POPL 2025
Sun 19 - Sat 25 January 2025 Denver, Colorado, United States

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.

Extended Abstract (planqc25-paper71.pdf)346KiB
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PLanQC
Ryan Shaffer AWS Quantum Technologies, Lauren Capelluto AWS Quantum Technologies, Yi-Ting Chen AWS Quantum Technologies, Aaron Berdy AWS Quantum Technologies, Kshitij Chhabra AWS Quantum Technologies, Jean-Christophe Jaskula AWS Quantum Technologies, Eric Kessler AWS Quantum Technologies, Yunong Shi AWS Quantum Technologies
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Compiling Qunity: From High-Level Quantum Programs to CircuitsPoster
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Mikhail Mints California Institute of Technology, Finn Voichick University of Maryland, Robert Rand University of Chicago
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Expressing and Analyzing Quantum Algorithms with QualtranPoster
PLanQC
Matthew P Harrigan Google Quantum AI
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Fusion and flow: formal protocols to reliably build photonic graph statesPoster
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Giovanni de Felice Quantinuum, Boldizsár Poór Quantinuum, Lia Yeh University of Oxford, William Cashman University of Oxford
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Lightweight functional verification of quantum programsPoster
PLanQC
Kevin Ye Simon Fraser University, Matthew Amy Simon Fraser University
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Qutes: a Pathway to High-Level Quantum ProgrammingPoster
PLanQC
Simone Faro University of Catania, Francesco Pio Marino University of Catania, University of Rouen, Gabriele Messina University of Catania
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Restricted Evolution as a Strategy for Constant Runtime Error MitigationPoster
PLanQC
Gaurav Saxena LG Electronics Toronto AI Lab, Thi Ha Kyaw LG Electronics Toronto AI Lab
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Sdim: A Qudit Stabilizer SimulatorPoster
PLanQC
Adeeb Kabir Rutgers University, Steven Nguyen Rutgers University, Tijil Kiran Rutgers University, Anika Kumar Rutgers University, Yipeng Huang Rutgers University
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Size Analysis of Imperative Quantum Circuit Building Programs Through Floyd-Hoare LogicsPoster
PLanQC
Olga Becci University of Bologna, Andrea Colledan University of Bologna & INRIA Sophia Antipolis, Ugo Dal Lago University of Bologna & INRIA Sophia Antipolis, Leonardo Venturi University of Bologna
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The Focked-up ZX Calculus: Picturing Continuous-Variable Quantum ComputationPoster
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Razin A. Shaikh University of Oxford, Lia Yeh University of Oxford, Stefano Gogioso University of Oxford
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