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Quantum Advantage Seeker with Kernels (quask)

A software framework to speed up the research in quantum machine learning

We have started rolling out the second version of quask.
Keep in touch to help us improve our alpha!

Our Purpose

What differentiates our software from anything else?

Complex features w/ little code

Easily craft complex machine learning scenarios in just a few lines of code. Our high-level API streamlines the process for researchers.

Reference implementation

Tired of wasting time replicating results from the latest papers? quask serves as a reliable reference implementation for popular literature.

Pedagogical mission

Kickstart your exploration of quantum machine learning with quask. Utilize our set of introductory tutorials to embark on your learning journey.

Features

Backend independent, stable and fully documented, focused toward applications

Backend independent

quask seamlessly integrates with popular frameworks like Qiskit, Pennylane, Braket, and Qibo, utilizing each as a backend for maximum compatibility.

Stable and fully documented

Like any new software, we encounter challenges. We actively address them via extensive testing and detailed documentation to continuously enhance the reliability of our platform.

Focused toward applications

Skip the technical details and dive straight into your tasks. quask simplifies your experience, allowing you to focus on your objectives without unnecessary complexity.

Where do I start?

Do you spare 5 minutes? Install and try quask with our Getting Started guide

Getting Started

What can I do?

These are just some of the features the framework offers

Build a reinforcement learning agent that guides you through the construction of a quantum circuit.

Try it!

Use task-model alignment to estimate the spectral bias between your quantum kernel and your task.

Try it!

Run a geometric test to explore the potential quantum advantage.

Try it!

Powered by quask

List of projects using quask

Automatic and effective discovery of quantum kernels (arxiv 2023)