Matic Petrič: Qrisp – A High-Level Framework for Scalable and Maintainable Quantum Code

Abstract: Qrisp is a high-level, Python-based quantum programming framework that bridges the gap between classical software engineering and today’s quantum hardware by automating low-level tasks such as qubit management, circuit construction, and uncomputation. Moving beyond assembler-like manual circuit design, Qrisp introduces abstractions like QuantumVariables (and other QuantumTypes) and modular algorithmic primitives as functions, enabling scalable, maintainable quantum code. Recent updates include the Operators module, which provides a unified framework for describing, optimizing, and simulating both qubit and fermionic Hamiltonians-critical for applications in physics, chemistry, and optimization. The Jasp module integrates JAX primitives, supporting real-time computations, repeat-until-success protocols, and scalable hybrid workflows through Catalyst’s compilation pipeline. These advances have enabled efficient implementations of advanced algorithms, including HHL for solving linear systems and forthcoming support for LCU, with benchmarks against OpenFermion demonstrating high fidelity and resource efficiency. Qrisp compiles high-level code to circuit-level representations compatible with major hardware providers, features a high-performance simulator for large-scale experiments, and offers seamless integration with Python libraries such as NumPy and TensorFlow. Comprehensive documentation and user-friendly syntax make quantum algorithm development accessible and reproducible, positioning Qrisp as a robust platform for both research and practical quantum computing applications.