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Execution on Alice and Bob Quantum Cloud

The Classiq executor supports execution on Alice and Bob logical hardwares.

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Usage

Alice and Bob provide multiple logical targets that we can use. Execution on Alice and Bob requires a valid API key. Additionally, Alice and Bob introduces several customizable hardware parameters (Available through SDK only):

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average_nb_photons

Bit-flip probability decreases exponentially with this parameter, phase-flip probability increases linearly.

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kappa_1

The rate at which the cat qubit loses one photon, creating a bit-flip. Lower values mean lower error rates.

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kappa_2

The rate at which the cat qubit is stabilized using two-photon dissipation. Higher values mean lower error rates.

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distance

The number of times information is duplicated in the repetition code. Phase-flip probability decreases exponentially with this parameter, bit-flip probability increases linearly.

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Execution

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Setting up Backend Preferences

from classiq import AliceBobBackendNames, AliceBobBackendPreferences

backend_preferences = AliceBobBackendPreferences(
    backend_service_provider="Alice & Bob",
    api_key="<API KEY>",
    backend_name=AliceBobBackendNames.LOGICAL_TARGET,
    kappa_1=10.0,  # OR Remove it to keep default value
    kappa_2=1000,  # OR Remove it to keep default value
    distance=3,  # OR Remove it to keep default value
    average_nb_photons=7,  # OR Remove it to keep default value
)

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Setting up execution preferences and adding number of shots

from classiq import ExecutionPreferences

execution_preferences = ExecutionPreferences(
    num_shots=1000,
    backend_preferences=backend_preferences,
)

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Prepare for Hardware-aware synthesis

from classiq import Preferences

preferences = Preferences(
    backend_service_provider=ProviderVendor.ALICE_AND_BOB,
    backend_name=AliceBobBackendNames.LOGICAL_TARGET,
)

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Execute

At this point you should just create your model, set execution preferences and perform Hardware-aware synthesize then execute.
quantum_program = synthesize(your_model, preferences=preferences)
quantum_program = set_quantum_program_execution_preferences(
    quantum_program, execution_preferences
)

result = execute(quantum_program).result()

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Supported Backends

  • “LOGICAL_EARLY”
  • “LOGICAL_TARGET”
  • “LOGICAL_NOISELESS”