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Qrisp: A Framework for Compilable High-Level Programming of Gate-Based Quantum Computers

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arxiv 2406.14792 v1 pith:SCG6YVIQ submitted 2024-06-20 quant-ph cs.PL

classification quant-phcs.PL
keywords quantumprogrammingalgorithmhigh-levelqrispabstractionsframeworkcircuit
verification ladder T0 review T1 audit T2 compute T3 formal
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While significant progress has been made on the hardware side of quantum computing, support for high-level quantum programming abstractions remains underdeveloped compared to classical programming languages. In this article, we introduce Qrisp, a framework designed to bridge several gaps between high-level programming paradigms in state-of-the-art software engineering and the physical reality of today's quantum hardware. The framework aims to provide a systematic approach to quantum algorithm development such that they can be effortlessly implemented, maintained and improved. We propose a number of programming abstractions that are inspired by classical paradigms, yet consistently focus on the particular needs of a quantum developer. Unlike many other high-level language approaches, Qrisp's standout feature is its ability to compile programs to the circuit level, making them executable on most existing physical backends. The introduced abstractions enable the Qrisp compiler to leverage algorithm structure for increased compilation efficiency. Finally, we present a set of code examples, including an implementation of Shor's factoring algorithm. For the latter, the resulting circuit shows significantly reduced quantum resource requirements, strongly supporting the claim that systematic quantum algorithm development can give quantitative benefits.

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Forward citations

Cited by 7 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 12 citations worldwide. Full citation record

  1. High-level quantum structured programs as quantum registers compositions

    quant-ph 2026-08 conditional novelty 6.0 of 10

    A formal framework for structured quantum programming where operations act on entire quantum registers, demonstrated by a quantum SMT solver prototype.

  2. Transpiler Autotuning with Predictive Models for Quantum Circuit Optimization

    quant-ph 2026-07 conditional novelty 6.0 of 10

    A learning-to-rank model over feature-model-sampled Qiskit transpiler pass configurations reliably outperforms Qiskit's fixed optimization levels on two-qubit gate reduction.

  3. A Course on the Introduction to Quantum Software Engineering: Experience Report

    cs.SE 2026-02 conditional novelty 6.0 of 10

    An experience report describes a modular course that enables students with minimal quantum exposure to work productively on quantum software engineering topics using executable artifacts and empirical reasoning.

  4. ProvideQ: A Quantum Optimization Toolbox

    quant-ph 2025-07 conditional novelty 4.0 of 10

    ProvideQ is a configurable toolbox for composing classical and quantum optimization subroutines, demonstrated on small VRP instances where the classical solver outperforms the hybrid quantum approach.

  5. SLURM Heterogeneous Jobs for Hybrid Classical-Quantum Workflows

    cs.DC 2025-06 conditional novelty 4.0 of 10

    Splitting hybrid classical-quantum workflows into sub-jobs and using MPI dynamic process management lets SLURM release the quantum device earlier, potentially reducing quantum idle time and total wall time.

  6. A parameter study for LLL and BKZ with application to shortest vector problems

    cs.CR 2025-02 conditional novelty 4.0 of 10

    An empirical sweep shows LLL and BKZ solve small LWE-derived shortest vector problems with probability that falls with key length and rises with modulus, and the feasible key length grows logarithmically with the modulus.

  7. Qrisp Implementation and Resource Analysis of a T-Count-Optimised Non-Restoring Quantum Square-Root Circuit

    quant-ph 2025-07 reject novelty 3.0 of 10

    A Qrisp implementation of the non-restoring square root circuit is demonstrated, but its headline resource claim (T-count 14n-14) is contradicted by the paper's own table, which matches the quadratic 7/2 n^2 + 21n - 28.

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