Unify execution interface

README.md

@@ -69,7 +69,7 @@ platform.connect()
 
 # Execute a pulse sequence
 options = ExecutionParameters(nshots=1000)
-results = platform.execute_pulse_sequence(sequence, options)
+results = platform.execute([sequence], options)
 
 # Print the acquired shots
 print(results.samples)

doc/source/getting-started/experiment.rst

@@ -208,10 +208,10 @@ We leave to the dedicated tutorial a full explanation of the experiment, but her
         acquisition_type=AcquisitionType.INTEGRATION,
     )
 
-    results = platform.sweep(sequence, options, sweeper)
+    results = platform.execute([sequence], options, sweeper)
 
     # plot the results
-    amplitudes = results[ro_pulse.id].magnitude
+    amplitudes = results[ro_pulse.id][0].magnitude
     frequencies = np.arange(-2e8, +2e8, 1e6) + ro_pulse.frequency
 
     plt.title("Resonator Spectroscopy")

doc/source/main-documentation/qibolab.rst

@@ -15,7 +15,7 @@ In the platform, the main methods can be divided in different sections:
 
 - functions save and change qubit parameters (``dump``, ``update``)
 - functions to coordinate the instruments (``connect``, ``setup``, ``disconnect``)
-- functions to execute experiments (``execute_pulse_sequence``, ``execute_pulse_sequences``, ``sweep``)
+- a unique interface to execute experiments (``execute``)
 - functions to initialize gates (``create_RX90_pulse``, ``create_RX_pulse``, ``create_CZ_pulse``, ``create_MZ_pulse``, ``create_qubit_drive_pulse``, ``create_qubit_readout_pulse``, ``create_RX90_drag_pulse``, ``create_RX_drag_pulse``)
 - setters and getters of channel/qubit parameters (local oscillator parameters, attenuations, gain and biases)
 
@@ -86,7 +86,7 @@ Now we can execute the sequence on hardware:
         acquisition_type=AcquisitionType.INTEGRATION,
         averaging_mode=AveragingMode.CYCLIC,
     )
-    results = platform.execute_pulse_sequence(ps, options=options)
+    results = platform.execute([ps], options=options)
 
 Finally, we can stop instruments and close connections.
 
@@ -390,7 +390,7 @@ When conducting experiments on quantum hardware, pulse sequences are vital. Assu
 
 .. testcode:: python
 
-    result = platform.execute_pulse_sequence(sequence, options=options)
+    result = platform.execute([sequence], options=options)
 
 Lastly, when conducting an experiment, it is not always required to define a pulse from scratch.
 Usual pulses, such as pi-pulses or measurements, are already defined in the platform runcard and can be easily initialized with platform methods.
@@ -415,7 +415,7 @@ Typical experiments may include both pre-defined pulses and new ones:
     )
     sequence.append(platform.create_MZ_pulse(0))
 
-    results = platform.execute_pulse_sequence(sequence, options=options)
+    results = platform.execute([sequence], options=options)
 
 .. note::
 
@@ -496,7 +496,7 @@ A tipical resonator spectroscopy experiment could be defined with:
         type=SweeperType.OFFSET,
     )
 
-    results = platform.sweep(sequence, options, sweeper)
+    results = platform.execute([sequence], options, sweeper)
 
 .. note::
 
@@ -543,7 +543,7 @@ For example:
         type=SweeperType.FACTOR,
     )
 
-    results = platform.sweep(sequence, options, sweeper_freq, sweeper_amp)
+    results = platform.execute([sequence], options, sweeper_freq, sweeper_amp)
 
 Let's say that the RX pulse has, from the runcard, a frequency of 4.5 GHz and an amplitude of 0.3, the parameter space probed will be:
 
@@ -562,8 +562,7 @@ In the course of several examples, you've encountered the ``options`` argument i
 
 .. testcode:: python
 
-   res = platform.execute_pulse_sequence(sequence, options=options)
-   res = platform.sweep(sequence, options=options)
+   res = platform.execute([sequence], options=options)
 
 Let's now delve into the details of the ``options`` parameter and understand its components.
 
@@ -636,7 +635,7 @@ Let's now delve into a typical use case for result objects within the qibolab fr
         averaging_mode=AveragingMode.CYCLIC,
     )
 
-    res = platform.execute_pulse_sequence(sequence, options=options)
+    res = platform.execute([sequence], options=options)
 
 The ``res`` object will manifest as a dictionary, mapping the measurement pulse serial to its corresponding results.
 
@@ -734,10 +733,8 @@ Instruments all implement a set of methods:
 - setup
 - disconnect
 
-While the controllers, the main instruments in a typical setup, add other two methods:
-
-- execute_pulse_sequence
-- sweep
+While the controllers, the main instruments in a typical setup, add another, i.e.
+execute.
 
 Some more detail on the interal functionalities of instruments is given in :doc:`/tutorials/instrument`
 

doc/source/tutorials/calibration.rst

@@ -65,15 +65,15 @@ We then define the execution parameters and launch the experiment.
         acquisition_type=AcquisitionType.INTEGRATION,
     )
 
-    results = platform.sweep(sequence, options, sweeper)
+    results = platform.execute([sequence], options, sweeper)
 
 In few seconds, the experiment will be finished and we can proceed to plot it.
 
 .. testcode:: python
 
     import matplotlib.pyplot as plt
 
-    amplitudes = results[readout_pulse.id].magnitude
+    amplitudes = results[readout_pulse.id][0].magnitude
     frequencies = np.arange(-2e8, +2e8, 1e6) + readout_pulse.frequency
 
     plt.title("Resonator Spectroscopy")
@@ -153,9 +153,9 @@ We can now proceed to launch on hardware:
         acquisition_type=AcquisitionType.INTEGRATION,
     )
 
-    results = platform.sweep(sequence, options, sweeper)
+    results = platform.execute([sequence], options, sweeper)
 
-    amplitudes = results[readout_pulse.id].magnitude
+    amplitudes = results[readout_pulse.id][0].magnitude
     frequencies = np.arange(-2e8, +2e8, 1e6) + drive_pulse.frequency
 
     plt.title("Resonator Spectroscopy")
@@ -239,20 +239,20 @@ and its impact on qubit states in the IQ plane.
         acquisition_type=AcquisitionType.INTEGRATION,
     )
 
-    results_one = platform.execute_pulse_sequence(one_sequence, options)
-    results_zero = platform.execute_pulse_sequence(zero_sequence, options)
+    results_one = platform.execute([one_sequence], options)
+    results_zero = platform.execute([zero_sequence], options)
 
     plt.title("Single shot classification")
     plt.xlabel("I [a.u.]")
     plt.ylabel("Q [a.u.]")
     plt.scatter(
-        results_one[readout_pulse1.id].voltage_i,
-        results_one[readout_pulse1.id].voltage_q,
+        results_one[readout_pulse1.id][0].voltage_i,
+        results_one[readout_pulse1.id][0].voltage_q,
         label="One state",
     )
     plt.scatter(
-        results_zero[readout_pulse2.id].voltage_i,
-        results_zero[readout_pulse2.id].voltage_q,
+        results_zero[readout_pulse2.id][0].voltage_i,
+        results_zero[readout_pulse2.id][0].voltage_q,
         label="Zero state",
     )
     plt.show()

doc/source/tutorials/pulses.rst

@@ -65,7 +65,7 @@ pulse sequence according to the number of shots ``nshots`` specified.
 
     # Executes a pulse sequence.
     options = ExecutionParameters(nshots=1000, relaxation_time=100)
-    results = platform.execute_pulse_sequence(sequence, options=options)
+    results = platform.execute([sequence], options=options)
 
     # Disconnect from the instruments
     platform.disconnect()

examples/minimum_working_example.py

@@ -38,7 +38,7 @@
 # Connects to lab instruments using the details specified in the calibration settings.
 platform.connect()
 # Executes a pulse sequence.
-results = platform.execute_pulse_sequence(sequence, nshots=3000)
+results = platform.execute([sequence], nshots=3000)
 print(f"results (amplitude, phase, i, q): {results}")
 # Disconnect from the instruments
 platform.disconnect()

examples/qibolab_v017_1Q_emulator_test_QuTiP.ipynb

@@ -108,7 +108,7 @@
     "\n",
     "# Execute the pulse sequence and save the output\n",
     "options = ExecutionParameters(nshots=1000)\n",
-    "results = emulator_platform.execute_pulse_sequence(sequence, options=options)"
+    "results = emulator_platform.execute([sequence], options=options)"
    ]
   },
   {
@@ -454,7 +454,7 @@
    "id": "08e1c8ee-8076-47ee-a05a-bcc068d681d0",
    "metadata": {},
    "source": [
-    "The simulation results generated by the simulation engine are returned together with the usual outputs of `execute_pulse_sequence` for device platforms and are grouped under 'simulation'. \n",
+    "The simulation results generated by the simulation engine are returned together with the usual outputs of `execute` for device platforms and are grouped under 'simulation'. \n",
     "\n",
     "Let us retrieve the simulation results obtained previously:"
    ]

src/qibolab/backends.py

@@ -102,10 +102,11 @@ def execute_circuit(self, circuit, initial_state=None, nshots=1000):
         if not self.platform.is_connected:
             self.platform.connect()
 
-        readout = self.platform.execute_pulse_sequence(
-            sequence,
+        readout_ = self.platform.execute(
+            [sequence],
             ExecutionParameters(nshots=nshots),
         )
+        readout = {k: v[0] for k, v in readout_.items()}
 
         self.platform.disconnect()
 
@@ -147,10 +148,7 @@ def execute_circuits(self, circuits, initial_states=None, nshots=1000):
         if not self.platform.is_connected:
             self.platform.connect()
 
-        readout = self.platform.execute_pulse_sequences(
-            sequences,
-            ExecutionParameters(nshots=nshots),
-        )
+        readout = self.platform.execute(sequences, ExecutionParameters(nshots=nshots))
 
         self.platform.disconnect()
 

src/qibolab/instruments/abstract.py

@@ -97,17 +97,11 @@ def ports(self, port_name, *args, **kwargs):
     def play(self, *args, **kwargs):
         """Play a pulse sequence and retrieve feedback.
 
-        Returns:
-            (Dict[ResultType]) mapping the serial of the readout pulses used to
-            the acquired :class:`qibolab.result.ExecutionResults` object.
-        """
-
-    @abstractmethod
-    def sweep(self, *args, **kwargs):
-        """Play a pulse sequence while sweeping one or more parameters.
+        If :cls:`qibolab.sweeper.Sweeper` objects are passed as arguments, they are
+        executed in real-time. If not possible, an error is raised.
 
         Returns:
-            (dict) mapping the serial of the readout pulses used to
+            (Dict[ResultType]) mapping the serial of the readout pulses used to
             the acquired :class:`qibolab.result.ExecutionResults` object.
         """
 

src/qibolab/instruments/dummy.py

@@ -120,27 +120,6 @@ def play(
         couplers: Dict[QubitId, Coupler],
         sequence: PulseSequence,
         options: ExecutionParameters,
-    ):
-        exp_points = (
-            1 if options.averaging_mode is AveragingMode.CYCLIC else options.nshots
-        )
-        shape = (exp_points,)
-        results = {}
-
-        for ro_pulse in sequence.ro_pulses:
-            values = np.squeeze(self.get_values(options, ro_pulse, shape))
-            results[ro_pulse.qubit] = results[ro_pulse.id] = options.results_type(
-                values
-            )
-
-        return results
-
-    def sweep(
-        self,
-        qubits: Dict[QubitId, Qubit],
-        couplers: Dict[QubitId, Coupler],
-        sequence: PulseSequence,
-        options: ExecutionParameters,
         *sweepers: List[Sweeper],
     ):
         results = {}