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Support

Welcome to the Classiq Support Center. This page is designed to help you quickly resolve common issues and get additional support if needed.

Frequently Asked Questions (FAQs)

Getting Started

Classiq is quantum-computing software that enables the design, optimization, analysis, and execution of quantum algorithms. Check out how to get started here.
Yes! With Classiq, you can run quantum algorithms on the quantum computers you have access to. Check out our list of quantum providers.

Technical Questions

This error arises when your authentication credentials are denied. Try overriding your authentication credentials by executing authenticate(overwrite=True).
If you’re experiencing failed attempts to reconnect to the Studio or long loading times, please try closing and reopening your web browser.
Try authenticating again using:
import classiq

classiq.authenticate()
To prevent such problems in the future, it is a good practice to begin code files in the Studio with authenticate().
Some example notebooks (e.g., chemistry) require additional packages in the Studio. First, try:
pip install "classiq[chemistry]"
If it still doesn’t work, reset the virtual environment by running:
reset-user-env
If none of these options work, reach out to us on the Community Slack.
Use quantum_program_from_qasm().

Contributing to the Library

You can find contribution guidelines on this page.

Designing Quantum Models

In Classiq, you can define any observable as a linear combination of Pauli strings. To measure a set of observables from a quantum program, see Execution Session and the Execution Tutorial.
You can synthesize the quantum circuit using Constraints. See Quantum Program Constraints.
You can synthesize the quantum program using hardware-aware synthesis. See Hardware-Aware Synthesis.
Using control, you can define multi-qubit controls and gates. You can also use if_ for classical control of quantum gates. See Classical Control Flow.
There are two ways to work around this: either bind the qubits you want to a QArray (see bind) or slice the QArrays (see Path Operators).
Use the apply_to_all function. See Utility functions.
You can use the free() function. For more information, see Uncomputation.
Use qprog.data.width and qprog.transpiled_circuit.depth.

Execution

Use ExecutionPreferences and set the backend appropriately. The Execution Tutorial shows this step by step.
In Qmod, it is possible to use Pyomo to formulate the optimization problem. See Problem Formulation.
Use ExecutionPreferences and set the number of shots. See the Execution Tutorial.
After defining the quantum program, use ExecutionSession.minimize() or ExecutionSession.estimate() for VQAs. See Execution Tutorial 2: Expectation Values and Parameterized Quantum Programs.

Need More Help?

If your question is not answered here, please:
  • Reach out in the #support-and-questions channel on our community Slack.
  • For additional assistance, to report a bug, or to request a feature, submit a ticket via our Support Center.