atomiq.components.optoelectronics.lightmodulator ================================================ .. py:module:: atomiq.components.optoelectronics.lightmodulator Classes ------- .. autoapisummary:: atomiq.components.optoelectronics.lightmodulator.Shutter atomiq.components.optoelectronics.lightmodulator.LightModulator atomiq.components.optoelectronics.lightmodulator.RFLightModulator atomiq.components.optoelectronics.lightmodulator.AOM Module Contents --------------- .. py:class:: Shutter(switch, invert = False, opening_time = 0, closing_time = 0, *args, **kwargs) Bases: :py:obj:`atomiq.components.primitives.Component`, :py:obj:`atomiq.components.primitives.Switchable` Component to switch light on or off depending on a logical signal. This could be a mechanical shutter or a binary only amplitude modulator (e.g. AOM, EOM, Pockels cell etc.). It requires a class:Switchable switch that operates the shutter :param switch: Switch that operates the shutter, e.g. TTL :param invert: invert the logic of on and off :param opening_time: Time in s it takes from the arrival of the TTL until the shutter is fully opened (default 0) :param closing_time: Time in s it takes from the arrival of the TTL until the shutter is completely closed (default 0). Note that if closing_time is > 0 the shutter is already closing before the time at which the off() method is called .. py:attribute:: kernel_invariants .. py:attribute:: switch .. py:attribute:: invert :value: False .. py:attribute:: opening_time :value: 0 .. py:attribute:: closing_time :value: 0 .. py:method:: on() Opens the shutter. The time cursor is moved back in time to accommodate the `opening_time` of the shutter. After executing the `on` (or `off` if inverted) method of the defined switch the time cursor is then forwarded by `opening_time` again. The time cursor advancement is therefore given by the `switch.on()` or `switch.off()` method. .. py:method:: off() Closes the shutter. The time cursor is moved back in time to accommodate the `closing_time` of the shutter. After executing the `off` (or `on` if inverted) method of the defined switch the time cursor is then forwarded by `closing_time` again. The time cursor advancement is therefore given by the `switch.on()` or `switch.off()` method. .. py:attribute:: experiment .. py:attribute:: identifier .. py:attribute:: debug_output :value: False .. py:attribute:: core .. py:attribute:: _kernel_invariants .. py:attribute:: _prepare_done :value: False .. py:attribute:: _build_done :value: False .. py:attribute:: _hooks_done :value: [] .. py:method:: _recursive_prepare() .. py:method:: _prepare() Specify here what should be done for this component in the prepare phase .. py:method:: _recursive_build() .. py:method:: _build() Specify here what should be done for this component in the build phase .. py:method:: _do_prerun() .. py:method:: required_components(ancestors=[]) .. py:method:: _prerun() Specify here what should be done for this component before the run starts. In contrast to the _build() method, the _prerun() routine is executed on the core device before the actual experiment starts. .. py:attribute:: children :value: [] .. py:attribute:: __in_build :value: True .. py:method:: register_child(child) .. py:method:: call_child_method(method, *args, **kwargs) Calls the named method for each child, if it exists for that child, in the order of registration. :param method: Name of the method to call :type method: str :param args: Tuple of positional arguments to pass to all children :param kwargs: Dict of keyword arguments to pass to all children .. py:method:: build() Should be implemented by the user to request arguments. Other initialization steps such as requesting devices may also be performed here. There are two situations where the requested devices are replaced by ``DummyDevice()`` and arguments are set to their defaults (or ``None``) instead: when the repository is scanned to build the list of available experiments and when the dataset browser ``artiq_browser`` is used to open or run the analysis stage of an experiment. Do not rely on being able to operate on devices or arguments in :meth:`build`. Datasets are read-only in this method. Leftover positional and keyword arguments from the constructor are forwarded to this method. This is intended for experiments that are only meant to be executed programmatically (not from the GUI). .. py:method:: get_argument(key, processor, group=None, tooltip=None) Retrieves and returns the value of an argument. This function should only be called from ``build``. :param key: Name of the argument. :param processor: A description of how to process the argument, such as instances of :mod:`~artiq.language.environment.BooleanValue` and :mod:`~artiq.language.environment.NumberValue`. :param group: An optional string that defines what group the argument belongs to, for user interface purposes. :param tooltip: An optional string to describe the argument in more detail, applied as a tooltip to the argument name in the user interface. .. py:method:: setattr_argument(key, processor=None, group=None, tooltip=None) Sets an argument as attribute. The names of the argument and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: interactive(title='') Request arguments from the user interactively. This context manager returns a namespace object on which the method :meth:`~artiq.language.environment.HasEnvironment.setattr_argument` should be called, with the usual semantics. When the context manager terminates, the experiment is blocked and the user is presented with the requested argument widgets. After the user enters values, the experiment is resumed and the namespace contains the values of the arguments. If the interactive arguments request is cancelled, raises :exc:`~artiq.language.environment.CancelledArgsError`. .. py:method:: get_device_db() Returns the full contents of the device database. .. py:method:: get_device(key) Creates and returns a device driver. .. py:method:: setattr_device(key) Sets a device driver as attribute. The names of the device driver and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: set_dataset(key, value, *, unit=None, scale=None, precision=None, broadcast=False, persist=False, archive=True) Sets the contents and handling modes of a dataset. Datasets must be scalars (``bool``, ``int``, ``float`` or NumPy scalar) or NumPy arrays. :param unit: A string representing the unit of the value. :param scale: A numerical factor that is used to adjust the value of the dataset to match the scale or units of the experiment's reference frame when the value is displayed. :param precision: The maximum number of digits to print after the decimal point. Set ``precision=None`` to print as many digits as necessary to uniquely specify the value. Uses IEEE unbiased rounding. :param broadcast: the data is sent in real-time to the master, which dispatches it. :param persist: the master should store the data on-disk. Implies broadcast. :param archive: the data is saved into the local storage of the current run (archived as a HDF5 file). .. py:method:: mutate_dataset(key, index, value) Mutate an existing dataset at the given index (e.g. set a value at a given position in a NumPy array) If the dataset was created in broadcast mode, the modification is immediately transmitted. If the index is a tuple of integers, it is interpreted as ``slice(*index)``. If the index is a tuple of tuples, each sub-tuple is interpreted as ``slice(*sub_tuple)`` (multi-dimensional slicing). .. py:method:: append_to_dataset(key, value) Append a value to a dataset. The target dataset must be a list (i.e. support ``append()``), and must have previously been set from this experiment. The broadcast/persist/archive mode of the given key remains unchanged from when the dataset was last set. Appended values are transmitted efficiently as incremental modifications in broadcast mode. .. py:method:: get_dataset(key, default=NoDefault, archive=True) Returns the contents of a dataset. The local storage is searched first, followed by the master storage (which contains the broadcasted datasets from all experiments) if the key was not found initially. If the dataset does not exist, returns the default value. If no default is provided, raises ``KeyError``. By default, datasets obtained by this method are archived into the output HDF5 file of the experiment. If an archived dataset is requested more than one time or is modified, only the value at the time of the first call is archived. This may impact reproducibility of experiments. :param archive: Set to ``False`` to prevent archival together with the run's results. Default is ``True``. .. py:method:: get_dataset_metadata(key, default=NoDefault) Returns the metadata of a dataset. Returns dictionary with items describing the dataset, including the units, scale and precision. This function is used to get additional information for displaying the dataset. See :meth:`set_dataset` for documentation of metadata items. .. py:method:: setattr_dataset(key, default=NoDefault, archive=True) Sets the contents of a dataset as attribute. The names of the dataset and of the attribute are the same. .. py:method:: set_default_scheduling(priority=None, pipeline_name=None, flush=None) Sets the default scheduling options. This function should only be called from ``build``. .. py:method:: is_on(channel = None) :abstractmethod: .. py:method:: toggle(channel = None) .. py:method:: pulse(pulsetime, channel = '') .. py:class:: LightModulator(*args, **kwargs) Bases: :py:obj:`atomiq.components.primitives.Component`, :py:obj:`atomiq.components.primitives.Parametrizable` An abstract light modulator for frequency, amplitude, phase, polarisation This class serves as a base class for all kinds of electro-optic devices that can change the properties of light. .. py:method:: set_frequency(frequency) :abstractmethod: Set the frequency by which the light is shifted. :param frequency: Frequency in Hz by which the light is shifted. .. py:method:: get_frequency() :abstractmethod: .. py:method:: set_amplitude(amplitude) :abstractmethod: Set the amplitude of the light after the modulator :param amplitude: Relative amplitude [0 .. 1] of the light after the modulator .. py:method:: set_phase(phase) :abstractmethod: Set the phase shift of the light imposed by the modulator :param phase: Phase shift in radians .. py:method:: set_polarisation(angle) :abstractmethod: Set the polarization rotation imposed by the modulator :param angle: Rotation angle in radians .. py:attribute:: kernel_invariants .. py:attribute:: experiment .. py:attribute:: identifier .. py:attribute:: debug_output :value: False .. py:attribute:: core .. py:attribute:: _kernel_invariants .. py:attribute:: _prepare_done :value: False .. py:attribute:: _build_done :value: False .. py:attribute:: _hooks_done :value: [] .. py:method:: _recursive_prepare() .. py:method:: _prepare() Specify here what should be done for this component in the prepare phase .. py:method:: _recursive_build() .. py:method:: _build() Specify here what should be done for this component in the build phase .. py:method:: _do_prerun() .. py:method:: required_components(ancestors=[]) .. py:method:: _prerun() Specify here what should be done for this component before the run starts. In contrast to the _build() method, the _prerun() routine is executed on the core device before the actual experiment starts. .. py:attribute:: children :value: [] .. py:attribute:: __in_build :value: True .. py:method:: register_child(child) .. py:method:: call_child_method(method, *args, **kwargs) Calls the named method for each child, if it exists for that child, in the order of registration. :param method: Name of the method to call :type method: str :param args: Tuple of positional arguments to pass to all children :param kwargs: Dict of keyword arguments to pass to all children .. py:method:: build() Should be implemented by the user to request arguments. Other initialization steps such as requesting devices may also be performed here. There are two situations where the requested devices are replaced by ``DummyDevice()`` and arguments are set to their defaults (or ``None``) instead: when the repository is scanned to build the list of available experiments and when the dataset browser ``artiq_browser`` is used to open or run the analysis stage of an experiment. Do not rely on being able to operate on devices or arguments in :meth:`build`. Datasets are read-only in this method. Leftover positional and keyword arguments from the constructor are forwarded to this method. This is intended for experiments that are only meant to be executed programmatically (not from the GUI). .. py:method:: get_argument(key, processor, group=None, tooltip=None) Retrieves and returns the value of an argument. This function should only be called from ``build``. :param key: Name of the argument. :param processor: A description of how to process the argument, such as instances of :mod:`~artiq.language.environment.BooleanValue` and :mod:`~artiq.language.environment.NumberValue`. :param group: An optional string that defines what group the argument belongs to, for user interface purposes. :param tooltip: An optional string to describe the argument in more detail, applied as a tooltip to the argument name in the user interface. .. py:method:: setattr_argument(key, processor=None, group=None, tooltip=None) Sets an argument as attribute. The names of the argument and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: interactive(title='') Request arguments from the user interactively. This context manager returns a namespace object on which the method :meth:`~artiq.language.environment.HasEnvironment.setattr_argument` should be called, with the usual semantics. When the context manager terminates, the experiment is blocked and the user is presented with the requested argument widgets. After the user enters values, the experiment is resumed and the namespace contains the values of the arguments. If the interactive arguments request is cancelled, raises :exc:`~artiq.language.environment.CancelledArgsError`. .. py:method:: get_device_db() Returns the full contents of the device database. .. py:method:: get_device(key) Creates and returns a device driver. .. py:method:: setattr_device(key) Sets a device driver as attribute. The names of the device driver and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: set_dataset(key, value, *, unit=None, scale=None, precision=None, broadcast=False, persist=False, archive=True) Sets the contents and handling modes of a dataset. Datasets must be scalars (``bool``, ``int``, ``float`` or NumPy scalar) or NumPy arrays. :param unit: A string representing the unit of the value. :param scale: A numerical factor that is used to adjust the value of the dataset to match the scale or units of the experiment's reference frame when the value is displayed. :param precision: The maximum number of digits to print after the decimal point. Set ``precision=None`` to print as many digits as necessary to uniquely specify the value. Uses IEEE unbiased rounding. :param broadcast: the data is sent in real-time to the master, which dispatches it. :param persist: the master should store the data on-disk. Implies broadcast. :param archive: the data is saved into the local storage of the current run (archived as a HDF5 file). .. py:method:: mutate_dataset(key, index, value) Mutate an existing dataset at the given index (e.g. set a value at a given position in a NumPy array) If the dataset was created in broadcast mode, the modification is immediately transmitted. If the index is a tuple of integers, it is interpreted as ``slice(*index)``. If the index is a tuple of tuples, each sub-tuple is interpreted as ``slice(*sub_tuple)`` (multi-dimensional slicing). .. py:method:: append_to_dataset(key, value) Append a value to a dataset. The target dataset must be a list (i.e. support ``append()``), and must have previously been set from this experiment. The broadcast/persist/archive mode of the given key remains unchanged from when the dataset was last set. Appended values are transmitted efficiently as incremental modifications in broadcast mode. .. py:method:: get_dataset(key, default=NoDefault, archive=True) Returns the contents of a dataset. The local storage is searched first, followed by the master storage (which contains the broadcasted datasets from all experiments) if the key was not found initially. If the dataset does not exist, returns the default value. If no default is provided, raises ``KeyError``. By default, datasets obtained by this method are archived into the output HDF5 file of the experiment. If an archived dataset is requested more than one time or is modified, only the value at the time of the first call is archived. This may impact reproducibility of experiments. :param archive: Set to ``False`` to prevent archival together with the run's results. Default is ``True``. .. py:method:: get_dataset_metadata(key, default=NoDefault) Returns the metadata of a dataset. Returns dictionary with items describing the dataset, including the units, scale and precision. This function is used to get additional information for displaying the dataset. See :meth:`set_dataset` for documentation of metadata items. .. py:method:: setattr_dataset(key, default=NoDefault, archive=True) Sets the contents of a dataset as attribute. The names of the dataset and of the attribute are the same. .. py:method:: set_default_scheduling(priority=None, pipeline_name=None, flush=None) Sets the default scheduling options. This function should only be called from ``build``. .. py:method:: set_parameter(value, channel = None) .. py:class:: RFLightModulator(rfsource, freq_limit, amp_limit = (0.0, 1.0), soft_amp_limit = (False, False), *args, **kwargs) Bases: :py:obj:`LightModulator` A light modulator driven by an RF source This class serves as a base class for devices like AOM, EOM, etc. :param rfsource: The rfsource that drives the modulator :param freq_limit: Tuple (freq_min, freq_max) giving the minimum/maximum RF frequency that the modulator can handle in Hz. :param amp_limit: Tuple (amp_min, amp_max) giving the minimum/maximum RF attenuation that the modulator can do in range [0..1]. :param soft_amp_limit: Tuple[bool] (lower, upper) setting the behavior if an amplitude value outside the limits is requested. If ``True``, a warning is emitted and the offending value is set to the minimum/maximum allowed value. If ``False``, an error is emitted and no value is set on the device. .. py:attribute:: kernel_invariants .. py:attribute:: rfsource .. py:attribute:: soft_amp_limit :value: (False, False) .. py:method:: ramp(duration, frequency_start = NAN, frequency_end = NAN, amplitude_start = NAN, amplitude_end = NAN, ramp_timestep = NAN, ramp_steps = -1) Ramp frequency and/or power/amplitude over a given duration. Parameters default to ``-1`` or ``nan`` to indicate no change. If no starting value is given, the ramp starts from the last frequency/amplitude which was set. This method advances the timeline by ´duration´ :param duration: ramp duration [s] :param frequency_start: initial frequency [Hz] :param frequency_end: end frequency [Hz] :param amplitude_start: initial amplitude :param amplitude_end: end amplitude .. py:method:: arb(duration, samples_amp = [], samples_freq = [], samples_phase = [], repetitions = 1, prepare_only = False, run_prepared = False, transform_amp=identity_float, transform_freq=identity_float, transform_phase=identity_float) Play Arbitrary Samples from a List This method allows to set the output amplitude, frequency an phase according to the values specified in respective lists. The whole sequence is played in the specified duration. The pattern store in the sample list can also be repeated. We supports a scheme to prepare the arb function before it is actually used. If that is needed, run this function with `prepapre_only = True` when the arb should be prepared and with `run_only = True` when the prepared arb should be played. In both calls the other parameters have to be passed. :param samples_amp: List of amplitude samples. If this list is empty (default), the amplitude is not modified. :param samples_freq: List of frequency samples. If this list is empty (default), the frequency is not modified. :param samples_phase: List of phase samples. If this list is empty (default), the phase is not modified. :param duration: The time in which the whole sequence of samples should be played back [s]. :param repetitions: Number of times the sequence of all samples should be played. (default 1) .. py:method:: _arb(duration, samples_amp = [], samples_freq = [], samples_phase = [], repetitions = 1, prepare_only = False, run_prepared = False, transform_amp=identity_float, transform_freq=identity_float, transform_phase=identity_float) .. py:method:: get_frequency_min() .. py:method:: get_frequency_max() .. py:method:: get_frequency() .. py:method:: _check_and_set_frequency(frequency) .. py:method:: set_frequency(frequency) Set the frequency by which the light is shifted. :param frequency: Frequency in Hz by which the light is shifted. .. py:method:: get_amplitude_min() .. py:method:: get_amplitude_max() .. py:method:: get_amplitude() .. py:method:: _check_amplitude(amplitude) .. py:method:: set_amplitude(amplitude) Set the amplitude of the light after the modulator :param amplitude: Relative amplitude [0 .. 1] of the light after the modulator .. py:method:: get_phase() .. py:method:: set_phase(value) Set the phase shift of the light imposed by the modulator :param phase: Phase shift in radians .. py:method:: on() .. py:method:: off() .. py:method:: set_polarisation(angle) :abstractmethod: Set the polarization rotation imposed by the modulator :param angle: Rotation angle in radians .. py:attribute:: experiment .. py:attribute:: identifier .. py:attribute:: debug_output :value: False .. py:attribute:: core .. py:attribute:: _kernel_invariants .. py:attribute:: _prepare_done :value: False .. py:attribute:: _build_done :value: False .. py:attribute:: _hooks_done :value: [] .. py:method:: _recursive_prepare() .. py:method:: _prepare() Specify here what should be done for this component in the prepare phase .. py:method:: _recursive_build() .. py:method:: _build() Specify here what should be done for this component in the build phase .. py:method:: _do_prerun() .. py:method:: required_components(ancestors=[]) .. py:method:: _prerun() Specify here what should be done for this component before the run starts. In contrast to the _build() method, the _prerun() routine is executed on the core device before the actual experiment starts. .. py:attribute:: children :value: [] .. py:attribute:: __in_build :value: True .. py:method:: register_child(child) .. py:method:: call_child_method(method, *args, **kwargs) Calls the named method for each child, if it exists for that child, in the order of registration. :param method: Name of the method to call :type method: str :param args: Tuple of positional arguments to pass to all children :param kwargs: Dict of keyword arguments to pass to all children .. py:method:: build() Should be implemented by the user to request arguments. Other initialization steps such as requesting devices may also be performed here. There are two situations where the requested devices are replaced by ``DummyDevice()`` and arguments are set to their defaults (or ``None``) instead: when the repository is scanned to build the list of available experiments and when the dataset browser ``artiq_browser`` is used to open or run the analysis stage of an experiment. Do not rely on being able to operate on devices or arguments in :meth:`build`. Datasets are read-only in this method. Leftover positional and keyword arguments from the constructor are forwarded to this method. This is intended for experiments that are only meant to be executed programmatically (not from the GUI). .. py:method:: get_argument(key, processor, group=None, tooltip=None) Retrieves and returns the value of an argument. This function should only be called from ``build``. :param key: Name of the argument. :param processor: A description of how to process the argument, such as instances of :mod:`~artiq.language.environment.BooleanValue` and :mod:`~artiq.language.environment.NumberValue`. :param group: An optional string that defines what group the argument belongs to, for user interface purposes. :param tooltip: An optional string to describe the argument in more detail, applied as a tooltip to the argument name in the user interface. .. py:method:: setattr_argument(key, processor=None, group=None, tooltip=None) Sets an argument as attribute. The names of the argument and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: interactive(title='') Request arguments from the user interactively. This context manager returns a namespace object on which the method :meth:`~artiq.language.environment.HasEnvironment.setattr_argument` should be called, with the usual semantics. When the context manager terminates, the experiment is blocked and the user is presented with the requested argument widgets. After the user enters values, the experiment is resumed and the namespace contains the values of the arguments. If the interactive arguments request is cancelled, raises :exc:`~artiq.language.environment.CancelledArgsError`. .. py:method:: get_device_db() Returns the full contents of the device database. .. py:method:: get_device(key) Creates and returns a device driver. .. py:method:: setattr_device(key) Sets a device driver as attribute. The names of the device driver and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: set_dataset(key, value, *, unit=None, scale=None, precision=None, broadcast=False, persist=False, archive=True) Sets the contents and handling modes of a dataset. Datasets must be scalars (``bool``, ``int``, ``float`` or NumPy scalar) or NumPy arrays. :param unit: A string representing the unit of the value. :param scale: A numerical factor that is used to adjust the value of the dataset to match the scale or units of the experiment's reference frame when the value is displayed. :param precision: The maximum number of digits to print after the decimal point. Set ``precision=None`` to print as many digits as necessary to uniquely specify the value. Uses IEEE unbiased rounding. :param broadcast: the data is sent in real-time to the master, which dispatches it. :param persist: the master should store the data on-disk. Implies broadcast. :param archive: the data is saved into the local storage of the current run (archived as a HDF5 file). .. py:method:: mutate_dataset(key, index, value) Mutate an existing dataset at the given index (e.g. set a value at a given position in a NumPy array) If the dataset was created in broadcast mode, the modification is immediately transmitted. If the index is a tuple of integers, it is interpreted as ``slice(*index)``. If the index is a tuple of tuples, each sub-tuple is interpreted as ``slice(*sub_tuple)`` (multi-dimensional slicing). .. py:method:: append_to_dataset(key, value) Append a value to a dataset. The target dataset must be a list (i.e. support ``append()``), and must have previously been set from this experiment. The broadcast/persist/archive mode of the given key remains unchanged from when the dataset was last set. Appended values are transmitted efficiently as incremental modifications in broadcast mode. .. py:method:: get_dataset(key, default=NoDefault, archive=True) Returns the contents of a dataset. The local storage is searched first, followed by the master storage (which contains the broadcasted datasets from all experiments) if the key was not found initially. If the dataset does not exist, returns the default value. If no default is provided, raises ``KeyError``. By default, datasets obtained by this method are archived into the output HDF5 file of the experiment. If an archived dataset is requested more than one time or is modified, only the value at the time of the first call is archived. This may impact reproducibility of experiments. :param archive: Set to ``False`` to prevent archival together with the run's results. Default is ``True``. .. py:method:: get_dataset_metadata(key, default=NoDefault) Returns the metadata of a dataset. Returns dictionary with items describing the dataset, including the units, scale and precision. This function is used to get additional information for displaying the dataset. See :meth:`set_dataset` for documentation of metadata items. .. py:method:: setattr_dataset(key, default=NoDefault, archive=True) Sets the contents of a dataset as attribute. The names of the dataset and of the attribute are the same. .. py:method:: set_default_scheduling(priority=None, pipeline_name=None, flush=None) Sets the default scheduling options. This function should only be called from ``build``. .. py:method:: set_parameter(value, channel = None) .. py:class:: AOM(center_freq, freq_limit = None, bandwidth = None, switch = None, switching_delay = 0, passes = 1, order = 1, am_calibration = None, *args, **kwargs) Bases: :py:obj:`RFLightModulator`, :py:obj:`atomiq.components.primitives.Switchable` An acousto-optical modulator to alter amplitude, frequency and phase of the light. A component to represent an AOM to attenuate, switch and frequency-shift light. It is controlled by an :class:`~atomiq.components.electronics.rfsource.RFSource` and a :class:`~atomiq.components.primitives.Switchable` to rapidly switch the light on and off. As such, the AOM works also as a (non-perfect) shutter. :param rfsource: The rf source that drives the AOM :param center_freq: RF center frequency of the AOM in Hz. :param freq_limit: Tuple (freq_min, freq_max) giving the minimum/maximum RF frequency that the AOM can handle in Hz. Either freq_limit xor bandwidth must be given :param bandwidth: RF bandwidth of the AOM around the center frequency in Hz. Either bandwidth xor freq_limit must be given. :param switch: An optional switch to rapidly switch on and off the AOM. If none is given the rfsource is used to switch. :param switching_delay: the switching delay of the AOM, i.e. the time it takes from the arrival of the TTL to having full optical power. (default 0) :param passes: How often does the beam pass the AOM? Singlepass -> 1, Doublepass -> 2 (default 1) :param order: The diffraction order the AOM is aligned to. -2, -1, 1, 2 ... (default 1) :param am_calibration: Calibration of RF power vs output power. Typically an inverse sigmoid. (default none) .. py:attribute:: kernel_invariants .. py:attribute:: center_freq .. py:attribute:: switching_delay :value: 0 .. py:attribute:: passes :value: 1 .. py:attribute:: order :value: 1 .. py:method:: _prerun() Specify here what should be done for this component before the run starts. In contrast to the _build() method, the _prerun() routine is executed on the core device before the actual experiment starts. .. py:method:: get_frequency_min() .. py:method:: get_frequency_max() .. py:method:: get_frequency() .. py:method:: set_frequency(frequency) Set the frequency shift of the light coming out of the AOM .. py:method:: set_detuning(detuning) Set the frequency shift of the light coming out of the AOM relative to the center frequency :param detuning: Detuning from the AOM center frequency in Hz .. py:method:: detune(detuning) Alias for set_detuning() .. py:method:: _amplitude_transform_calibration(amplitude) .. py:method:: _amplitude_transform_identity(amplitude) .. py:method:: set_amplitude(amplitude) Set the amplitude of the light after the modulator :param amplitude: Relative amplitude [0 .. 1] of the light after the modulator .. py:method:: arb(duration, samples_amp = [], samples_freq = [], samples_det = [], samples_phase = [], repetitions = 1, prepare_only = False, run_prepared = False, transform_amp=identity_float, transform_freq=identity_float, transform_phase=identity_float) Play Arbitrary Samples from a List This method allows to set the output amplitude, frequency an phase according to the values specified in respective lists. The whole sequence is played in the specified duration. The pattern store in the sample list can also be repeated. We supports a scheme to prepare the arb function before it is actually used. If that is needed, run this function with `prepapre_only = True` when the arb should be prepared and with `run_only = True` when the prepared arb should be played. In both calls the other parameters have to be passed. :param samples_amp: List of amplitude samples. If this list is empty (default), the amplitude is not modified. :param samples_freq: List of frequency samples. If this list is empty (default), the frequency is not modified. :param samples_det: List of frequency samples relative to the center frequency. If this list is empty (default), the frequency is not modified. This overwrites `samples_frequency` :param samples_phase: List of phase samples. If this list is empty (default), the phase is not modified. :param duration: The time in which the whole sequence of samples should be played back [s]. :param repetitions: Number of times the sequence of all samples should be played. (default 1) .. py:method:: ramp(duration, frequency_start = NAN, frequency_end = NAN, amplitude_start = NAN, amplitude_end = NAN, ramp_timestep = NAN, ramp_steps = -1) Ramp frequency and amplitude over a given duration. Parameters default to ``-1`` or ``nan`` to indicate no change. If the start frequency/amplitude is set to ``nan``, the ramp starts from the last frequency/amplitude which was set. This method advances the timeline by ´duration´. .. note:: The amplitude calibration is only applied at the start and end point of the ramp to reduce calculation overhead. This relies on the calibration being sufficiently linear in the ramp range. :param duration: ramp duration [s] :param frequency_start: initial frequency shift of the light exiting the AOM [Hz] :param frequency_end: final frequency shift of the light exiting the AOM [Hz] :param amplitude_start: initial amplitude :param amplitude_end: end amplitude .. py:method:: on() Turns on the AOM. The time cursor is moved back in time to accommodate the `switching_delay` of the AOM. After executing the `on` method of the defined switch the time cursor is then forwarded by `switching_delay` again. The time cursor advancement is therefore given by the `switch.on()` method. .. py:method:: off() Turns off the AOM. The time cursor is moved back in time to accommodate the `switching_delay` of the AOM. After executing the `off` method of the defined switch the time cursor is then forwarded by `switching_delay` again. The time cursor advancement is therefore given by the `switch.off()` method. .. py:attribute:: rfsource .. py:attribute:: soft_amp_limit :value: (False, False) .. py:method:: _arb(duration, samples_amp = [], samples_freq = [], samples_phase = [], repetitions = 1, prepare_only = False, run_prepared = False, transform_amp=identity_float, transform_freq=identity_float, transform_phase=identity_float) .. py:method:: _check_and_set_frequency(frequency) .. py:method:: get_amplitude_min() .. py:method:: get_amplitude_max() .. py:method:: get_amplitude() .. py:method:: _check_amplitude(amplitude) .. py:method:: get_phase() .. py:method:: set_phase(value) Set the phase shift of the light imposed by the modulator :param phase: Phase shift in radians .. py:method:: set_polarisation(angle) :abstractmethod: Set the polarization rotation imposed by the modulator :param angle: Rotation angle in radians .. py:attribute:: experiment .. py:attribute:: identifier .. py:attribute:: debug_output :value: False .. py:attribute:: core .. py:attribute:: _kernel_invariants .. py:attribute:: _prepare_done :value: False .. py:attribute:: _build_done :value: False .. py:attribute:: _hooks_done :value: [] .. py:method:: _recursive_prepare() .. py:method:: _prepare() Specify here what should be done for this component in the prepare phase .. py:method:: _recursive_build() .. py:method:: _build() Specify here what should be done for this component in the build phase .. py:method:: _do_prerun() .. py:method:: required_components(ancestors=[]) .. py:attribute:: children :value: [] .. py:attribute:: __in_build :value: True .. py:method:: register_child(child) .. py:method:: call_child_method(method, *args, **kwargs) Calls the named method for each child, if it exists for that child, in the order of registration. :param method: Name of the method to call :type method: str :param args: Tuple of positional arguments to pass to all children :param kwargs: Dict of keyword arguments to pass to all children .. py:method:: build() Should be implemented by the user to request arguments. Other initialization steps such as requesting devices may also be performed here. There are two situations where the requested devices are replaced by ``DummyDevice()`` and arguments are set to their defaults (or ``None``) instead: when the repository is scanned to build the list of available experiments and when the dataset browser ``artiq_browser`` is used to open or run the analysis stage of an experiment. Do not rely on being able to operate on devices or arguments in :meth:`build`. Datasets are read-only in this method. Leftover positional and keyword arguments from the constructor are forwarded to this method. This is intended for experiments that are only meant to be executed programmatically (not from the GUI). .. py:method:: get_argument(key, processor, group=None, tooltip=None) Retrieves and returns the value of an argument. This function should only be called from ``build``. :param key: Name of the argument. :param processor: A description of how to process the argument, such as instances of :mod:`~artiq.language.environment.BooleanValue` and :mod:`~artiq.language.environment.NumberValue`. :param group: An optional string that defines what group the argument belongs to, for user interface purposes. :param tooltip: An optional string to describe the argument in more detail, applied as a tooltip to the argument name in the user interface. .. py:method:: setattr_argument(key, processor=None, group=None, tooltip=None) Sets an argument as attribute. The names of the argument and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: interactive(title='') Request arguments from the user interactively. This context manager returns a namespace object on which the method :meth:`~artiq.language.environment.HasEnvironment.setattr_argument` should be called, with the usual semantics. When the context manager terminates, the experiment is blocked and the user is presented with the requested argument widgets. After the user enters values, the experiment is resumed and the namespace contains the values of the arguments. If the interactive arguments request is cancelled, raises :exc:`~artiq.language.environment.CancelledArgsError`. .. py:method:: get_device_db() Returns the full contents of the device database. .. py:method:: get_device(key) Creates and returns a device driver. .. py:method:: setattr_device(key) Sets a device driver as attribute. The names of the device driver and of the attribute are the same. The key is added to the instance's kernel invariants. .. py:method:: set_dataset(key, value, *, unit=None, scale=None, precision=None, broadcast=False, persist=False, archive=True) Sets the contents and handling modes of a dataset. Datasets must be scalars (``bool``, ``int``, ``float`` or NumPy scalar) or NumPy arrays. :param unit: A string representing the unit of the value. :param scale: A numerical factor that is used to adjust the value of the dataset to match the scale or units of the experiment's reference frame when the value is displayed. :param precision: The maximum number of digits to print after the decimal point. Set ``precision=None`` to print as many digits as necessary to uniquely specify the value. Uses IEEE unbiased rounding. :param broadcast: the data is sent in real-time to the master, which dispatches it. :param persist: the master should store the data on-disk. Implies broadcast. :param archive: the data is saved into the local storage of the current run (archived as a HDF5 file). .. py:method:: mutate_dataset(key, index, value) Mutate an existing dataset at the given index (e.g. set a value at a given position in a NumPy array) If the dataset was created in broadcast mode, the modification is immediately transmitted. If the index is a tuple of integers, it is interpreted as ``slice(*index)``. If the index is a tuple of tuples, each sub-tuple is interpreted as ``slice(*sub_tuple)`` (multi-dimensional slicing). .. py:method:: append_to_dataset(key, value) Append a value to a dataset. The target dataset must be a list (i.e. support ``append()``), and must have previously been set from this experiment. The broadcast/persist/archive mode of the given key remains unchanged from when the dataset was last set. Appended values are transmitted efficiently as incremental modifications in broadcast mode. .. py:method:: get_dataset(key, default=NoDefault, archive=True) Returns the contents of a dataset. The local storage is searched first, followed by the master storage (which contains the broadcasted datasets from all experiments) if the key was not found initially. If the dataset does not exist, returns the default value. If no default is provided, raises ``KeyError``. By default, datasets obtained by this method are archived into the output HDF5 file of the experiment. If an archived dataset is requested more than one time or is modified, only the value at the time of the first call is archived. This may impact reproducibility of experiments. :param archive: Set to ``False`` to prevent archival together with the run's results. Default is ``True``. .. py:method:: get_dataset_metadata(key, default=NoDefault) Returns the metadata of a dataset. Returns dictionary with items describing the dataset, including the units, scale and precision. This function is used to get additional information for displaying the dataset. See :meth:`set_dataset` for documentation of metadata items. .. py:method:: setattr_dataset(key, default=NoDefault, archive=True) Sets the contents of a dataset as attribute. The names of the dataset and of the attribute are the same. .. py:method:: set_default_scheduling(priority=None, pipeline_name=None, flush=None) Sets the default scheduling options. This function should only be called from ``build``. .. py:method:: set_parameter(value, channel = None) .. py:method:: is_on(channel = None) :abstractmethod: .. py:method:: toggle(channel = None) .. py:method:: pulse(pulsetime, channel = '')