InterQ: Communication-Aware Scheduling Across Modular QPUs with Classical and Quantum Links
Pith reviewed 2026-05-20 11:27 UTC · model grok-4.3
The pith
InterQ scheduler accounts for classical and quantum links to optimize qubit placement and adaptive circuit cutting across modular QPUs.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
InterQ is a communication-aware scheduler that jointly considers qubit capacity, placement, parallel execution, and communication-driven dependencies across distributed subcircuits on modular QPUs. It supports adaptive circuit cutting to shorten the overall runtime while trading off fidelity against communication overhead. By distinguishing classical-link execution with its synchronization needs from quantum-link execution with entanglement costs, and applying a unified simulator to three hardware types, the work demonstrates that neutral-atom systems deliver the highest fidelity, superconducting systems the shortest runtimes, and trapped-ion systems an intermediate balance.
What carries the argument
InterQ, the communication-aware scheduler that models distinct costs for classical and quantum inter-QPU links and incorporates adaptive circuit cutting for distributed subcircuits.
If this is right
- Explicit modeling of link types allows better scheduling decisions for distributed quantum circuits.
- Adaptive cutting decisions can trade some fidelity for reduced overall execution time.
- The choice of hardware platform affects the achievable balance between fidelity and makespan under the same scheduler.
- Simulation frameworks can highlight tradeoffs between different modular quantum architectures.
Where Pith is reading between the lines
- Future quantum cloud providers might use similar schedulers to allocate jobs across heterogeneous modular systems.
- The findings suggest that hardware developers should prioritize either low-latency classical links or high-fidelity quantum links depending on target workloads.
- Testing the scheduler with real inter-QPU entanglement generation could reveal additional overheads not captured in simulation.
Load-bearing premise
The unified simulation framework correctly captures the distinct synchronization and error costs of classical links versus quantum links for each hardware platform.
What would settle it
Executing the scheduled circuits on physical modular quantum hardware and verifying whether the observed fidelity and makespan match the simulation predictions for the three architectures.
Figures
read the original abstract
As quantum computing scales toward practical workloads, future systems are expected to move beyond single monolithic processors toward modular architectures that connect multiple QPUs. Different platforms realize this modularity through different communication models: superconducting systems rely on real-time classical links and dynamic-circuit coordination, trapped-ion systems use photonic interconnects for remote entanglement, and neutral-atom systems provide strong intra-core connectivity with proposed optical links for inter-core communication. This heterogeneity makes communication-aware scheduling essential for shared modular quantum cloud environments. We present InterQ, a communication-aware scheduler for modular QPU architectures with heterogeneous communication models. InterQ jointly considers qubit capacity, placement, parallel execution, and communication-driven dependencies across distributed subcircuits, while enabling adaptive circuit cutting to reduce makespan while balancing fidelity and communication overhead. The framework distinguishes classical-link execution, where measurement and feedforward impose synchronization constraints, from quantum-link execution, where entanglement distribution and state transfer determine coordination cost. Using a unified simulation framework to compare superconducting, trapped-ion, and neutral-atom modular systems, InterQ shows how communication models and scheduler-driven cutting decisions affect throughput, latency, and fidelity. Across evaluated workloads, InterQ exposes an architecture-dependent tradeoff: neutral-atom modular QPUs achieve the highest fidelity, superconducting systems minimize runtime, and trapped-ion systems provide a balanced intermediate profile across fidelity and makespan.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper introduces InterQ, a communication-aware scheduler for modular QPUs supporting heterogeneous links: classical dynamic-circuit coordination for superconducting systems, photonic interconnects for trapped-ion systems, and optical links for neutral-atom systems. It jointly optimizes qubit placement, parallel execution, and communication dependencies while using adaptive circuit cutting to trade off makespan against fidelity and overhead. A unified simulator is used to compare the three platforms across workloads, revealing architecture-dependent tradeoffs (neutral-atom highest fidelity, superconducting lowest runtime, trapped-ion intermediate).
Significance. If the simulation models prove accurate, the work would provide a practical framework for scheduling in future modular quantum clouds and highlight how communication primitives shape performance tradeoffs across hardware platforms.
major comments (2)
- [§5] §5 (Simulation Framework and Evaluation): The platform-specific latency, synchronization, and fidelity parameters for classical versus quantum links are not validated or cross-checked against published experimental data on photonic interconnects, classical feedforward latency, or inter-core optical links. This is load-bearing for the central claim of architecture-dependent tradeoffs, because the reported differences (e.g., neutral-atom fidelity advantage) could arise from the chosen constants rather than inherent platform properties.
- [§6] §6 (Results): Workload definitions, exact makespan and fidelity numbers, error bars, and sensitivity analysis to the assumed error rates and timing parameters are not reported in sufficient detail to allow reproduction or assessment of robustness.
minor comments (2)
- [Abstract] The abstract would benefit from one or two concrete quantitative results (e.g., percentage makespan reduction or fidelity values) to substantiate the tradeoff claims.
- [§3] Notation for classical-link synchronization constraints versus quantum-link entanglement distribution costs should be introduced earlier and used consistently in the scheduler description.
Simulated Author's Rebuttal
We thank the referee for their constructive and detailed feedback. The comments highlight important aspects of parameter sourcing and reproducibility that will improve the manuscript. We address each major comment below and commit to revisions that directly respond to the concerns raised.
read point-by-point responses
-
Referee: [§5] §5 (Simulation Framework and Evaluation): The platform-specific latency, synchronization, and fidelity parameters for classical versus quantum links are not validated or cross-checked against published experimental data on photonic interconnects, classical feedforward latency, or inter-core optical links. This is load-bearing for the central claim of architecture-dependent tradeoffs, because the reported differences (e.g., neutral-atom fidelity advantage) could arise from the chosen constants rather than inherent platform properties.
Authors: We agree that the simulation parameters require clearer grounding in experimental literature to support the architecture-dependent tradeoff claims. While the values were drawn from published works on each platform, the original manuscript did not include explicit citations or cross-checks for each latency, synchronization, and fidelity constant. In the revised version we will add a dedicated table in §5 that lists every parameter together with its source reference (e.g., specific photonic-interconnect experiments for trapped-ion systems and feedforward-latency measurements for superconducting dynamic circuits). We will also include a short robustness discussion showing how the reported fidelity and makespan differences persist when parameters are varied within the ranges given in those experimental papers. revision: yes
-
Referee: [§6] §6 (Results): Workload definitions, exact makespan and fidelity numbers, error bars, and sensitivity analysis to the assumed error rates and timing parameters are not reported in sufficient detail to allow reproduction or assessment of robustness.
Authors: We accept that the current results presentation lacks the granularity needed for independent reproduction and robustness evaluation. The revised manuscript will expand §6 (and add an appendix if space is limited) to provide: (i) precise workload definitions including qubit counts, gate statistics, and inter-subcircuit communication patterns; (ii) tabulated numerical values for makespan and fidelity on each platform; (iii) error bars or standard deviations obtained from repeated simulation runs; and (iv) a sensitivity analysis that sweeps key error rates and timing parameters across literature-reported ranges. These additions will enable readers to verify the findings and assess how sensitive the architecture tradeoffs are to the underlying assumptions. revision: yes
Circularity Check
No circularity: InterQ introduces new scheduler and simulation framework without self-referential derivations
full rationale
The paper presents InterQ as a newly constructed communication-aware scheduler for modular QPUs, jointly considering qubit capacity, placement, parallel execution, and adaptive circuit cutting. It distinguishes classical-link synchronization from quantum-link entanglement costs within a unified simulation framework to compare superconducting, trapped-ion, and neutral-atom architectures. No equations, fitted parameters, or load-bearing self-citations appear in the abstract or description that would reduce any result to its own inputs by construction. The architecture-dependent tradeoffs (neutral-atom highest fidelity, superconducting lowest runtime) are outputs of the simulation rather than mathematical identities or renamed prior fits. This is a standard case of an independent modeling contribution.
Axiom & Free-Parameter Ledger
Reference graph
Works this paper leans on
-
[1]
Quantum computing in the nisq era and beyond,
J. Preskill, “Quantum computing in the nisq era and beyond,”Quantum, vol. 2, p. 79, 2018
work page 2018
-
[2]
Quantum error correction: an introductory guide,
J. Roffe, “Quantum error correction: an introductory guide,”Contempo- rary Physics, vol. 60, no. 3, pp. 226–245, 2019
work page 2019
-
[3]
Review of distributed quantum computing: From single qpu to high performance quantum computing,
D. Barral, F. J. Cardama, G. D ´ıaz-Camacho, D. Fa ´ılde, I. F. Llovo, M. Mussa-Juane, J. V ´azquez-P´erez, J. Villasuso, C. Pi ˜neiro, N. Costas, J. C. Pichel, T. F. Pena, and A. G ´omez, “Review of distributed quantum computing: From single qpu to high performance quantum computing,” Computer Science Review, vol. 57, p. 100747, Aug. 2025. [Online]. Avai...
-
[4]
Distributed quantum computing across an optical network link,
D. Main, P. Drmota, D. P. Nadlinger, E. M. Ainley, A. Agrawal, B. C. Nichol, R. Srinivas, G. Araneda, and D. M. Lucas, “Distributed quantum computing across an optical network link,” Nature, vol. 638, no. 8050, p. 383–388, Feb. 2025. [Online]. Available: http://dx.doi.org/10.1038/s41586-024-08404-x
-
[5]
Combining quantum processors with real-time classical communication,
A. Carrera Vazquez, C. Tornow, D. Rist `e, S. Woerner, M. Takita, and D. J. Egger, “Combining quantum processors with real-time classical communication,”Nature, vol. 636, no. 8041, p. 75–79, Nov. 2024. [Online]. Available: http://dx.doi.org/10.1038/s41586-024-08178-2
-
[6]
Cutqc: using small quantum computers for large quantum circuit evaluations,
W. Tang, T. Tomesh, M. Suchara, J. Larson, and M. Martonosi, “Cutqc: using small quantum computers for large quantum circuit evaluations,” in Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2021, pp. 473–486
work page 2021
-
[7]
Cutting circuits with multiple two-qubit unitaries,
L. Schmitt, C. Piveteau, and D. Sutter, “Cutting circuits with multiple two-qubit unitaries,”Quantum, vol. 9, p. 1634, Feb. 2025. [Online]. Available: https://doi.org/10.22331/q-2025-02-18-1634
-
[8]
Qiskit addon: circuit cutting,
A. M. Bra ´nczyk, A. Carrera Vazquez, D. J. Egger, B. Fuller, J. Gacon, J. R. Garrison, J. R. Glick, C. Johnson, S. Joshi, E. Pednault, C. D. Pemmaraju, P. Rivero, I. Shehzad, and S. Woerner, “Qiskit addon: circuit cutting,” https://github.com/Qiskit/qiskit-addon-cutting, 2024
work page 2024
-
[9]
Circuit knitting with classical communication,
C. Piveteau and D. Sutter, “Circuit knitting with classical communication,”IEEE Transactions on Information Theory, vol. 70, no. 4, p. 2734–2745, Apr. 2024. [Online]. Available: http://dx.doi.org/10.1109/TIT.2023.3310797
-
[10]
Optimal wire cutting with classical communication,
L. Brenner, C. Piveteau, and D. Sutter, “Optimal wire cutting with classical communication,” 2023. [Online]. Available: https: //arxiv.org/abs/2302.03366
-
[11]
Experimental demonstration of a high-fidelity virtual two-qubit gate,
A. P. Singh, K. Mitarai, Y . Suzuki, K. Heya, Y . Tabuchi, K. Fujii, and Y . Nakamura, “Experimental demonstration of a high-fidelity virtual two-qubit gate,”Phys. Rev. Res., vol. 6, p. 013235, Mar 2024. [Online]. Available: https://link.aps.org/doi/10.1103/PhysRevResearch.6.013235
-
[12]
Entanglement of trapped-ion qubits separated by 230 meters,
V . Krutyanskiy, M. Galli, V . Krcmarsky, S. Baier, D. A. Fioretto, Y . Pu, A. Mazloom, P. Sekatski, M. Canteri, M. Teller, J. Schupp, J. Bate, M. Meraner, N. Sangouard, B. P. Lanyon, and T. E. Northup, “Entanglement of trapped-ion qubits separated by 230 meters,”Phys. Rev. Lett., vol. 130, p. 050803, Feb 2023. [Online]. Available: https://link.aps.org/do...
-
[13]
High-rate and high-fidelity modular interconnects between neutral atom quantum processors,
Y . Li and J. D. Thompson, “High-rate and high-fidelity modular interconnects between neutral atom quantum processors,” 2024. [Online]. Available: https://arxiv.org/abs/2401.04075
-
[14]
Quflex: Parallel quantum job scheduling using adaptive circuit cutting,
V . Kulkarni, A. Orenstein, X. Li, S. Xu, D. Blankenberg, and V . Chaud- hary, “Quflex: Parallel quantum job scheduling using adaptive circuit cutting,” inProceedings of Supercomputing India (SCI), 2025, to appear
work page 2025
-
[15]
Scalable circuit cutting and scheduling in a resource- constrained and distributed quantum system,
S. Kan, Z. Du, M. Palma, S. A. Stein, C. Liu, W. Wei, J. Chen, A. Li, and Y . Mao, “Scalable circuit cutting and scheduling in a resource- constrained and distributed quantum system,” in2024 IEEE Interna- tional Conference on Quantum Computing and Engineering (QCE), vol. 01, 2024, pp. 1077–1088
work page 2024
-
[16]
Qiskit: An open-source framework for quantum computing,
H. Abraham, I. AduOffei, I. Y . Akhalwaya, G. Aleksandrowicz, T. Alexanderet al., “Qiskit: An open-source framework for quantum computing,” Zenodo, 2019. [Online]. Available: https: //doi.org/10.5281/zenodo.2562111
-
[17]
L. Liu and X. Dou, “Qucloud+: A holistic qubit mapping scheme for single/multi-programming on 2d/3d nisq quantum computers,”ACM Trans. Archit. Code Optim., vol. 21, no. 1, Jan. 2024. [Online]. Available: https://doi.org/10.1145/3631525
-
[18]
Enabling multi-programming mechanism for quantum computing in the nisq era,
S. Niu and A. Todri-Sanial, “Enabling multi-programming mechanism for quantum computing in the nisq era,”Quantum, vol. 7, p. 925, 2023
work page 2023
-
[19]
Qgroup: Parallel quantum job schedul- ing using dynamic programming,
A. Orenstein and V . Chaudhary, “Qgroup: Parallel quantum job schedul- ing using dynamic programming,” in2024 IEEE International Confer- ence on Quantum Computing and Engineering (QCE), vol. 01, 2024, pp. 990–999
work page 2024
-
[20]
Two-step approach to scheduling quantum circuits,
G. G. Guerreschi and J. Park, “Two-step approach to scheduling quantum circuits,”Quantum Science and Technology, vol. 3, no. 4, p. 045003, 2018
work page 2018
-
[21]
Adaptive job schedul- ing in quantum clouds using reinforcement learning,
W. Luo, J. Zhao, T. Zhan, and Q. Guan, “Adaptive job schedul- ing in quantum clouds using reinforcement learning,”arXiv preprint arXiv:2506.10889, 2025
-
[22]
Quantum circuit cutting with maximum-likelihood tomography,
M. A. Perlin, Z. H. Saleem, M. Suchara, and J. C. Osborn, “Quantum circuit cutting with maximum-likelihood tomography,”npj Quantum Information, vol. 7, no. 1, p. 64, 2021. [Online]. Available: https://doi.org/10.1038/s41534-021-00390-6
-
[23]
Simulating large quantum circuits on a small quantum computer,
T. Peng, A. W. Harrow, M. Ozols, and X. Wu, “Simulating large quantum circuits on a small quantum computer,”Physical review letters, vol. 125, no. 15, p. 150504, 2020
work page 2020
-
[24]
Fast quantum circuit cutting with randomized measurements,
A. Lowe, M. Medvidovi ´c, A. Hayes, L. J. O’Riordan, T. R. Bromley, J. M. Arrazola, and N. Killoran, “Fast quantum circuit cutting with randomized measurements,”Quantum, vol. 7, p. 934, 2023
work page 2023
-
[25]
Cutting multi-control quantum gates with zx calculus,
C. Ufrecht, M. Periyasamy, S. Rietsch, D. D. Scherer, A. Plinge, and C. Mutschler, “Cutting multi-control quantum gates with zx calculus,” Quantum, vol. 7, p. 1147, 2023
work page 2023
-
[26]
Ap- proximate quantum circuit reconstruction,
D. Chen, B. Baheri, V . Chaudhary, Q. Guan, N. Xie, and S. Xu, “Ap- proximate quantum circuit reconstruction,” in2022 IEEE International Conference on Quantum Computing and Engineering (QCE). IEEE, 2022, pp. 509–515
work page 2022
-
[27]
Efficient quantum circuit cutting by neglecting basis elements,
D. T. Chen, E. H. Hansen, X. Li, V . Kulkarni, V . Chaudhary, B. Ren, Q. Guan, S. Kuppannagari, J. Liu, and S. Xu, “Efficient quantum circuit cutting by neglecting basis elements,”arXiv preprint arXiv:2304.04093, 2023
-
[28]
Efficient circuit wire cutting based on commuting groups,
X. Li, V . Kulkarni, D. T. Chen, Q. Guan, W. Jiang, N. Xie, S. Xu, and V . Chaudhary, “Efficient circuit wire cutting based on commuting groups,”arXiv preprint arXiv:2410.20313, 2024
-
[29]
QuMod: Parallel Quantum Job Scheduling on Modular QPUs using Circuit Cutting
V . Kulkarni, A. Orenstein, X. Li, S. Xu, D. Blankenberg, and V . Chaudhary, “Qumod: Parallel quantum job scheduling on modular qpus using circuit cutting,” 2026, published in QCNC 2026. [Online]. Available: https://arxiv.org/abs/2604.11013
work page internal anchor Pith review Pith/arXiv arXiv 2026
-
[30]
MQT Bench: Benchmarking software and design automation tools for quantum computing,
N. Quetschlich, L. Burgholzer, and R. Wille, “MQT Bench: Benchmarking software and design automation tools for quantum computing,”Quantum, vol. 7, p. 1067, 2023. [Online]. Available: https://doi.org/10.22331/q-2023-09-28-1067
-
[31]
Optimality study of existing quantum computing layout synthesis tools,
B. Tan and J. Cong, “Optimality study of existing quantum computing layout synthesis tools,”IEEE Transactions on Computers, vol. 70, no. 9, pp. 1363–1373, 2021, introduces QUEKO benchmarks with known optimal depths and gate counts. [Online]. Available: https://doi.org/10.1109/TC.2020.3009140
-
[32]
Revlib: An online resource for reversible functions and reversible circuits,
R. Wille, S. Offermann, and R. Drechsler, “Revlib: An online resource for reversible functions and reversible circuits,” in2008 38th International Symposium on Multiple Valued Logic. IEEE, 2008, pp. 220–225. [Online]. Available: https://doi.org/10.1109/ISMVL.2008.13
-
[33]
Constructing a virtual two-qubit gate by sampling single-qubit operations,
K. Mitarai and K. Fujii, “Constructing a virtual two-qubit gate by sampling single-qubit operations,”New J. Phys., vol. 23, p. 023021, 2021
work page 2021
-
[34]
Experimental simulation of larger quantum circuits with fewer superconducting qubits,
C. Ying, B. Cheng, Y . Zhao, H.-L. Huang, Y .-N. Zhang, M. Gong, Y . Wu, S. Wang, F. Liang, J. Lin, Y . Xu, H. Deng, H. Rong, C.-Z. Peng, M.-H. Yung, X. Zhu, and J.-W. Pan, “Experimental simulation of larger quantum circuits with fewer superconducting qubits,”Phys. Rev. Lett., vol. 130, p. 110601, Mar 2023. [Online]. Available: https://link.aps.org/doi/10...
-
[35]
Qoncord: A multi-device job scheduling framework for variational quantum algorithms,
M. Wang, P. Das, and P. J. Nair, “Qoncord: A multi-device job scheduling framework for variational quantum algorithms,” in2024 57th IEEE/ACM International Symposium on Microarchitecture (MICRO), 2024, pp. 735–749
work page 2024
-
[36]
Qusplit: Achieving both high fidelity and throughput via job splitting on noisy quantum computers,
J. Li, Y . Song, Y . Liu, J. Pan, L. Yang, T. Humble, and W. Jiang, “Qusplit: Achieving both high fidelity and throughput via job splitting on noisy quantum computers,”arXiv preprint arXiv:2501.12492, 2025
-
[37]
PeerJ Computer Science 3, e103 (Jan 2017).https://doi.org/10.7717/peerj-cs.103
T. SimPy, “Simpy: A discrete-event simulation library,”PeerJ Computer Science, vol. 2, p. e103, 2016. [Online]. Available: https://doi.org/10.7717/peerj-cs.103
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.