With the advent of more quantum computing applications, it is imperative to provide developers with a set of metrics to determine how much trust they can place in the execution of their programs. In this study, we propose a novel protocol based on quantum teleportation to systematically evaluate the performance of quantum circuits and quantify their execution reliability. Our protocol consists of three parts: the payload, composed of entangled qubits with random gates applied to each wire; the bridge, which corresponds to the teleportation-inspired protocol; and an inverse payload operation, designed to return the circuit to its initial state. We validated the algorithm by elaborating its mathematical framework, followed by a comparative analysis with simulation results using Qiskit AerSimulator and ultimately through an execution on the IBM quantum and Rigetti services. A key aspect of our methodology was to set the circuit transpilation to its lowest optimization level (level 0). We recognize that even without aggressive optimization, randomly generated gates can form self-canceling sequences. As a result, our analysis correlates the pre-runtime metrics of the final, minimally-transpiled circuit (such as its actual depth and gate count) with post-runtime results (such as success rate). This approach reveals significant correlations and offers developers quantitative metrics to assess both the reliability of quantum circuit execution and scalability limitations in their applications.
With the advent of more quantum computing applications, it is imperative to provide developers with a set of metrics to determine how much trust they can place in the execution of their programs. In this study, we propose a novel protocol based on quantum teleportation to systematically evaluate the performance of quantum circuits and quantify their execution reliability. Our protocol consists of three parts: the payload, composed of entangled qubits with random gates applied to each wire; the bridge, which corresponds to the teleportation-inspired protocol; and an inverse payload operation, designed to return the circuit to its initial state. We validated the algorithm by elaborating its mathematical framework, followed by a comparative analysis with simulation results using Qiskit AerSimulator and ultimately through an execution on the IBM quantum and Rigetti services. A key aspect of our methodology was to set the circuit transpilation to its lowest optimization level (level 0). We recognize that even without aggressive optimization, randomly generated gates can form self-canceling sequences. As a result, our analysis correlates the pre-runtime metrics of the final, minimally-transpiled circuit (such as its actual depth and gate count) with post-runtime results (such as success rate). This approach reveals significant correlations and offers developers quantitative metrics to assess both the reliability of quantum circuit execution and scalability limitations in their applications.
Abstract We present the first experimental demonstration of quantum circuit teleportation between heterogeneous quantum processors using Bell state topology as a hardware-agnostic encoding framework. A complete quantum circuit---comprising 4 gate instructions (H, CNOT, Z measurements)---was teleported from Rigetti Computing's Ankaa-3 superconducting QPU to IQM Quantum Computers' Garnet system, with successful reconstruction and execution. The protocol encodes circuit instructions as Bell state manifolds using a 3-qubit error correction code with majority voting, achieving complete circuit fidelity despite architectural differences in native gate sets and connectivity topologies. By treating quantum gates as equivalence classes under entanglement structure---mapping H→∣Φ+⟩, CNOT→∣Ψ+⟩, Z→∣Φ−⟩, and M→∣Ψ−⟩---we establish a foundational equivalence between gate operations and Bell basis projections. Implementation utilizes the hyperelliptic lattice infrastructure developed previously, enabling topologically-aware routing of quantum programs. This work demonstrates that heterogeneous quantum networks can execute distributed quantum algorithms without dedicated quantum channels or pre-shared high-fidelity entanglement, using only classical database coordination. The 100\% circuit execution success rate combined with error-corrected Bell state decoding provides strong evidence that topology-mediated programming offers a practical pathway toward distributed quantum computing infrastructure. We present comprehensive experimental data, theoretical analysis connecting Bell topology to quantum circuit semantics, and a scalable framework for cross-architecture quantum software distribution.
Quantum computing is progressing beyond experimental prototypes toward cloud-based services and commercially deployed turnkey systems. Evaluating and comparing platform performance requires robust, standardized measures, yet vendors frequently report heterogeneous metrics that are not directly comparable or may not capture whole-system performance. Peaked Random Circuits (PRCs) have recently been proposed as a viable path to demonstrate quantum advantage: a quantum processor can reliably identify a single known high-probability outcome while the circuits' inherent complexity may render classical simulation infeasible. To support robust, system-level evaluation and comparison, we propose a novel benchmarking protocol based on PRCs. By successively running a set of PRCs with varying qubit counts and circuit depths, we quantify a system's ability to identify the deterministic peak despite cumulative noise, gate errors, and connectivity constraints. We demonstrate the benchmark experimentally on IQM's superconducting and AQT's trapped-ion architectures. Our results show that the PRC benchmark provides a holistic yet high-precision view of hardware performance and offers researchers and industry stakeholders a practical and scalable framework for the continuous comparison and evaluation of current and future quantum systems.
This research paper provides an in-depth examination of verification and testing approaches for quantum circuits, focusing on methodologies essential for ensuring the correctness, reliability and operational efficiency of quantum computing systems. Since quantum circuits function on the fundamental principles of superposition and entanglement, they present verification challenges that cannot be effectively addressed using conventional classical testing techniques. As a result, the development of specialized quantum-specific verification strategies has become critically important. The study highlights simulation-based verification as a foundational technique, wherein the outcomes of quantum circuit simulations are systematically compared with results obtained from physical quantum hardware. This process enables the identification of functional inconsistencies and supports iterative refinement of circuit designs. In addition, randomized benchmarking is examined as a key evaluation method for estimating circuit fidelity and quantifying error rates through the application of random gate sequences and performance comparisons against established benchmarks. To further improve system robustness, the research investigates fault-tolerant mechanisms, particularly quantum error correction codes, which play a vital role in minimizing the effects of noise, decoherence and hardware imperfections. The integration of advanced quantum metrology and characterization techniques is also explored, enabling precise measurement and detailed analysis of quantum system behavior. These techniques provide deeper insights into circuit performance and contribute significantly to validation processes. By combining simulation-based verification, randomized benchmarking, fault-tolerant protocols and quantum metrology, this study proposes a comprehensive and reliable framework for quantum circuit verification and testing. The findings contribute to the advancement of dependable quantum technologies and support their growing applications in areas such as cryptography, materials science and other emerging domains.
In this study, we present a comprehensive evaluation of popular SDK-to-SDK quantum transpilers (that is transpilers that takes a quantum circuit from an initial SDK and output a quantum circuit in another SDK), focusing on critical metrics such as correctness, failure rate, and transpilation time. To ensure unbiased evaluation and accommodate diverse quantum computing scenarios, we developed two dedicated tools: RandomQC, for generating random quantum circuits across various types (pure random, VQE-like, and SDK-specific circuits), and Benchmarq, to streamline the benchmarking process. Using these tools, we benchmarked prominent quantum transpilers as of February 2024. Our results highlight the superior performance of the qiskit-braket-provider, a specialized transpiler from Qiskit to Braket, achieving a remarkably low failure rate of 0. 2 %. The qBraid-SDK, offering generalized transpilation across multiple SDKs, demonstrated robust but slower performance. The pytket extensions, while fast, faced limitations with complex circuits due to their one-to-one transpilation approach. In particular, the exceptional performance of the qiskit-bracket-provider stems not only from its specialization but also from its architecture, which combines one-to-one transpilation with gate decomposition for unsupported gates, enhancing both speed and capability. This study aims to provide practical guidelines to users of SDK-to-SDK quantum transpilers and guidance to developers for improving the design and development of future tools.
As quantum computing (QC) matures towards practical applications, effective methods to evaluate quantum algorithms, circuits, and execution quality in quantum software are gaining more relevance. To apply such methods, a set of meaningful metrics must be defined, understood, calculated, and applied. In an effort to solve that problem, this paper categorizes quantum related metrics into pre-runtime (derived from the static analysis of circuits before execution) and post-runtime (derived from the analysis of execution results). It is worthwhile to mention that while popular quantum SDKs such as Qiskit, PennyLane, and Q\# offer some circuit characteristics, there is often a gap between these native capabilities and the broader set of insightful pre- and post-runtime metrics in the literature. This paper introducesqWard, a Python library developed to bridge this gap by offering an initial implementation for the Qiskit SDK. qWard provides a toolkit designed to compute and visualize key pre-runtime and post-runtime metrics, facilitating the analysis of quantum algorithms. To illustrate its application, an experiment using a bell state circuit is conducted, which includes different backend configurations within the simulator as well as its execution on the IBM “torino” quantum processor. It is important to note that the initial version of qWard is limited to the Qiskit SDK and the Qiskit AER simulator.
Quantum teleportation transfers and processes quantum information through quantum entanglement channels. It is one of the most versatile protocols in quantum information science and leads to many remarkable applications, particularly the one-way quantum computing. Here, we show, for the first time, that the concept of teleportation can also be used to facilitate an important classical computing task, sampling random quantum circuits, which is highly relevant to prove the near-term demonstration of quantum computational supremacy. In our method, the classical computation in the physical-qubit state space is converted to simulate teleportation in logical-qubit state space, resulting in a much smaller number of qubits involved in classical computing. We tested this new method on 1D and 2D lattices up to 1000 qubits. This Letter presents a new quantum-inspired classical computing technology and is helpful to design and optimize classically hard quantum sampling experiments.