Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2512.13422

QMon: Monitoring the Execution of Quantum Circuits with Mid-Circuit Measurement and Reset

Ning Ma, Jianjun Zhao, Foutse Khomh, Ali, Shaukat, Heng Li

Published Dec 15, 2025• 0 citations
arXivHTMLPDF

Abstract

Unlike classical software, where logging and runtime tracing can effectively reveal internal execution status, quantum circuits possess unique properties, such as the no-cloning theorem and measurement-induced collapse, that prevent direct observation or duplication of their states. These characteristics make it especially challenging to monitor the execution of quantum circuits, complicating essential tasks such as debugging and runtime monitoring. This paper presents QMon, a practical methodology that leverages mid-circuit measurements, reset operations, and causal-cone replay to monitor selected intermediate values of quantum circuits while preserving their original runtime behavior under explicit conditions. QMon enables the instrumentation of monitoring operators at selected locations within the circuit, allowing comparisons between expected and observed one-qubit outcome probabilities at those locations. Under an ideal noise-free model, we prove that QMon preserves the full circuit state when the monitored qubit is separable, replay is exact, and the measurement record does not control later operations. Across 310 benchmark circuits with a 24-qubit limit per run, QMon monitors 44.54% of gate-qubit locations and 89.75% of circuit qubits at least once, on average. On 2,860 simulated buggy circuits (mutated circuits that alter final outputs), it achieves a detection rate of 62.4%, remaining competitive with three assertion baselines while requiring a median of one planned run per circuit, compared with 21 for the assertion baselines. By collecting multiple checkpoint observations within continued executions, QMon combines practical efficiency with an exact preservation guarantee under explicit conditions.

DOI
10.48550/arxiv.2512.13422

Related papers

Toward Circuit-Aware Mutation Testing for Quantum Programs: Exact Visibility and Execution Planning

Andriy Miranskyy, Jose Campos

Mutation testing assesses test suites by introducing program changes and checking whether tests detect them. In quantum programs, a surviving mutant may leave program behavior unchanged, produce a change hidden by the chosen input or measurement, or remain undetected because statistical evidence is insufficient. We develop a circuit-aware framework to distinguish these causes and guide execution planning and test changes. The framework covers ideal, noiseless programs and mutations that replace one gate or subcircuit. The method traces how a mutation can affect measured outputs and combines established mathematical checks with statistical estimates. For supported cases, we establish conditions under which a test cannot reveal a mutation and exact formulas for its effect when the required state information is available. Under stated assumptions, we bound the mutation score while retaining surviving and unresolved mutants, and identify a restricted circuit family whose mutation effects admit efficient classical classification. The deliverables include a decision procedure, mathematical guarantees, worked examples of test changes and their implementation requirements, and a small-circuit reference implementation for differential expectation tests. These results help testers decide what to execute, what to change, and what remains unknown. The evidence is limited to proofs and executable examples under the ideal model.

cs.SECross-listedarXiv:2610.36976•Oct 28, 2026•0 citations

Qubit-Reuse Compilation with Mid-Circuit Measurement and Reset

Matthew P. DeCross, Eli Chertkov, Megan Kohagen +1 more

A number of commercially available quantum computers, such as those based on trapped-ion or superconducting qubits, can now perform mid-circuit measurements and resets.In addition to being crucial for quantum error correction, this capability can help reduce the number of qubits needed to execute many types of quantum algorithms by measuring qubits as early as possible, resetting them, and reusing them elsewhere in the circuit.In this work, we introduce the idea of qubit-reuse compilation, which takes as input a quantum circuit and produces as output a compiled circuit that requires fewer qubits to execute due to qubit reuse.We present two algorithms for performing qubit-reuse compilation: an exact constraint programming optimization model and a greedy heuristic.We introduce the concept of dual circuits, obtained by exchanging state preparations with measurements and vice versa and reversing time, and show that optimal qubit-reuse compilation requires the same number of qubits to execute a circuit as its dual.We illustrate the performance of these algorithms on a variety of relevant near-term quantum circuits, such as one-dimensional and two-dimensional time-evolution circuits, and numerically benchmark their performance on the quantum adiabatic optimization algorithm (QAOA) applied to the MaxCut problem on random three-regular graphs.To demonstrate the practical benefit of these techniques, we experimentally realize an 80-qubit QAOA MaxCut circuit on the 20-qubit Quantinuum H1-1 trapped-ion quantum processor using qubit-reuse compilation algorithms.

arXiv:2210.08039•Physical Review X•Dec 22, 2023•65 citations

Continuous Monitoring for Noisy Intermediate-Scale Quantum Processors

Y. F. Zolotarev, I. A. Luchnikov, Julio A. López-Saldívar +2 more

We present a continuous monitoring system for intermediate-scale quantum processors that allows extracting estimates of noisy native gate and read-out measurements based on the set of executed quantum circuits and resulting measurement outcomes. In contrast to standard approaches for calibration and benchmarking quantum processors, the executed circuits, which are input to the monitoring system, are assumed to be out of any control. We provide the results of applying our system to the synthetically generated data obtained from a quantum emulator, as well as to the experimental data collected from a publicly accessible cloud-based quantum processor. In both cases, we demonstrate that the developed approach provides valuable results about inherent noises of emulators and processors. Considering that our approach uses only already accessible data from implemented circuits without the need to run additional algorithms, the monitoring system can complement existing approaches. We expect that our monitoring system can become a useful tool for various quantum computers in the near-term horizon, including publicly accessible cloud-based platforms, and reduce resources that are required for their benchmarking and calibration.

arXiv:2205.06191•Physical Review Applied•Jan 9, 2023•3 citations

Quantum Circuits for Dynamic Runtime Assertions in Quantum Computation

Huiyang Zhou, Gregory T. Byrd

In this paper, we propose quantum circuits for runtime assertions, which can be used for both software debugging and error detection. Runtime assertion is challenging in quantum computing for two key reasons. First, a quantum bit (qubit) cannot be copied, which is known as the non-cloning theorem. Second, when a qubit is measured, its superposition state collapses into a classical state, losing the inherent parallel information. In this paper, we overcome these challenges with runtime computation through ancilla qubits, which are used to indirectly collect the information of the qubits of interest. We design quantum circuits to assert classical states, entanglement, and superposition states.

arXiv:1905.12068•IEEE Computer Architecture Letters•Jul 1, 2019•23 citations

Advancing hybrid quantum–classical computation with real-time execution

Thomas Lubinski, Cassandra Granade, Amos Anderson +4 more

The use of mid-circuit measurement and qubit reset within quantum programs has been introduced recently and several applications demonstrated that perform conditional branching based on these measurements. In this work, we go a step further and describe a next-generation implementation of classical computation embedded within quantum programs that enables the real-time calculation and adjustment of program variables based on the mid-circuit state of measured qubits. A full-featured Quantum Intermediate Representation (QIR) model is used to describe the quantum circuit including its embedded classical computation. This integrated approach eliminates the need to evaluate and store a potentially prohibitive volume of classical data within the quantum program in order to explore multiple solution paths. It enables a new type of quantum algorithm that requires fewer round-trips between an external classical driver program and the execution of the quantum program, significantly reducing computational latency, as much of the classical computation can be performed during the coherence time of quantum program execution. We review practical challenges to implementing this approach along with developments underway to address these challenges. An implementation of this novel and powerful quantum programming pattern, a random walk phase estimation algorithm, is demonstrated on a physical quantum computer with an analysis of its benefits and feasibility as compared to existing quantum computing methods.

arXiv:2206.12950•Frontiers in Physics•Aug 5, 2022•50 citations

QQLink: A Declarative Framework for Multi-QPU Quantum Workflow Orchestration

Vicente Leyton Ortega, Narasinga Rao Miniskar, Thomas Naughton +1 more

Distributed quantum protocols require measurement outcomes produced at one node to control operations at another. We present QQLink, a programming and orchestration layer that expresses these dependencies in a single program, using workflow nodes, deferred measurement references, and declared entanglement, and derives the cross-node coordination automatically. Its planner constructs a provably acyclic dependency graph in time linear in the total size of the instructions' qubit footprints. The same programs execute through simulator backends or are lowered to dynamic circuits on partitioned quantum hardware. We evaluate seven protocol workflows. Exhaustive feedforward-branch tests on the simulator runtime path, over tomographically complete input sets, yield output-state infidelities of at most $5\times10^{-12}$ and no incorrect classical outputs, and replaying every plan in random topological orders leaves each final state unchanged. Separate executor processes run the plans with delayed messages, with the joint quantum state held by a centralized simulation service. Every run with the full plan is correct, and removing required cross-node dependencies causes protocol failures. The lowered circuits match hand-written implementations of the same construction in two-qubit gate and conditional-block counts. Runs on two IBM Heron processors, each partitioned into virtual QPUs, demonstrate same-chip execution in two sessions a week apart. The runs also show large variation between sessions and losses beyond what calibration-derived noise models predict. Coherence-sensitive checks do not establish coherent Toffoli operation or preservation of the intended repetition-code superposition. These results support QQLink's workflow semantics on the tested execution paths and identify limits of the current hardware realization; execution across physically networked QPUs remains future work.

quant-pharXiv:2610.34486•Oct 27, 2026•0 citations
Unlike classical software, where logging and runtime tracing can effectively reveal internal execution status, quantum circuits possess unique properties, such as the no-cloning theorem and measurement-induced collapse, that prevent direct observation or duplication of their states. These characteristics make it especially challenging to monitor the execution of quantum circuits, complicating essential tasks such as debugging and runtime monitoring. This paper presents QMon, a practical methodology that leverages mid-circuit measurements, reset operations, and causal-cone replay to monitor selected intermediate values of quantum circuits while preserving their original runtime behavior under explicit conditions. QMon enables the instrumentation of monitoring operators at selected locations within the circuit, allowing comparisons between expected and observed one-qubit outcome probabilities at those locations. Under an ideal noise-free model, we prove that QMon preserves the full circuit state when the monitored qubit is separable, replay is exact, and the measurement record does not control later operations. Across 310 benchmark circuits with a 24-qubit limit per run, QMon monitors 44.54% of gate-qubit locations and 89.75% of circuit qubits at least once, on average. On 2,860 simulated buggy circuits (mutated circuits that alter final outputs), it achieves a detection rate of 62.4%, remaining competitive with three assertion baselines while requiring a median of one planned run per circuit, compared with 21 for the assertion baselines. By collecting multiple checkpoint observations within continued executions, QMon combines practical efficiency with an exact preservation guarantee under explicit conditions.
Mutation testing assesses test suites by introducing program changes and checking whether tests detect them. In quantum programs, a surviving mutant may leave program behavior unchanged, produce a change hidden by the chosen input or measurement, or remain undetected because statistical evidence is insufficient. We develop a circuit-aware framework to distinguish these causes and guide execution planning and test changes. The framework covers ideal, noiseless programs and mutations that replace one gate or subcircuit. The method traces how a mutation can affect measured outputs and combines established mathematical checks with statistical estimates. For supported cases, we establish conditions under which a test cannot reveal a mutation and exact formulas for its effect when the required state information is available. Under stated assumptions, we bound the mutation score while retaining surviving and unresolved mutants, and identify a restricted circuit family whose mutation effects admit efficient classical classification. The deliverables include a decision procedure, mathematical guarantees, worked examples of test changes and their implementation requirements, and a small-circuit reference implementation for differential expectation tests. These results help testers decide what to execute, what to change, and what remains unknown. The evidence is limited to proofs and executable examples under the ideal model.
A number of commercially available quantum computers, such as those based on trapped-ion or superconducting qubits, can now perform mid-circuit measurements and resets.In addition to being crucial for quantum error correction, this capability can help reduce the number of qubits needed to execute many types of quantum algorithms by measuring qubits as early as possible, resetting them, and reusing them elsewhere in the circuit.In this work, we introduce the idea of qubit-reuse compilation, which takes as input a quantum circuit and produces as output a compiled circuit that requires fewer qubits to execute due to qubit reuse.We present two algorithms for performing qubit-reuse compilation: an exact constraint programming optimization model and a greedy heuristic.We introduce the concept of dual circuits, obtained by exchanging state preparations with measurements and vice versa and reversing time, and show that optimal qubit-reuse compilation requires the same number of qubits to execute a circuit as its dual.We illustrate the performance of these algorithms on a variety of relevant near-term quantum circuits, such as one-dimensional and two-dimensional time-evolution circuits, and numerically benchmark their performance on the quantum adiabatic optimization algorithm (QAOA) applied to the MaxCut problem on random three-regular graphs.To demonstrate the practical benefit of these techniques, we experimentally realize an 80-qubit QAOA MaxCut circuit on the 20-qubit Quantinuum H1-1 trapped-ion quantum processor using qubit-reuse compilation algorithms.
We present a continuous monitoring system for intermediate-scale quantum processors that allows extracting estimates of noisy native gate and read-out measurements based on the set of executed quantum circuits and resulting measurement outcomes. In contrast to standard approaches for calibration and benchmarking quantum processors, the executed circuits, which are input to the monitoring system, are assumed to be out of any control. We provide the results of applying our system to the synthetically generated data obtained from a quantum emulator, as well as to the experimental data collected from a publicly accessible cloud-based quantum processor. In both cases, we demonstrate that the developed approach provides valuable results about inherent noises of emulators and processors. Considering that our approach uses only already accessible data from implemented circuits without the need to run additional algorithms, the monitoring system can complement existing approaches. We expect that our monitoring system can become a useful tool for various quantum computers in the near-term horizon, including publicly accessible cloud-based platforms, and reduce resources that are required for their benchmarking and calibration.
In this paper, we propose quantum circuits for runtime assertions, which can be used for both software debugging and error detection. Runtime assertion is challenging in quantum computing for two key reasons. First, a quantum bit (qubit) cannot be copied, which is known as the non-cloning theorem. Second, when a qubit is measured, its superposition state collapses into a classical state, losing the inherent parallel information. In this paper, we overcome these challenges with runtime computation through ancilla qubits, which are used to indirectly collect the information of the qubits of interest. We design quantum circuits to assert classical states, entanglement, and superposition states.
The use of mid-circuit measurement and qubit reset within quantum programs has been introduced recently and several applications demonstrated that perform conditional branching based on these measurements. In this work, we go a step further and describe a next-generation implementation of classical computation embedded within quantum programs that enables the real-time calculation and adjustment of program variables based on the mid-circuit state of measured qubits. A full-featured Quantum Intermediate Representation (QIR) model is used to describe the quantum circuit including its embedded classical computation. This integrated approach eliminates the need to evaluate and store a potentially prohibitive volume of classical data within the quantum program in order to explore multiple solution paths. It enables a new type of quantum algorithm that requires fewer round-trips between an external classical driver program and the execution of the quantum program, significantly reducing computational latency, as much of the classical computation can be performed during the coherence time of quantum program execution. We review practical challenges to implementing this approach along with developments underway to address these challenges. An implementation of this novel and powerful quantum programming pattern, a random walk phase estimation algorithm, is demonstrated on a physical quantum computer with an analysis of its benefits and feasibility as compared to existing quantum computing methods.
Distributed quantum protocols require measurement outcomes produced at one node to control operations at another. We present QQLink, a programming and orchestration layer that expresses these dependencies in a single program, using workflow nodes, deferred measurement references, and declared entanglement, and derives the cross-node coordination automatically. Its planner constructs a provably acyclic dependency graph in time linear in the total size of the instructions' qubit footprints. The same programs execute through simulator backends or are lowered to dynamic circuits on partitioned quantum hardware. We evaluate seven protocol workflows. Exhaustive feedforward-branch tests on the simulator runtime path, over tomographically complete input sets, yield output-state infidelities of at most 5×10−125\times10^{-12}5×10−12 and no incorrect classical outputs, and replaying every plan in random topological orders leaves each final state unchanged. Separate executor processes run the plans with delayed messages, with the joint quantum state held by a centralized simulation service. Every run with the full plan is correct, and removing required cross-node dependencies causes protocol failures. The lowered circuits match hand-written implementations of the same construction in two-qubit gate and conditional-block counts. Runs on two IBM Heron processors, each partitioned into virtual QPUs, demonstrate same-chip execution in two sessions a week apart. The runs also show large variation between sessions and losses beyond what calibration-derived noise models predict. Coherence-sensitive checks do not establish coherent Toffoli operation or preservation of the intended repetition-code superposition. These results support QQLink's workflow semantics on the tested execution paths and identify limits of the current hardware realization; execution across physically networked QPUs remains future work.