Problem
Research questions and friction points this paper is trying to address.
fault-tolerant quantum computation
resource estimation
quantum programming languages
error correction
resource overhead
Resource Estimation for Fault-Tolerant Quantum Programs
🤖 AI Summary
Existing quantum programming languages struggle to balance programmability and resource estimation accuracy in fault-tolerant computing: they either expose excessive hardware details or incur resource inefficiencies due to over-abstraction. This work proposes a novel fault-tolerant quantum programming language that introduces programmer-visible error-correction abstractions and integrates a cross-layer hardware-software co-analysis mechanism. This approach enables fine-grained, high-fidelity resource modeling and estimation, significantly reducing the fault-tolerance overhead for large-scale practical quantum algorithms while delivering precise and actionable resource assessments.
📝 Abstract
Fault-tolerant quantum computation enables the deployment of practical quantum algorithms but incurs substantial overhead from error correction, making resource estimation a central concern. Beyond case-by-case analyses, existing quantum programming languages either require programmers to manipulate low-level hardware details, rendering fault-tolerant implementations cumbersome, or abstract away the underlying error-correction schemes, reducing the effectiveness of resource utilization and estimation.
To address these limitations while preserving programmability, we present a quantum programming language that enables efficient resource utilization, together with a resource-estimation framework for comprehensive resource analysis. Our framework features programmer-visible abstractions of error-correction schemes and cross-layer program-hardware analysis, allowing systematic exploration of resource trade-offs. We evaluate our approach on detailed fault-tolerant implementations of practical large-scale quantum algorithms, including components typically treated as black boxes in existing frameworks. The results demonstrate that our framework enables substantial resource savings while delivering detailed, fine-grained, and accurate resource estimates for fault-tolerant quantum programs.
Innovation
Methods, ideas, or system contributions that make the work stand out.
fault-tolerant quantum computation
resource estimation
quantum programming language
error-correction abstraction
cross-layer analysis
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