Managing Execution Budget

Enrolled users can run quantum programs on multiple backends without needing to provide their own credentials, by using run_through_classiq.

When a job is submitted using run_through_classiq, it will only proceed if the estimated cost is within the remaining budget allocated for the chosen provider.

Additionally, we offer methods to monitor usage and set limits, helping you control and optimize your spending.

For example, to set up execution using run_through_classiq on the Amazon Braket SV1 simulator:

from classiq import *


@qfunc
def main(x: Output[QBit]):
    allocate(x)


qprog = synthesize(main)

exec_pref = ExecutionPreferences(
    backend_preferences=AwsBackendPreferences(
        backend_name="SV1",
        run_through_classiq=True,
    )
)

# Assuming you have a pre-defined quantum program "qprog"

with ExecutionSession(qprog, execution_preferences=exec_pref) as es:
    result = es.sample()

Checking the Remaining Budget

To view your remaining execution budget, run the following command:

from classiq import *

budget = get_budget()
print(budget)

A table will be displayed:

Setting a Custom Budget Limit

You can also define a custom spending limit to stay within a desired budget (lower than your total budget). For example:

from classiq import *

budget = set_budget_limit(
    provider_vendor="Amazon Braket",
    limit=90,  # Set a custom limit below the provider's remaining budget
)

To verify the updated limit, simply run print(budget) again. The output will now reflect the new budget cap:

To clear user-defined budget limits, run clear_budget_limit("Amazon Braket").