I am writing a node that performs an accumulation measurement in a single electron transistor. I am wondering what the intended way is to handle different parameters for multiple identical components. Let's say I have a chip with two SETs on the left and on the right.
This is the simplified version of my node parameters
class AccumulationParameters(NodeParameters):
targets_name: ClassVar[str] = "locations"
locations: Optional[list[Literal["left", "right"]]] = None
maximal_current: float = 1e-9
accumulation_voltage_range: tuple[float, float] = (0.0, 1.0)
My node creates a qua program that accumulates all targeted SETs in parallel.
However, it is unclear to me how to handle different parameters for different targets. Let's say I want to allow a maximal current of 2e-9 for the right dot but keep the default parameter for the left. What would be the idiomatic way to set this up?
The only two solutions I see are to either tune the SETs sequentially or add separate parameters for all targets to the NodeParameters. The first gives up on parallelization and I am unsure how the second should be implemented in a scalable and readable way that can be processed by the surrounding qualibrate tooling.
I am writing a node that performs an accumulation measurement in a single electron transistor. I am wondering what the intended way is to handle different parameters for multiple identical components. Let's say I have a chip with two SETs on the left and on the right.
This is the simplified version of my node parameters
My node creates a qua program that accumulates all targeted SETs in parallel.
However, it is unclear to me how to handle different parameters for different targets. Let's say I want to allow a maximal current of
2e-9for the right dot but keep the default parameter for the left. What would be the idiomatic way to set this up?The only two solutions I see are to either tune the SETs sequentially or add separate parameters for all targets to the NodeParameters. The first gives up on parallelization and I am unsure how the second should be implemented in a scalable and readable way that can be processed by the surrounding qualibrate tooling.