AutoQuREO: Automated Full-Stack Quantum Resource Estimation Framework
A novel framework called AutoQuREO has been launched to facilitate automated estimation and optimization of quantum resources. This framework tackles the complex issue of system-level optimization in diverse quantum hardware and software environments, a major barrier as quantum computing evolves from theoretical models to real-world applications. Traditional quantum resource estimation (QRE) methods tend to be compilation-intensive, depend on expert-driven symbolic annotations, and are closely linked to long-term fault-tolerant assumptions, which restricts their use. AutoQuREO introduces four key innovations: a user-defined abstraction of the quantum stack, a modular library for quick prototyping, surrogate modeling through algorithmic profiling and neuro-symbolic methods, and an optimization engine to navigate the design space. Detailed in a paper on arXiv (arXiv:2608.12936), this work aims to enhance the flexibility and practicality of quantum resource estimation, potentially speeding up quantum computing advancements.
Key facts
- AutoQuREO is an automated framework for quantum resource estimation and optimization.
- It addresses system-level optimization across heterogeneous quantum hardware and software stacks.
- Existing QRE approaches are compilation-heavy or domain-knowledge-guided, limiting applicability.
- The framework includes four core novelties: flexible stack abstraction, modular library, surrogate modeling, and optimization engine.
- The paper is available on arXiv with identifier 2608.12936.
- The announcement type is cross.
- The work aims to support the transition of quantum computing from proof-of-principle to practical utility.
Entities
Institutions
- arXiv