1]),
-                    (fit.amplitude[target], fit.error_fit_pars[target][0]),
-                    (fit.anharmonicity[target], fit.error_fit_pars[target][2]),
-                    fit.chi2_reduced[target],
-                ],
-                display_error=True,
+        if show_error_bars:
+            report = table_html(
+                table_dict(
+                    target,
+                    [
+                        "Frequency 1->2 [Hz]",
+                        "Amplitude [a.u.]",
+                        "Anharmonicity [Hz]",
+                        "Chi2",
+                    ],
+                    [
+                        (fit.frequency[target], fit.error_fit_pars[target][1]),
+                        (fit.amplitude[target], fit.error_fit_pars[target][0]),
+                        (fit.anharmonicity[target], fit.error_fit_pars[target][2]),
+                        fit.chi2_reduced[target],
+                    ],
+                    display_error=True,
+                )
+            )
+        else:
+            report = table_html(
+                table_dict(
+                    target,
+                    [
+                        "Frequency 1->2 [Hz]",
+                        "Amplitude [a.u.]",
+                        "Anharmonicity [Hz]",
+                    ],
+                    [
+                        fit.frequency[target],
+                        fit.amplitude[target],
+                        fit.anharmonicity[target],
+                    ],
+                    display_error=False,
+                )
             )
-        )
 
     return figures, report