Integrating Quantum Software Tools with(in) MLIR

Overview

This work addresses the lack of interoperability in quantum compilation tools by proposing the adoption of Multi-Level Intermediate Representation (MLIR) as a unifying infrastructure. Quantum compilation remains underdeveloped compared to classical compilation, with many existing solutions built independently and without standardization. This fragmentation prevents effective integration of quantum software tools into cohesive toolchains, limiting the potential for scalable and reliable quantum computation. MLIR, developed within the LLVM project, has successfully addressed similar challenges in classical computing by enabling modular and interoperable compilation across diverse hardware and software components. However, its complexity presents a substantial barrier to adoption in the quantum computing field, where software development is often conducted by researchers and experimentalists rather than professional software engineers. The paper provides practical guidance for quantum software developers to navigate MLIR's technical challenges and leverage its capabilities for building more integrated quantum software ecosystems.

Methods and approach

The paper employs a case study methodology to demonstrate practical integration strategies for incorporating MLIR into quantum software tools. The case study connects Xanadu's PennyLane, a quantum machine learning framework, with the Munich Quantum Toolkit (MQT), illustrating concrete implementation steps for bridging distinct quantum software components through MLIR infrastructure. The authors present actionable integration procedures, documenting technical decisions and development practices derived from hands-on implementation experience. The approach emphasizes practical applicability by focusing on real-world development challenges rather than theoretical frameworks. The guide is structured to reduce the learning curve associated with MLIR adoption, translating complex technical concepts into accessible implementation patterns for quantum software engineers. This methodology aims to establish reproducible patterns that can be generalized across other quantum software integration efforts.

Key Findings

The case study demonstrates feasible pathways for integrating disparate quantum software tools through MLIR infrastructure. The work documents specific integration steps between PennyLane and MQT, providing a concrete reference implementation that establishes interoperability between previously isolated quantum software components. The authors identify and articulate best practices for MLIR adoption in quantum computing contexts, including design patterns and architectural decisions that emerged from development experience. The documentation of technical challenges and solutions provides a knowledge base for future integration efforts. The results validate MLIR's applicability to quantum software stack development and demonstrate that its complexity can be managed through systematic approaches. The case study serves as proof of concept that MLIR can function as a unifying bridge across quantum software tools, enabling more modular architectures than current ad hoc solutions permit.

Implications

This work contributes to establishing standardized infrastructure for quantum software development by advocating for MLIR adoption as a common intermediate representation layer. The practical guidance provided reduces barriers to entry for quantum software developers seeking to build interoperable tools, potentially accelerating the maturation of the quantum software ecosystem. By enabling seamless integration across quantum software components, MLIR-based approaches support the development of more sophisticated quantum compilation pipelines and facilitate collaboration between independent development efforts. The case study methodology establishes a template for future integration projects, promoting consistency in how quantum tools interface with compilation infrastructure. These developments are particularly relevant as quantum computing transitions from experimental systems to production environments requiring robust, maintainable software stacks. The work also highlights the importance of software engineering expertise in quantum computing infrastructure development, potentially influencing resource allocation and team composition in quantum software projects. Long-term adoption of MLIR standards could reduce redundant development effort and enable quantum software tools to benefit from advances in the broader LLVM ecosystem.