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Arline Benchmarks: Automated Benchmarking Platform for Quantum Compilers

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arxiv 2202.14025 v1 pith:LD7IHZ5K submitted 2022-02-28 quant-ph cs.SE

classification quant-phcs.SE
keywords quantumcompilationarlinecircuitcompilersalgorithmsbenchmarksautomated
verification ladder T0 review T1 audit T2 compute T3 formal
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Efficient compilation of quantum algorithms is vital in the era of Noisy Intermediate-Scale Quantum (NISQ) devices. While multiple open-source quantum compilation and circuit optimization frameworks are available, e.g. IBM Qiskit, CQC Tket, Google Cirq, Rigetti Quilc, PyZX, their relative performance is not always clear to a quantum programmer. The growth of complexity and diversity of quantum circuit compilation algorithms creates a demand for a dedicated tool for cross-benchmarking and profiling of inner workflow of the quantum compilation stack. We present an open-source software package, Arline Benchmarks, that is designed to perform automated benchmarking of quantum compilers with the focus on NISQ applications. The name "Arline" was given in honour of Arline Greenbaum Feynman, the first wife of Richard Feynman, the pioneer of quantum computing. We compared several quantum compilation frameworks based on a set of important metrics such as post-optimization gate counts, circuit depth, hardware-dependent circuit cost function, compiler run time etc. with a detailed analysis of metrics for each compilation stage. We performed a variety of compiler tests for random circuits and structured quantum algorithms (VQE, Trotter decomposition, Grover search, Option Pricing via Amplitude Estimation) for several popular quantum hardware architectures. Leveraging cross-platform functionality of Arline, we propose a concept of composite compilation pipeline that combines compiler-specific circuit optimization subroutines in a single compilation stack and finds an optimized sequence of compilation passes. By providing detailed insights into the compilation flow of quantum compilers, Arline Benchmarks offers a valuable toolkit for quantum computing researchers and software developers to gain additional insights into compilers' characteristics.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Comparing and learning figures of merit for quantum circuit compilation

    quant-ph 2026-07 conditional novelty 7.0 of 10

    ML models that fuse circuit structure with device coherence data predict weighted PST far more accurately than classical gate-count FoMs, enabling better circuit selection inside compilers.

  2. Quantum Computer Benchmarking: An Explorative Systematic Literature Review

    quant-ph 2025-09 conditional novelty 6.0 of 10

    A systematic review of 329 quantum benchmarking studies yields a stack-aligned taxonomy and definitions for hardware-, software-, and application-focused benchmarks.

  3. Stacking the Odds: Full-Stack Quantum System Design Space Exploration

    quant-ph 2025-06 conditional novelty 4.0 of 10

    A large benchmarking study shows that co-optimized mapping, routing, and connectivity settings improve simulated quantum circuit fidelity more than added optimization passes or larger devices.

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