Quantum Control for Silicon Qubits
AI software to enable scalable quantum computers.
Quantum control code examples
# Stanza SDK - Hardware Control from stanza.routines import RoutineRunner from stanza.models import DeviceConfig # Initialize device configuration config = DeviceConfig.from_yaml("device.yaml") runner = RoutineRunner(configs=[config]) # Execute pinchoff sweep measurement result = runner.run( "pinchoff_sweep", gate="LEFT_BARRIER", v_start=-2.0, v_stop=0.0, n_points=100, contact="DRAIN" )
# Models SDK - ML Models from conductorquantum import ConductorQuantum # Initialize client client = ConductorQuantum(token=TOKEN) # Load Charge Stability Diagram data data = np.load("data.npy") # shape (n, m) # Detect the transition lines in the Charge Stability Diagram result = client.models.execute( model="charge-stability-diagram-transition-detector-v3", data=data ) # Access the transition lines result transition_lines = result.output["transition_lines"]

Software to get you from zero to qubits as quickly as possible
Whether you want to build your own control software, get qubits automatically or use our pre-trained models, we have you covered.
ML models for analyzing noisy quantum dot data. Available through a simple to use Python SDK that integrates seemlessly with Stanza.
Hardware-level control software that integrates with your favorite control electronics to take you from zero to qubits automatically.
Unified Config
A single configuration format for all of your semiconductor devices, so starting a new experiment is a breeze.
name: "SiMOS_device" contacts: IN: {type: SOURCE, control_channel: 1, measure_channel: 1, v_lower_bound: -3.0, v_upper_bound: 3.0} OUT: {type: DRAIN, control_channel: 2, measure_channel: 2, v_lower_bound: -3.0, v_upper_bound: 3.0} gates: G1: {type: BARRIER, control_channel: 3, measure_channel: 3, v_lower_bound: -3.0, v_upper_bound: 3.0} G2: {type: PLUNGER, control_channel: 4, measure_channel: 4, v_lower_bound: -3.0, v_upper_bound: 3.0} G3: {type: BARRIER, control_channel: 5, measure_channel: 5, v_lower_bound: -3.0, v_upper_bound: 3.0} routines: - name: Characterization routines: - name: leakage_test parameters: leakage_threshold_resistance: 50e6 leakage_threshold_count: 0 - name: global_accumulation parameters: step_size: 1e-2 - name: reservoir_characterization parameters: step_size: 1e-2 - name: finger_gate_characterization parameters: step_size: 1e-2 instruments: - name: qdac2-control type: CONTROL driver: qdac2 ip_addr: 127.0.0.1 slew_rate: 1.0 - name: qdac2-measurement type: MEASUREMENT driver: qdac2 ip_addr: 127.0.0.1 measurement_duration: 1e-3 sample_time: 10e-6
Software that Scales
Specialized for spin qubits which suffer most from difficult control and tune-up challenges. Built for scale.
See our Models in Action
Our models accurately analyze your quantum data, no matter the level of noise.


Coulomb Diamond Segmentation


Charge Stability Diagram Transition Detection


Coulomb Blockade Peak Detection
Frequently Asked Questions
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