Qililab

Latest version: v0.27.1

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0.27.1

New features since last release

- Introduced the possibility to run multiple shots and averages at the same time for `execute_anneal_program` method.
[797](https://github.com/qilimanjaro-tech/qililab/pull/797)

- Introduced the `Experiment` class, which inherits from `StructuredProgram`. This new class enables the ability to set parameters and execute quantum programs within a structured experiment. Added the `set_parameter` method to allow setting platfform parameters and `execute_qprogram` method to facilitate the execution of quantum programs within the experiment.
[782](https://github.com/qilimanjaro-tech/qililab/pull/782)

- Introduced the `ExperimentExecutor` class to manage and execute quantum experiments within the Qililab framework. This class provides a streamlined way to handle the setup, execution, and results retrieval of experiments.

Temporary Constraints:

- The experiment must contain only one `QProgram`.
- The `QProgram` must contain a single measure operation.
- Parallel loops are not supported.
[790](https://github.com/qilimanjaro-tech/qililab/pull/790)

- Introduced the `platform.execute_experiment()` method for executing experiments. This method simplifies the interaction with the ExperimentExecutor by allowing users to run experiments with a single call.

Example:

Python
Define the QProgram
qp = QProgram()
gain = qp.variable(label='resonator gain', domain=Domain.Voltage)
with qp.for_loop(gain, 0, 10, 1):
qp.set_gain(bus="readout_bus", gain=gain)
qp.measure(bus="readout_bus", waveform=IQPair(I=Square(1.0, 1000), Q=Square(1.0, 1000)), weights=IQPair(I=Square(1.0, 2000), Q=Square(1.0, 2000)))

Define the Experiment
experiment = Experiment()
bias_z = experiment.variable(label='bias_z voltage', domain=Domain.Voltage)
frequency = experiment.variable(label='LO Frequency', domain=Domain.Frequency)
experiment.set_parameter(alias="drive_q0", parameter=Parameter.VOLTAGE, value=0.5)
experiment.set_parameter(alias="drive_q1", parameter=Parameter.VOLTAGE, value=0.5)
experiment.set_parameter(alias="drive_q2", parameter=Parameter.VOLTAGE, value=0.5)
with experiment.for_loop(bias_z, 0.0, 1.0, 0.1):
experiment.set_parameter(alias="readout_bus", parameter=Parameter.VOLTAGE, value=bias_z)
with experiment.for_loop(frequency, 2e9, 8e9, 1e9):
experiment.set_parameter(alias="readout_bus", parameter=Parameter.LO_FREQUENCY, value=frequency)
experiment.execute_qprogram(qp)

Execute the Experiment and display the progress bar.
Results will be streamed to an h5 file. The path of this file is returned from the method.
path = platform.execute_experiment(experiment=experiment, results_path="/tmp/results/")

Load results
results, loops = load_results(path)


[790](https://github.com/qilimanjaro-tech/qililab/pull/790)

- Introduced a robust context manager `platform.session()` for managing platform lifecycle operations. The manager automatically calls `platform.connect()`, `platform.initial_setup()`, and `platform.turn_on_instruments()` to set up the platform environment before experiment execution. It then ensures proper resource cleanup by invoking `platform.turn_off_instruments()` and `platform.disconnect()` after the experiment, even in the event of an error or exception during execution. If multiple exceptions occur during cleanup (e.g., failures in both `turn_off_instruments()` and `disconnect()`), they are aggregated into a single `ExceptionGroup` (Python 3.11+) or a custom exception for earlier Python versions.

Example:

Python
with platform.session():
do stuff...


[792](https://github.com/qilimanjaro-tech/qililab/pull/792)

- Add crosstalk compensation to `AnnealingProgram` workflow. Add methods to `CrosstalkMatrix` to ease crosstalk compensation in the annealing workflow
[775](https://github.com/qilimanjaro-tech/qililab/pull/775)

- Add default measurement to `execute_anneal_program()` method. This method takes now a calibration file and parameters
to add the dispersive measurement at the end of the annealing schedule.
[778](https://github.com/qilimanjaro-tech/qililab/pull/778)

- Added a try/except clause when executing a QProgram on Quantum Machines cluster that controls the execution failing to perform a turning off of the instrument so the \_qm object gets
removed. This, plus setting the close_other_machines=True by default allows to open more than one QuantumMachines VM at the same time to allow more than one experimentalist to work at the same time in the cluster.
[760](https://github.com/qilimanjaro-tech/qililab/pull/760/)

- Added `__str__` method to qprogram. The string is a readable qprogram.
[767](https://github.com/qilimanjaro-tech/qililab/pull/767)

- Added workflow for the execution of annealing programs.

Example:

Python
import qililab as ql

platform = ql.build_platform("examples/runcards/galadriel.yml")
anneal_program_dict = [
{qubit_0": {"sigma_x" : 0, "sigma_y": 0, "sigma_z": 1, "phix":1, "phiz":1},
"qubit_1": {"sigma_x" : 0.1, "sigma_y": 0.1, "sigma_z": 0.1},
"coupler_0_1": {"sigma_x" : 1, "sigma_y": 0.2, "sigma_z": 0.2}
},
{"qubit_0": {"sigma_x" : 0.1, "sigma_y": 0.1, "sigma_z": 1.1},
"qubit_1": {"sigma_x" : 0.2, "sigma_y": 0.2, "sigma_z": 0.2},
"coupler_0_1": {"sigma_x" : 0.9, "sigma_y": 0.1, "sigma_z": 0.1}
},
{"qubit_0": {"sigma_x" : 0.3, "sigma_y": 0.3, "sigma_z": 0.7},
"qubit_1": {"sigma_x" : 0.5, "sigma_y": 0.2, "sigma_z": 0.01},
"coupler_0_1": {"sigma_x" : 0.5, "sigma_y": 0, "sigma_z": -1}
}
]

results = platform.execute_anneal_program(anneal_program_dict=anneal_program_dict, transpiler=lambda delta, epsilon: (delta, epsilon), averages=100_000)


Alternatively, each step of the workflow can be executed separately i.e. the following is equivalent to the above:

python
import qililab as ql

platform = ql.build_platform("examples/runcards/galadriel.yml")
anneal_program_dict = [...] same as in the above example
intialize annealing program class
anneal_program = ql.AnnealingProgram(
platform=platform, anneal_program=anneal_program_dict
)
transpile ising to flux, now flux values can be accessed same as ising coeff values
eg. for phix qubit 0 at t=1ns anneal_program.anneal_program[1]["qubit_0"]["phix"]
anneal_program.transpile(lambda delta, epsilon: (delta, epsilon))
get a dictionary {control_flux: (bus, waveform) from the transpiled fluxes
anneal_waveforms = anneal_program.get_waveforms()
from here on we can create a qprogram to execute the annealing schedule


[767](https://github.com/qilimanjaro-tech/qililab/pull/767)

- Added `CrosstalkMatrix` class to represent and manipulate a crosstalk matrix, where each index corresponds to a bus. The class includes methods for initializing the matrix, getting and setting crosstalk values, and generating string representations of the matrix.

Example:

Python
Create an empty crosstalk matrix
crosstalk_matrix = CrosstalkMatrix()

Add crosstalk values, where the keys are in matrix shape [row][column]
crosstalk_matrix["bus1"]["bus2"] = 0.9
crosstalk_matrix["bus2"]["bus1"] = 0.1

Alternatively, create a matrix from a collection of buses.
All crosstalk values are initialized to 1.0
crosstalk_matrix = CrosstalkMatrix.from_buses({"bus1", "bus2", "bus3"})

Get a formatted string representation of the matrix
bus1 bus2 bus3
bus1 \ 1.0 1.0
bus2 1.0 \ 1.0
bus3 1.0 1.0 \

print(crosstalk_matrix)


- Added the Qblox-specific `set_markers()` method in `QProgram`. This method takes a 4-bit binary mask as input, where `0` means that the associated marker will be open (no signal) and `1` means that the associated marker will be closed (signal). The mapping between bit indexes and markers depends on the Qblox module that the compiled `QProgram` will run on.

Example:

Python
qp = QProgram()
qp.qblox.set_markers(bus='drive_q0', mask='0111')


[747](https://github.com/qilimanjaro-tech/qililab/pull/747)

- Added `set_markers_override_enabled_by_port` and `set_markers_override_value_by_port` methods in `QbloxModule` to set markers through QCoDeS, overriding Q1ASM values.
[747](https://github.com/qilimanjaro-tech/qililab/pull/747)

- Added `from_qprogram` method to the `Counts` class to compute the counts of quantum states obtained from a `QProgram`. The `Counts` object is designed to work for circuits that have only one measurement per bus at the end of the circuit execution. It is the user's responsibility to ensure that this method is used appropriately when it makes sense to compute the state counts for a `QProgram`. Note that probabilities can easily be obtained by calling the `probabilities()` method. See an example below.

Example:

Python
from qililab.result.counts import Counts

qp = QProgram()
Define instructions for QProgram
...
qp_results = platform.execute_qprogram(qp) Platform previously defined
counts_object = Counts.from_qprogram(qp_results)
probs = counts_object.probabilities()


[743](https://github.com/qilimanjaro-tech/qililab/pull/743)

- Added `threshold_rotations` argument to `compile()` method in `QProgram`. This argument allows to use rotation angles on measurement instructions if not specified. Currently used to use the angle rotations specified on the runcard (if any) so the user does not have to explicitly pass it as argument to the measure instruction. Used for classification of results in Quantum Machines's modules. The following example shows how to specify this value on the runcard.

Example:

yaml
buses:
- alias: readout_q0_bus
system_control:
name: readout_system_control
instruments: [QMM]
port: readout_line_q0
distortions: []
instruments:
- name: quantum_machines_cluster
alias: QMM
firmware: ...
elements:
- bus: readout_q0_bus
rf_inputs:
octave: octave1
port: 1
rf_outputs:
octave: octave1
port: 1
time_of_flight: 160
smearing: 0
intermediate_frequency: 10.0e+6
threshold_rotation: 0.5
threshold: 0.03
...


[759](https://github.com/qilimanjaro-tech/qililab/pull/759)

- Added `thresholds` argument to `_execute_qprogram_with_quantum_machines` method in `Platform`. This argument allows to threshold results after the execution of the `QProgram`. It is also a new parameter that can be specified on the runcard for each readout bus. An example of the configuration of this parameter on the runcard can be found above.

[762](https://github.com/qilimanjaro-tech/qililab/pull/762)

- Added `filter` argument inside the qua config file compilation from runcards with qm clusters. This is an optional element for distorsion filters that includes feedforward and feedback, two distorion lists for distorsion compensation and fields in qua config filter. These filters are calibrated and then introduced as compensation for the distorsions of the pulses from external sources such as Bias T. The runcard now might include the new filters (optional):

Example:


instruments:
- name: quantum_machines_cluster
alias: QMM
firmware: 0.7.0
...
controllers:
- name: con1
analog_outputs:
- port: 1
offset: 0.0
filter:
feedforward: [0.1,0.1,0.1]
feedback: [0.1,0.1,0.1]
...


[768](https://github.com/qilimanjaro-tech/qililab/pull/768)

- Added loopbacks in the octave config file for qua following the documentation at https://docs.quantum-machines.co/1.2.0/qm-qua-sdk/docs/Guides/octave/?h=octaves#setting-the-octaves-clock. By default only port 1 of the octave is linked with a local demodulator, to work with the rest of the ports at the back ports must be connected based on the Octave Block Diagram \[https://docs.quantum-machines.co/1.2.0/qm-qua-sdk/docs/Hardware/octave/#octave-block-diagram\]. Where `Synth` is one of the possible 3 synths and `Dmd` is one of the 2 demodulators.

Example:


- name: quantum_machines_cluster
alias: QMM
...
octaves:
- name: octave1
port: 11252
...
loopbacks:
Synth: Synth2 Synth1, Synth2, Synth3
Dmd: Dmd2LO Dmd1LO, Dmd2LO


[770](https://github.com/qilimanjaro-tech/qililab/pull/770)

- Added delay variables to Qblox qprogram implementation. The delays are added in the runcard in nanoseconds and they can be positive or negative scalars (negative delays will make the rest of buses wait). The delay is a wait applied to each iteration of a loop where the bus is present.

Example:


buses:
- alias: readout
...
delay: 100


[793](https://github.com/qilimanjaro-tech/qililab/pull/793)

Improvements

- Improve Crosstalk matrix `from_buses` method so it can be a dictionary of buses and crosstalks coefficients.
\[784\]https://github.com/qilimanjaro-tech/qililab/pull/784

- Now platform.get_parameter works for QM without the need of connecting to the machine.

- Added the option to get the time of flight and smearing information from the QM cluster
[751](https://github.com/qilimanjaro-tech/qililab/pull/751)

- Improved the algorithm determining which markers should be ON during execution of circuits and qprograms. Now, all markers are OFF by default, and only the markers associated with the `outputs` setting of QCM-RF and QRM-RF sequencers are turned on.
[747](https://github.com/qilimanjaro-tech/qililab/pull/747)

- Automatic method to implement the correct `upsampling_mode` when the output mode is selected as `amplified` (fluxes), the `upsampling_mode` is automatically defined as `pulse`. In this mode, the upsampling is optimized to produce cleaner step responses.
[783](https://github.com/qilimanjaro-tech/qililab/pull/783)

- Automatic method for `execute_qprogram` in quantum machines to restart the measurement in case the `StreamProcessingDataLossError` is risen by `qua-qm`, the new feature allows to try again the measurement a number of times equal to the value of `dataloss_tries` (default of three). We can define this value at `execute_qprogram(..., dataloss_tries = N)` and will only do its intended job in case of working with QM.
[788](https://github.com/qilimanjaro-tech/qililab/pull/788)

Breaking changes

- Big code refactor for the `calibration` module/directory, where all `comparisons`, `check_parameters`, `check_data()`,
`check_state()`, `maintain()`, `diagnose()` and other complex unused methods have been deleted, leaving only linear calibration.

Also some other minor improvements like:

- `drift_timeout` is now a single one for the full controller, instead of a different one for each node.
- Notebooks without an export are also accepted now (we will only raise error for multiple exports in a NB).
- Extended/Improved the accepted type for parameters to input/output in notebooks, thorught json serialization.
[746](https://github.com/qilimanjaro-tech/qililab/pull/746)

- Variables in `QProgram` and `Experiment` now require a label.

Python
qp = QProgram()
gain = qp.variable(label="gain", domain=Domain.Voltage)


[790](https://github.com/qilimanjaro-tech/qililab/pull/790)

Deprecations / Removals

- Deleted all the files in `execution` and `experiment` directories (Already obsolete).
[749](https://github.com/qilimanjaro-tech/qililab/pull/749)

Documentation

Bug fixes

- Hotfix to allow to serialise zeros in yaml.
[799](https://github.com/qilimanjaro-tech/qililab/pull/799)

- get_parameter for QM did not work due to the lack of the variable `bus_alias in self.system_control.get_parameter`. The variable has been added to the function and now get parameter does not return a crash.
[751](https://github.com/qilimanjaro-tech/qililab/pull/751)

- set_parameter for intermediate frequency in quantum machines has been adapted for both OPX+ and OPX1000 following the new requirements for OPX1000 with qm-qua job.set_intermediate_frequency.
[764](https://github.com/qilimanjaro-tech/qililab/pull/764)

0.27.0

New features since last release

- Added `Calibration` class to manage calibrated waveforms and weights for QProgram. Included methods to add (`add_waveform`/`add_weights`), check (`has_waveform`/`has_weights`), retrieve (`get_waveform`/`get_weights`), save (`save_to`), and load (`load_from`) calibration data.

Example:

Python
Create a Calibration instance
calibration = Calibration()

Define waveforms and weights
drag_wf = IQPair.DRAG(amplitude=1.0, duration=40, num_sigmas=4.5, drag_coefficient=-2.5)
readout_wf = ql.IQPair(I=ql.Square(amplitude=1.0, duration=200), Q=ql.Square(amplitude=0.0, duration=200))
weights = ql.IQPair(I=ql.Square(amplitude=1.0, duration=200), Q=ql.Square(amplitude=1.0, duration=200))

Add waveforms to the calibration
calibration.add_waveform(bus='drive_q0_bus', name='Xpi', waveform=drag_wf)
calibration.add_waveform(bus='readout_q0_bus', name='Measure', waveform=readout_wf)

Add weights to the calibration
calibration.add_weights(bus='readout_q0_bus', name='optimal_weights', weights=weights)

Save the calibration data to a file
calibration.save_to('calibration_data.yml')

Load the calibration data from a file
loaded_calibration = Calibration.load_from('calibration_data.yml')


The contents of `calibration_data.yml` will be:

YAML
!Calibration
waveforms:
drive_q0_bus:
Xpi: !IQPair
I: &id001 !Gaussian {amplitude: 1.0, duration: 40, num_sigmas: 4.5}
Q: !DragCorrection
drag_coefficient: -2.5
waveform: *id001
readout_q0_bus:
Measure: !IQPair
I: !Square {amplitude: 1.0, duration: 200}
Q: !Square {amplitude: 0.0, duration: 200}
weights:
readout_q0_bus:
optimal_weights: !IQPair
I: !Square {amplitude: 1.0, duration: 200}
Q: !Square {amplitude: 1.0, duration: 200}


Calibrated waveforms and weights can be used in QProgram by providing their name.

Python
qp = QProgram()
qp.play(bus='drive_q0_bus', waveform='Xpi')
qp.measure(bus='readout_q0_bus', waveform='Measure', weights='optimal_weights')


In that case, a `Calibration` instance must be provided when executing the QProgram. (see following changelog entries)

[729](https://github.com/qilimanjaro-tech/qililab/pull/729)
[736](https://github.com/qilimanjaro-tech/qililab/pull/736)

- Introduced `qililab.yaml` namespace that exports a single `YAML` instance for common use throughout qililab. Classes should be registered to this instance with the `yaml.register_class` decorator.

Python
from qililab.yaml import yaml

yaml.register_class
class MyClass:
...


`MyClass` can now be saved to and loaded from a yaml file.

Python
from qililab.yaml import yaml

my_instance = MyClass()

Save to file
with open(file="my_file.yml", mode="w", encoding="utf-8") as stream:
yaml.dump(data=my_instance, stream=stream)

Load from file
with open(file="my_file.yml", mode="r", encoding="utf8") as stream:
loaded_instance = yaml.load(stream)


[729](https://github.com/qilimanjaro-tech/qililab/pull/729)

- Added `serialize()`, `serialize_to()`, `deserialize()`, `deserialize_from()` functions to enable a unified method for serializing and deserializing Qililab classes to and from YAML memory strings and files.

Python
import qililab as ql

qp = QProgram()

Serialize QProgram to a memory string and deserialize from it.
yaml_string = ql.serialize(qp)
deserialized_qprogram = ql.deserialize(yaml_string)

Specify the class for deserialization using the `cls` parameter.
deserialized_qprogram = ql.deserialize(yaml_string, cls=ql.QProgram)

Serialize to and deserialize from a file.
ql.serialize_to(qp, 'qprogram.yml')
deserialized_qprogram = ql.deserialize_from('qprogram.yml', cls=ql.QProgram)


[737](https://github.com/qilimanjaro-tech/qililab/pull/737)

- Added Qblox support for QProgram's `measure` operation. The method can now be used for both Qblox
and Quantum Machines, and the expected behaviour is the same.

Python
readout_pair = IQPair(I=Square(amplitude=1.0, duration=1000), Q=Square(amplitude=0.0, duration=1000))
weights_pair = IQPair(I=Square(amplitude=1.0, duration=2000), Q=Square(amplitude=0.0, duration=2000))
qp = QProgram()

The measure operation has the same behaviour in both vendors.
Time of flight between readout pulse and beginning of acquisition is retrieved from the instrument's settings.
qp.measure(bus="readout_bus", waveform=readout_pair, weights=weights_pair, save_adc=True)


[734](https://github.com/qilimanjaro-tech/qililab/pull/734)
[736](https://github.com/qilimanjaro-tech/qililab/pull/736)
[738](https://github.com/qilimanjaro-tech/qililab/pull/738)

- Update Qibo version to `v.0.2.8`.
[732](https://github.com/qilimanjaro-tech/qililab/pull/732)

Improvements

- Introduced `QProgram.with_bus_mapping` method to remap buses within the QProgram.

Example:

Python
Define the bus mapping
bus_mapping = {"drive": "drive_q0"}

Apply the bus mapping to a QProgram instance
mapped_qprogram = qprogram.with_bus_mapping(bus_mapping=bus_mapping)


[729](https://github.com/qilimanjaro-tech/qililab/pull/729)
[740](https://github.com/qilimanjaro-tech/qililab/pull/740)

- Introduced `QProgram.with_calibration` method to apply calibrated waveforms and weights to the QProgram.

Example:

Python
Load the calibration data from a file
calibration = Calibration.load_from('calibration_data.yml')

Apply the calibration to a QProgram instance
calibrated_qprogram = qprogram.with_calibration(calibration=calibration)


[729](https://github.com/qilimanjaro-tech/qililab/pull/729)
[736](https://github.com/qilimanjaro-tech/qililab/pull/736)

- Extended `Platform.execute_qprogram` method to accept a calibration instance.

Python
Load the calibration data from a file
calibration = Calibration.load_from('calibration_data.yml')

platform.execute_qprogram(qprogram=qprogram, calibration=calibration)


[729](https://github.com/qilimanjaro-tech/qililab/pull/729)

- Added interfaces for Qblox and Quantum Machines to QProgram. The interfaces contain vendor-specific methods and parameters. They can be accessed by `qprogram.qblox` and `qprogram.quantum_machines` properties.

[736](https://github.com/qilimanjaro-tech/qililab/pull/736)

- Added `time_of_flight` setting to Qblox QRM and QRM-RF sequencers.

[738](https://github.com/qilimanjaro-tech/qililab/pull/738)

Breaking changes

- QProgram interface now contains methods and parameters that have common functionality for all hardware vendors. Vendor-specific methods and parameters have been move to their respective interface.

Examples:

Python
Acquire method has been moved to Qblox interface. Instead of running
qp.acquire(bus="readout_q0_bus", weights=weights)
you should run
qp.qblox.acquire(bus="readout_q0_bus", weights=weights)

Play method with `wait_time` parameter has been moved to Qblox interface. Instead of running
qp.play(bus="readout_q0_bus", waveform=waveform, wait_time=40)
you should run
qp.qblox.play(bus="readout_q0_bus", waveform=waveform, wait_time=40)

`disable_autosync` parameter has been moved to Qblox interface. Instead of running
qp = QProgram(disable_autosync=True)
you should run
qp = QProgram()
qp.qblox.disable_autosync = True

Measure method with parameters `rotation` and `demodulation` has been moved to Quantum Machines interface. Instead of running
qp.measure(bus="readout_q0_bus", waveform=waveform, weights=weights, save_adc=True, rotation=np.pi, demodulation=True)
you should run
qp.quantum_machines.measure(bus="readout_q0_bus", waveform=waveform, weights=weights, save_adc=True, rotation=np.pi, demodulation=True)


[736](https://github.com/qilimanjaro-tech/qililab/pull/736)

- `time_of_flight` parameter must be added to Qblox QRM and QRM-RF sequencers's runcard settings.

[738](https://github.com/qilimanjaro-tech/qililab/pull/738)

Deprecations / Removals

- Remove `qiboconnection` dependency from Qililab. It is not a requirement anymore.
[732](https://github.com/qilimanjaro-tech/qililab/pull/732)

- Following the remove of Qiboconnection, `LivePlot` has been removed along with the creation of a `Platform` via API.
[732](https://github.com/qilimanjaro-tech/qililab/pull/732)

- Remove the deprecated `path` argument from `build_platform()`.

[739](https://github.com/qilimanjaro-tech/qililab/pull/739)

0.26.2

New features since last release

- Introduce the Two-Step pulse shape to improve readout
[730](https://github.com/qilimanjaro-tech/qililab/pull/730)

Deprecations / Removals

- Remove qiboconnection_api.block_device() and release_device()
[728](https://github.com/qilimanjaro-tech/qililab/pull/728)

0.26.1

Bug fixes

- Hotfix for the 2readout problem
[720](https://github.com/qilimanjaro-tech/qililab/pull/720)

0.25.1

Bug fixes

- Appended hardcoded Time of Flight
[711](https://github.com/qilimanjaro-tech/qililab/pull/711)

0.25.0

New features since last release

- Add FlatTop pulse shape
[680](https://github.com/qilimanjaro-tech/qililab/pull/680)

- Add FlatTop waveform
[680](https://github.com/qilimanjaro-tech/qililab/pull/680)

- Add support for multiple QRM modules
[680](https://github.com/qilimanjaro-tech/qililab/pull/680)

- Update qpysequence to 10.1
[680](https://github.com/qilimanjaro-tech/qililab/pull/680)

Improvements

- The method `CalibrationNode._execute_notebook()` now changes the working directory to the notebook directory before the execution and restores the previous one after the papermill execution. It allows the notebooks now to use relative paths. Also, the initialization of `CalibrationNode` will now contain absolute paths for the attributes `nb_folder` and `nb_path`
[693](https://github.com/qilimanjaro-tech/qililab/pull/693)

Breaking changes

- Added support for Qblox cluster firmware v0.6.1 and qblox-instruments v0.11.2. This changes some of the i/o mappings in the runcard for qblox sequencers so with older versions is broken.
[680](https://github.com/qilimanjaro-tech/qililab/pull/680)

Documentation

- Added documentation for QProgram.

Bug fixes

- Resolved an issue where attempting to execute a previously compiled QUA program on a newly instantiated Quantum Machine resulted in errors due to cache invalidation.
[706](https://github.com/qilimanjaro-tech/qililab/pull/706)

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