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.

翻译：尽管量子计算的硬件方面已取得显著进展，但与经典编程语言相比，对高级量子编程抽象的支持仍显不足。本文介绍Qrisp框架，该框架旨在弥合前沿软件工程中的高级编程范式与当前量子硬件物理现实之间的若干差距。该框架致力于为量子算法开发提供系统化方法，使得算法能够被轻松实现、维护和改进。我们提出了一系列受经典范式启发的编程抽象，同时始终聚焦于量子开发者的特定需求。与许多其他高级语言方法不同，Qrisp的突出特性在于其能够将程序编译至电路层级，从而使其可在大多数现有物理后端上执行。所引入的抽象机制使Qrisp编译器能够利用算法结构来提升编译效率。最后，我们展示了一组代码示例，包括Shor因式分解算法的实现。对于后者，生成电路显示出量子资源需求的大幅降低，有力证明了系统化量子算法开发能够带来显著的量化优势。