This preprint documents a reproducible failure mode in cross-platform quantum benchmarking: compiler/transpiler optimization can silently invalidate circuit-depth (or “barrier-based”) proxies for decoherence exposure by eliminating the intended experimental variable. We show how barrier or idle-depth manipulation may collapse after compilation, producing misleading null depth-dependence or inflated conclusions. We provide an audit workflow based on compiled-circuit metadata (depth, 1Q/2Q gate counts, and optimization settings) and recommend benchmark designs that encode the experimental variable in gate parameters or analysis steps (e.g., phase-sweep parity witnesses), which are robust to structural circuit simplification. Related dataset: Cross-platform GHZ benchmarking JSON logs and analysis artifacts are available on Zenodo (concept DOI: 10.5281/zenodo.18530246; current version: 10.5281/zenodo.18530247). This methodological note is a companion focused on compiler/transpilation artefacts and reporting standards for compiled-circuit audits.
This preprint documents a reproducible failure mode in cross-platform quantum benchmarking: compiler/transpiler optimization can silently invalidate circuit-depth (or “barrier-based”) proxies for decoherence exposure by eliminating the intended experimental variable. We show how barrier or idle-depth manipulation may collapse after compilation, producing misleading null depth-dependence or inflated conclusions. We provide an audit workflow based on compiled-circuit metadata (depth, 1Q/2Q gate counts, and optimization settings) and recommend benchmark designs that encode the experimental variable in gate parameters or analysis steps (e.g., phase-sweep parity witnesses), which are robust to structural circuit simplification. Related dataset: Cross-platform GHZ benchmarking JSON logs and analysis artifacts are available on Zenodo (concept DOI: 10.5281/zenodo.18530246; current version: 10.5281/zenodo.18530247). This methodological note is a companion focused on compiler/transpilation artefacts and reporting standards for compiled-circuit audits.
Quantum software workflows rely on compiler and provider toolchains that evolve independently of application source code. Consequently, an unchanged quantum circuit may transpile into a different target-specific realization after changes in SDK versions, optimization settings, basis gates, coupling maps, or backend descriptions. Such transpilation drift can affect circuit depth, gate composition, qubit mapping, and execution behavior, yet it is rarely monitored in CI/CD pipelines. This paper proposes a Quantum DevOps workflow for detecting transpilation drift before execution. The workflow transpiles source circuits against configured target profiles, computes structural drift metrics, records provenance and artifacts in MLflow, and raises configurable warnings or failures in GitHub Actions. Using representative circuits and target profiles, we show how drift checks can expose toolchain-induced changes and support reproducibility audits. The contribution is a practical CI/CD guardrail for making quantum compilation behavior observable, testable, and auditable.
This work introduces ΩQ-SILQ, a structure-sensitive quantum compilation framework that extends high-level quantum programming concepts with Hamiltonian-aware stability analysis. Modern quantum compilers and languages such as Silq improve quantum software development through abstraction, resource optimization, and automatic uncomputation. However, traditional optimization primarily focuses on computational metrics such as gate count, circuit depth, and qubit usage. ΩQ-SILQ proposes an additional structure-sensitive layer based on a commutator-norm metric: Omega_Q(U,H) = ||[H,U]|| / ||U|| to evaluate the compatibility between quantum operations and the underlying Hamiltonian dynamics of the target system. The framework introduces: • Hamiltonian-aware structural scoring of quantum circuits • Structure-sensitive compiler decision functions • Integration concept with high-level quantum language pipelines • Fidelity-based validation using logically equivalent circuit decompositions • Extended GHZ benchmark experiments • A proposed Qiskit transpiler comparison protocol Initial simulations demonstrate that lower ΩQ circuit selections can preserve higher fidelity under structurally coupled noise models. A multi-sample GHZ benchmark further evaluates the relationship between structural-score differences and fidelity behavior. This work does not propose replacing existing quantum compilers or quantum error correction methods. Instead, ΩQ-SILQ is presented as a complementary pre-error structural optimization layer designed to explore how future quantum compilers may incorporate physical system dynamics alongside computational efficiency. Version v1.1 includes extended hub-selection benchmarking, and the accompanying v1.2 protocol defines future validation against Qiskit transpiler optimization levels and standard quantum algorithm families.
This whitepaper identifies execution-time phase exposure as a missing diagnostic layer in quantum circuit evaluation. Quantum circuit performance is commonly evaluated through aggregate quantities such as gate count, circuit depth, total idle time, calibration data, error rates, and hardware coherence parameters such as T1 and T2. These quantities are necessary, but they do not identify when a qubit is actually carrying phase-sensitive quantum information whose preservation matters to the intended readout. The central observation is that idle time is not uniformly harmful. Idle time becomes consequential when it overlaps an active phase-bearing execution window: an interval in which phase-sensitive structure exists, persists, and remains relevant to a later readout. The whitepaper frames this distinction from a compact-fiber readout perspective and reports sanitized aggregate validation results from contemporary superconducting quantum hardware. The validation supports the claim that circuits with similar aggregate metrics can differ in observed performance because their idle intervals occur in different execution-time locations relative to phase-bearing structure. This record contains the whitepaper PDF only. It does not include circuit definitions, job identifiers, report schemas, implementation details, raw validation artifacts, or non-public workflow material.
We present an analysis of quantum circuit fidelity across the full compilation stack, from high-level gate optimization through pulse-level control. We connect a C++ circuit optimizer to a per-gate Lindblad master-equation fidelity model whose decoherence channels are cross-validated against qiskit-dynamics and whose absolute predictions are benchmarked against execution on real hardware. Across a campaign of 4,452 experiment runs over 371 benchmark circuits, gate cancellation provides the dominant improvement (d=1.66, 72% of circuits improved), while circuit size and pulse duration are the strongest negative predictors of process fidelity (input gates r=−0.78; pulse duration r=−0.73, R2=0.53). A formal ablation study shows that pass ordering has no significant effect on two-qubit gate reduction (Kruskal--Wallis p=0.302). Comparing against Qiskit transpilation levels, we show that two-qubit gate count, not total gate count, is the hardware-relevant metric: our optimizer attains superior two-qubit reduction on structured circuits (87.8% on QFT, 100% on QAOA) whereas Qiskit's larger total-gate reduction is dominated by single-qubit (u3) consolidation. Finally, executing eight circuits on the IQM Resonance Garnet processor (8/8 jobs completed, job identifiers released) reveals that the model is a consistent upper bound: it preserves the relative difficulty ordering of circuits but overestimates absolute fidelity by a mean of 0.49, quantifying the error budget (crosstalk, leakage, readout) outside a T1/T2/depolarizing model. We release the framework, data, and scripts as open source.
Optimizing quantum circuits by reducing circuit depth is essential for improving the efficiency and scalability of quantum algorithms, particularly as quantum hardware continues to evolve. This can be achieved by restructuring quantum algorithms to allow more parallelism. A compiler is needed to automatically detect and apply these optimizations. In this work, we focus on the optimization of two fundamental quantum subroutines: GHZ state creation and CNOT/CZ chain decomposition. Traditional implementations of these subroutines suffer from linearly increasing circuit depth, which limits scalability. We propose a compiler-driven approach that automatically detects and optimizes these two fundamental quantum subroutines. Our approach reduces circuit depth through constant-depth GHZ state creation, constant depth CZ chain decomposition, and logarithmic depth recursive CNOT chain decomposition, which enhance parallel execution. Performance analysis of benchmarked algorithms shows significant reductions in depth. However, our solution also results in an increased gate count, which makes our optimization a trade-off. The gate count for the CNOT chains is doubled, where logarithmic depth reduction is achieved. The reduced circuit depth results in more efficient algorithms by reducing execution time.
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.