Qutes: a Pathway to High-Level Quantum ProgrammingPoster
Despite the impressive growth in quantum programming languages~\cite{gill2024} and the development of a wide array of quantum simulators~\cite{LaRose_2019}, the current tools still face significant limitations. Most existing quantum languages remain relatively low-level~\cite{HSKRH24}, necessitating a deep understanding of quantum circuits and the underlying quantum mechanics. For many developers, the steep learning curve of these languages makes quantum programming complex and often inaccessible to those outside the quantum computing field.
Consequently, there is a pressing need for high-level programming languages that can abstract much of the complexity involved, making quantum programming more intuitive.
To address this challenge, we introduce \Qutes, a new high-level quantum programming language designed to simplify the development process while maintaining the flexibility and power needed for advanced quantum algorithms. Our goal with \Qutes is to make quantum programming more intuitive and accessible by abstracting away the complexities of quantum mechanics, enabling users to engage with quantum computing through high-level constructs. Unlike traditional quantum languages that require programmers to work closely with quantum gates and circuits~\cite{HSKRH24}, \Qutes allows users to focus on higher-order abstractions, making it easier to express quantum computations without being burdened by the intricate details of the underlying hardware. By offering a more approachable interface, \Qutes enables a wider range of researchers, developers, and industry professionals to harness quantum computing technologies effectively, bridging the gap between quantum theory and practical application.
The source code for \Qutes is available online on GitHub\footnote{A current version of the project can be found at \url{https://github.com/GabrieleMessina/qutes_lang}}, providing easy access for developers and researchers. To quickly start working with Qutes, you can use platforms like Colab or GitHub Codespaces.