Overview | Conductor Quantum

Our AI-driven models accelerate quantum device characterization by automating health checks, calibration, and validation. The Conductor Quantum SDK delivers critical parameters in minutes rather than weeks, streamlining your path from raw transport data to operational qubits.

Models return either:

• Boolean classification – e.g. True if the measurement shows pinch‑off
• Dictionary of indices – parameter names mapped to the index (not the actual voltage) in your input array

Regardless of the specific model, the SDK always wraps the response in a ModelResultInfo object:

Field	Type	Description
`id`	`str`	Unique identifier for the execution
`model`	`str`	Name of the executed model
`created_at`	`datetime`	Timestamp (UTC) when the execution was created
`input_file_name`	`str`	Name of the uploaded input file
`input_file_size`	`int`	Size of the input file in bytes
`output`	`Dict`	Model‑specific output (boolean or dictionary of indices)

Model Versioning

Our models use a versioning scheme (v0, v1, etc.) where higher numbers generally indicate improved accuracy and performance. When selecting a model version, consider:

Newer versions typically offer better accuracy and robustness
Specialized versions for specific data types or conditions
Performance variations based on your measurement characteristics

We recommend testing multiple versions to find the optimal one for your quantum device data.

Charge Stability Diagram Analysis

Model	Description	Input Shape	Output Keys	Endpoints
`charge-stability-diagram-segmenter-v0`	Segments a charge stability diagram into different regions	(128, 128)	`segmentation`	Execute

You can see how to use the charge stability diagram models on the Charge Stability Diagram Models page.

Coulomb Blockade Analysis

Model	Description	Input Shape	Output Keys	Endpoints
`coulomb-blockade-classifier-v0`	Determines if a current measurement exhibits Coulomb blockade characteristics	(n, )	`classification`	Execute
`coulomb-blockade-peak-detector-v0`	Detects the locations of Coulomb blockade peaks in current measurement	(n, )	`peak_indices`	Execute
`coulomb-blockade-peak-detector-v1`	Detects the locations of Coulomb blockade peaks in current measurement	(n, )	`peak_indices`	Execute

You can see how to use the Coulomb Blockade models on the Coulomb Blockade Models page.

Pinch-off Analysis

Model	Description	Input Shape	Output Keys	Endpoints
`pinch-off-classifier-v0`	Determines if a current measurement exhibits pinch-off characteristics	(n, )	`classification`	Execute
`pinch-off-parameter-extractor-v0`	Extracts key parameters from pinch-off measurements (cut_off_voltage, transition_voltage, saturation_voltage)	(n, )	`cut_off_index`, `transition_index`, `saturation_index`	Execute

You can see how to use the Pinch-off models on the Pinch-off Models page.

Turn-on Analysis

Model	Description	Input Shape	Output Keys	Endpoints
`turn-on-classifier-v0`	Determines if a current measurement exhibits turn-on characteristics	(n, )	`classification`	Execute
`turn-on-parameter-extractor-v0`	Extracts the threshold voltage from turn-on measurements	(n, )	`threshold_index`	Execute

You can see how to use the Turn-on models on the Turn-on Models page.