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Qrisp: A Framework for Compilable High-Level Programming of Gate-Based Quantum Computers
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Qrisp: A Framework for Compilable High-Level Programming of Gate-Based Quantum Computers
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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.
Forward citations
Cited by 12 Pith papers
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A Course on the Introduction to Quantum Software Engineering: Experience Report
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Lagrange: Operating Italy's First Publicly-Accessible Quantum Computer for Research and Education
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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.
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The QuaST Decision Tree: Achieving Automation With Data-Based Recommendations
The QuaST Decision Tree is a configurable modular system that automates recommendations for hybrid quantum algorithms, featuring a module for assessing variational algorithm feasibility through scalability analysis.
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Unitaria: Quantum Linear Algebra via Block Encodings
Unitaria is a new open-source Python library that provides a high-level, composable interface for block encodings in quantum computing, enabling automatic circuit generation and classical simulation-based verification.
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svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm
svPITE is a Python package that provides state-vector and shot-based implementations of probabilistic imaginary-time evolution for quantum ground-state preparation along with parameter tuning and interoperability for ...
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svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm
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