Averaging and Sweeping
This section introduces the averaging and parameter sweeping capabilities of LabOne Q. Quantum experiments performed using LabOne Q generally rely on nested loops, which control how results are averaged and how parameters are swept over, referred to here as “acquisition loops” and “sweeps”, respectively.
We discuss the implementation of acquisition loops and sweeps below. Then, we present the timing paradigms utilized by LabOne Q (sample-precise real-time execution and near-time execution) and provide timing recommendations for experiments. Finally, we outline how to generalize sweeps to n-dimensions.
The Real-Time Acquisition Loop
The real-time acquisition loop (
acquire_loop_rt) is the fundamental building block of an experiment definition in LabOne Q. Each measurement of a qubit state with a Zurich Instruments Quantum Analyzer must be executed within a real-time acquisition loop. The real-time acquisition loop specifies:
The number of recorded averages
The averaging mode, which defines whether nested sweeps are executed in a cyclic or sequential manner
The acquisition mode of the Quantum Analyzer
The repetition mode, which governs the repetition rate of the acquisition loop
The Number of Averages and the Averaging Mode
The number of averages n specifies how often the acquisition loop is executed.
The averaging mode differentiates between cyclic averaging and sequential averaging and determines in which order the parameter sweeps within a real-time acquisition loop are executed.
Cyclic averaging: A parameter sweep is fully executed and then repeated n times. This is the default mode and is useful for averaging out temporal drifts.
Sequential averaging: The sequence within a parameter sweep step is executed n times before proceeding with the next sweep steep, i.e., n times with the first parameter step, then n times with the second parameter step, and so on.
Single shot: Used when acquiring single shot data. No averaging is applied to the data, and cyclic averaging is assumed if a parameter sweep is contained within the acquisition loop. In this mode it is still possible to specify the number of averages, which will then be reflected in the number of single shot data points per sweep point that are acquired and returned.
The Acquisition Mode
The acquisition mode of the Quantum Analyzer specifies how the qubit state is measured.
Spectroscopy: Used to obtain a frequency spectrum to characterize the response of resonances.
Integration: Measurement results are obtained by integrating over an acquired response, with an integration weight specified in
Raw: The raw, acquired time-domain data is returned.
The Repetition Mode and Execution Timing
By default, LabOne Q attempts to execute the contents of the real-time acquisition loop as fast as possible. However, it may be advantageous to run experiments with a fixed repetition rate, to make timing and subsequent instrument programming less complex. To accommodate these use cases, LabOne Q provides the following options:
Fastest execution: The experiment is executed as fast as possible, and the repetition rate might vary over the experiment’s course:
Fixed repetition rate: The experiment is executed with a fixed time per shot
Repetition rate specified by the user:
Repetition rate calculated by LabOne Q: Guarantees the fastest possible execution of the experiment, while keeping a fixed repetition rate:
At least one section, which can be a parameter sweep, must be placed within
In a parameter sweep, a parameter is successively varied over a range of values. In quantum experiments, such sweeps are used together with the real-time acquisition loops described above.
LabOne Q provides direct access to linear parameter sweeps, and it also allows for arbitrary sweeps.
sweep_parameter_1 = LinearSweepParameter(uid="amplitude", start=start, stop=stop, count=count) sweep_parameter_2 = SweepParameter(uid="arbitrary", values=some_numpy_array)
sweep syntax is used to execute a parameter sweep, as in this simplified example:
with exp.acquire_loop_rt(uid="shots", count=2**8, acquisition_type=AcquisitionType.INTEGRATION): # real time acquisition loop with exp.sweep(uid="sweep", parameter=sweep_parameter_1, execution_type=ExecutionType.REAL_TIME, alignment=SectionAlignment.RIGHT): # real-time parameter sweep exp.play(signal="q0_drive", pulse=x90) exp.delay(signal="q0_drive", time=sweep_parameter_1) exp.acquire(signal="acquire", handle="acq_0", kernel=readout_weighting_function)
Besides the sweep parameters, the
sweep command also accepts arguments regarding the execution type (real time or near time) and the alignment of the sweep’s child sections or pulses (left or right). In case the readout is the last section within a sweep, the right alignment can be used together with the
AUTO repetition mode of an acquisition loop to keep the time between readouts constant and reduce experiment complexity.
A near-time sweep section cannot be defined within a real-time acquisition loop.
Real-Time and Near-Time Sweeps
While some parameter sweeps, such as the delay time sweep in a Ramsey experiment, rely on sample-precise execution in real time, other sweeps can be executed only in near time. This is the case when a swept property cannot be accessed by the sequencer of the involved instruments, for example, when the frequency of a hardware oscillator on the HDAWG is changed, or when a third-party instrument is used in the experiment.
Typical experiments that use real-time parameter sweeps are Amplitude Rabi sweeps, T1 measurements, and Ramsey sweeps.
Experiments that use near-time sweeps are the readout resonator spectroscopy and the pulsed qubit spectroscopy.
When near-time sweeps are used, it is not necessary to set the sweep parameter within the definition of the experimental sequence. Rather, it can be assigned directly to the setup configuration, as shown in this simplified example:
sweep_parameter = LinearSweepParameter(uid="frequency", start=start, stop=stop, count=count) device_setup.logical_signal_groups["q0"].logical_signals["measure_line"].oscillator.frequency = sweep_parameter
With the resulting combination of sweep and real-time acquisition loop:
with exp.sweep(uid="sweep", parameter=sweep_parameter, execution_type=ExecutionType.NEAR_TIME): with exp.acquire_loop_rt(uid="shots", count=2**8, averaging_mode=AveragingMode.SEQUENTIAL): with exp.section(uid="qubit_excitation"): exp.play(signal="drive", pulse=const_iq_100ns)
Note that the averaging mode of the real-time acquisition loop does not play a role in this example, as it would influence only sweeps within the real-time loop, but not those around it.
Simultaneous Parameter Sweeps
It is possible to sweep two parameters with the same number of steps simultaneously, by grouping them in a list. This works both for near-time and for real-time sweeps.
# define two sweep parameters with the same number of steps sweep_parameter_1 = LinearSweepParameter(uid="delay_1", start=0, stop=1e-6, count=11) sweep_parameter_2 = LinearSweepParameter(uid="delay_2", start=0, stop=5e-6, count=11) with exp.sweep(uid="sweep", parameter=[sweep_parameter_1, sweep_parameter_2]): with exp.section(uid="qubit_excitation"): exp.play(signal="q0_drive", pulse=x90) exp.delay(signal="q0_drive", time=sweep_parameter_1) exp.play(signal="q0_drive", pulse=x90) exp.delay(signal="q0_drive", time=sweep_parameter_2) exp.play(signal="q0_drive", pulse=x90)
Parameter sweeps can also be extended to n dimensions, by nesting them:
# define two sweep parameters, they do not need to have the same number of steps sweep_parameter_1 = LinearSweepParameter(uid="delay", start=0, stop=1e-6, count=11) sweep_parameter_2 = LinearSweepParameter(uid="amplitude", start=0.1, stop=1, count=37) with exp.sweep(uid="sweep1", parameter=sweep_parameter_1): with exp.sweep(uid="sweep2", parameter=sweep_parameter_2): with exp.section(uid="qubit_excitation"): exp.play(signal="q0_drive", pulse=x90) exp.delay(signal="q0_drive", time=sweep_parameter_1) exp.play(signal="q0_drive", pulse=x90, amplitude=sweep_parameter_2)
The QCCS session takes care of the correct ordering of the acquired results and returns them via the results object.
Finally, sweeps in n-dimensions can be defined both in near time and in real time, or in a combination of the two. Note that within a real-time sweep or real-time acquisition loop, only real-time sweeps can be nested further.