Architecting Hybrid Quantum-Classical Software Systems: Exploration of the Design Trade-off Space with Quantitative Guarantees
Pith reviewed 2026-06-25 23:13 UTC · model grok-4.3
The pith
A formalization of hybrid quantum-classical architectural styles enables trade-off analysis that identifies decision boundaries for QoS-based configuration selection.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The paper claims that a formalization of an architectural style for hybrid applications allows the exploration of the design trade-off space, successfully identifying decision boundaries that enable the dynamic selection of the most suitable hybrid or classical configuration based on the user's QoS criteria, while providing quantitative guarantees.
What carries the argument
Formalization of an architectural style for hybrid quantum-classical applications that incorporates NISQ constraints and SOA structural/behavioral properties to support trade-off analysis with quantitative guarantees.
If this is right
- The method identifies decision boundaries in the design space of hybrid systems.
- It enables dynamic selection of hybrid or classical configurations based on QoS criteria.
- It delivers quantitative guarantees for system configurations under prescribed levels of uncertainty.
- It addresses challenges arising from NISQ idiosyncrasies such as algorithm-machine specificity and disparate quality metrics.
Where Pith is reading between the lines
- The decision boundaries could be embedded in runtime adaptation mechanisms for deployed hybrid services.
- Analogous formal styles might be developed for other mixed-paradigm systems, such as classical-edge-quantum combinations.
- Empirical calibration against real device noise models would test whether the modeled constraints suffice for production use.
Load-bearing premise
The formalization of the architectural style for hybrid applications adequately captures the constraints of NISQ hardware and the structural and behavioral properties of SOA systems so that the resulting trade-off analysis yields reliable quantitative guarantees.
What would settle it
Running the selected hybrid or classical configurations on actual NISQ hardware and observing that measured QoS metrics fall outside the predicted quantitative bounds would falsify the reliability of the guarantees.
Figures
read the original abstract
Addressing problems beyond classical computing limits is sparking an increasing interest in Quantum Computing. However, despite their adequacy to address specific problems, quantum algorithms cover a limited subset of the functionality required in real-world computing systems. Additionally, they require expensive specialized hardware. To overcome this issue, hybrid (quantum-classical) software systems are emerging as a promising way to integrate both computing paradigms by applying the principles of Service-Oriented Architectures (SOA). Still, the design and deployment of hybrid service-based systems faces unique challenges like the idiosyncrasies and constraints of NISQ computers (e.g., algorithms that can only run in specific machines, disparate quality attribute metrics), and the management of structural and behavioural properties of service-based applications. From the SOA perspective, architectural decisions need to be made by performing a trade-off analysis and providing quantitative guarantees of system configurations under prescribed levels of uncertainty. In this paper, a method to explore the design space of quantum-classical applications is provided by a formalization of an architectural style of hybrid applications. The obtained results demonstrate that the proposed method successfully identifies decision boundaries. It enables the dynamic selection of the most suitable hybrid or classical configuration based on the user's QoS criteria.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper proposes a formalization of an architectural style for hybrid quantum-classical applications grounded in SOA principles. This formalization is used to explore the design trade-off space and identify decision boundaries that support dynamic selection between hybrid and classical configurations according to user-specified QoS criteria, while addressing NISQ hardware constraints and structural/behavioral properties of service-based systems.
Significance. If the formalization produces decision boundaries whose quantitative guarantees remain valid when mapped to actual NISQ constraints (algorithm-machine specificity and heterogeneous metrics), the work could provide a useful framework for architectural decision-making in an emerging area of quantum software engineering. The abstract, however, supplies no evidence of such validation or external benchmarks.
major comments (1)
- [Abstract] Abstract: The central claim that the method 'successfully identifies decision boundaries' with quantitative guarantees for QoS selection rests on the assumption that the architectural-style formalization encodes NISQ idiosyncrasies (algorithm-machine binding, disparate quality metrics) and SOA properties as endogenous elements. No description is given of how these constraints are incorporated rather than treated as exogenous parameters; if they are exogenous, the resulting trade-off surfaces are artifacts of the abstraction and do not constitute the claimed guarantees.
minor comments (1)
- [Abstract] The abstract would benefit from a concise statement of the formal method employed (e.g., the modeling formalism or analysis technique) and the nature of the 'obtained results' (e.g., specific metrics or case studies).
Simulated Author's Rebuttal
We thank the referee for the constructive feedback on our manuscript. We address the major comment below and agree that the abstract requires clarification to better convey the formalization approach.
read point-by-point responses
-
Referee: [Abstract] Abstract: The central claim that the method 'successfully identifies decision boundaries' with quantitative guarantees for QoS selection rests on the assumption that the architectural-style formalization encodes NISQ idiosyncrasies (algorithm-machine binding, disparate quality metrics) and SOA properties as endogenous elements. No description is given of how these constraints are incorporated rather than treated as exogenous parameters; if they are exogenous, the resulting trade-off surfaces are artifacts of the abstraction and do not constitute the claimed guarantees.
Authors: The manuscript's formalization of the hybrid architectural style incorporates NISQ idiosyncrasies (algorithm-machine binding, disparate metrics) and SOA structural/behavioral properties directly into the style definition and its primitives, rendering them endogenous rather than exogenous parameters. The trade-off surfaces and decision boundaries are generated from this integrated model, yielding quantitative guarantees relative to the formalized constraints. We agree, however, that the abstract is overly concise and provides no description of this incorporation. We will revise the abstract to explicitly note that the style formalization encodes these elements endogenously. We will also add a brief clarification in the introduction or discussion section on the model's assumptions when mapping to real NISQ hardware. revision: yes
Circularity Check
No circularity in derivation chain
full rationale
The provided abstract and description outline a formalization of an architectural style for hybrid quantum-classical SOA systems to explore design trade-offs and identify decision boundaries for QoS-based selection. No equations, parameters, or derivations are shown. No self-citations, fitted inputs, ansatzes, or uniqueness theorems are referenced that would reduce any claim to its own inputs by construction. The approach is presented as a modeling method whose outputs (decision boundaries) are not shown to be equivalent to inputs via any of the enumerated circular patterns; the central claim remains independent of the listed circularity mechanisms.
Axiom & Free-Parameter Ledger
Reference graph
Works this paper leans on
-
[1]
A. Aleti, S. Bjornander, L. Grunske, and I. Meedeniya. 2009. ArcheOpterix: An extendable tool for architecture optimization of AADL models. InModel-Based Methodologies for Pervasive and Embedded Software, 2009. MOMPES ’09. ICSE Workshop on. IEEE, Vancouver, Canada, 61–71. doi:10.1109/MOMPES.2009.5069138
-
[2]
Jaime Alvarado-Valiente, Javier Romero-Álvarez, Jose Garcia-Alonso, and Juan M Murillo. 2022. A guide for quantum web services deployment. InInternational Conference on Web Engineering. Springer, Bari, Italy, 493–496. doi:10.1007/978- 3-031-09917-5_42
-
[3]
Álvaro M. Aparicio-Morales, Majid Haghparast, Niko Mäkitalo, José García-Alonso, Javier Berrocal, Vlad Stirbu, Tommi Mikkonen, and Juan Manuel Murillo. 2024. Liquifying Quantum-Classical Software-Intensive System of Systems. In IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2024 - March 12, 2024. IEEE, Rovaniemi, Fi...
-
[4]
Applying qnlp to sentiment analysis in finance,
Álvaro M. Aparicio-Morales, Juan Luis Herrera, Enrique Moguel, Javier Berrocal, Jose Garcia-Alonso, and Juan M. Murillo. 2023. Minimizing Deployment Cost of Hybrid Applications. In2023 IEEE International Conference on Quantum Computing and Engineering (QCE), Vol. 02. IEEE, Bellevue, WA, USA, 191–194. doi:10.1109/QCE57702.2023.10209
-
[5]
Hemant Kumar Apat, Bibhudutta Sahoo, Veena Goswami, and Rabindra K. Barik. 2024. A hybrid meta-heuristic algorithm for multi-objective IoT service placement in fog computing environments.Decision Analytics Journal10 (2024), 100379. doi:10.1016/j.dajour.2023.100379
-
[6]
Hamid Bagheri, Chong Tang, and Kevin J. Sullivan. 2014. TradeMaker: automated dynamic analysis of synthesized tradespaces. In36th Int. Conf. on Software Engineering. ACM, Hyderabad, India, 106–116. doi:10.1145/2568225.2568291
-
[7]
Simonetta Balsamo, Antinisca Di Marco, Paola Inverardi, and Marta Simeoni. 2004. Model-Based Performance Prediction in Software Development: A Survey.IEEE Trans. Software Eng.30, 5 (2004), 295–310. doi:10.1109/TSE.2004.9
-
[8]
Steffen Becker, Heiko Koziolek, and Ralf H. Reussner. 2009. The Palladio component model for model-driven perfor- mance prediction.Journal of Systems and Software82, 1 (2009), 3–22. doi:10.1016/j.jss.2008.03.066
-
[9]
Olivier Belli, Charles Loomis, and Nabil Abdennadher. 2016. Towards a Cost-Optimized Cloud Application Placement Tool. In2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, Luxembourg, Luxembourg, 43–50. doi:10.1109/CloudCom.2016.0022
-
[10]
Egor Bondarev, Michel R. V. Chaudron, and Erwin A. de Kock. 2007. Exploring Performance Trade-offs of a JPEG Decoder Using the Deepcompass Framework. In6th WS on Software and Performance (WOSP). ACM, New York, NY, J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2026. Architecting Hybrid Quantum-Classical Software Systems 111:29 USA, 153–163....
-
[11]
Franz Brosch, Heiko Koziolek, Barbora Buhnova, and Ralf H. Reussner. 2012. Architecture-Based Reliability Prediction with the Palladio Component Model.IEEE Trans. Software Eng.38, 6 (2012), 1319–1339. doi:10.1109/TSE.2011.94
-
[12]
Javier Cámara. 2020. HaiQ: Synthesis of Software Design Spaces with Structural and Probabilistic Guarantees. InFormaliSE@ICSE 2020: 8th International Conference on Formal Methods in Software Engineering, July 13, 2020, Kyungmin Bae, Domenico Bianculli, Stefania Gnesi, and Nico Plat (Eds.). ACM, Seoul, Republic of Korea, 22–33. doi:10.1145/3372020.3391562
-
[13]
Javier Cámara, David Garlan, and Bradley R. Schmerl. 2019. Synthesizing tradeoff spaces with quantitative guarantees for families of software systems.J. Syst. Softw.152 (2019), 33–49. doi:10.1016/j.jss.2019.02.055
-
[14]
Yongcheng Ding, Xi Chen, Lucas Lamata, Enrique Solano, and Mikel Sanz. 2021. Implementation of a Hybrid Classical- Quantum Annealing Algorithm for Logistic Network Design.SN Comput. Sci.2, 1 (2021), 68. doi:10.1007/S42979-021- 00466-2
-
[15]
Vishal Dwivedi, David Garlan, Jürgen Pfeffer, and Bradley Schmerl. 2014. Model-Based Assistance for Making Time/Fidelity Trade-Offs in Component Compositions. In11th International Conference on Information Technology: New Generations, ITNG 2014. IEEE CS, Las Vegas, NV, USA, 235–240. doi:10.13140/2.1.2495.6164
-
[16]
Naeem Esfahani, Sam Malek, and Kaveh Razavi. 2013. GuideArch: guiding the exploration of architectural solution space under uncertainty. In35th International Conference on Software Engineering, ICSE. IEEE CS, San Francisco, CA, USA, 43–52. doi:10.1109/ICSE.2013.6606550
-
[17]
Peter H Feiler, Bruce Lewis, Steve Vestal, and Ed Colbert. 2004. An overview of the SAE architecture analysis & design language (AADL) standard: A basis for model-based architecture-driven embedded systems engineering. InIFIP World Computer Congress, TC 2. Springer, Springer, Toulouse, France, 3–15. doi:10.1007/0-387-24590-1_1
-
[18]
Frank Gaitan. 2020. Finding flows of a Navier–Stokes fluid through quantum computing.npj Quantum Information 2020 6:16 (7 2020), 1–6. Issue 1. doi:10.1038/s41534-020-00291-0
-
[19]
José García-Alonso, Javier Rojo, David Valencia, Enrique Moguel, Javier Berrocal, and Juan Manuel Murillo. 2022. Quantum Software as a Service Through a Quantum API Gateway.IEEE Internet Comput.26, 1 (2022), 34–41. doi:10. 1109/MIC.2021.3132688
arXiv 2022
-
[20]
David Garlan, Robert T. Monroe, and David Wile. 1997. Acme: an architecture description interchange language. In Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative Research, November 10-13, 1997. IBM Press, Toronto, Ontario, Canada, 7. doi:10.1145/782010.782017
-
[21]
Peter Garraghan, Paul Townend, and Jie Xu. 2014. An Empirical Failure-Analysis of a Large-Scale Cloud Computing Environment. In2014 IEEE 15th International Symposium on High-Assurance Systems Engineering. IEEE, Miami Beach, FL, USA, 113–120. doi:10.1109/HASE.2014.24
-
[22]
Lov K Grover. 1996. A fast quantum mechanical algorithm for database search. InProceedings of the twenty-eighth annual ACM symposium on Theory of computing. Association for Computing Machinery, Philadelphia, Pennsylvania, USA, 212–219. doi:10.1145/237814.237866
-
[23]
Lars Grunske and Aldeida Aleti. 2013. Quality optimisation of software architectures and design specifications.Journal of Systems and Software86, 10 (2013), 2465–2466. doi:10.1016/j.jss.2013.06.001
-
[24]
Hans Hansson and Bengt Jonsson. 1994. A logic for reasoning about time and reliability.Formal Aspects of Computing 6, 5 (1994), 512–535. doi:10.1007/BF01211866
-
[25]
Juan Luis Herrera, Jaime Galan-Jimenez, Jose Garcia-Alonso, Javier Berrocal, and Juan Manuel Murillo. 2023. Joint Optimization of Response Time and Deployment Cost in Next-Gen IoT Applications.IEEE Internet of Things Journal 10 (3 2023), 3968–3981. Issue 5. doi:10.1109/JIOT.2022.3165646
-
[26]
Jack D. Hidary. 2021.Quantum Computing: An Applied Approach, Second Edition. Springer, Cham, Switzerland. doi:10.1007/978-3-030-83274-2
-
[27]
Yang Hu, Cees de Laat, and Zhiming Zhao. 2019. Optimizing Service Placement for Microservice Architecture in Clouds.Applied Sciences 2019, Vol. 9, Page 46639 (11 2019), 4663. Issue 21. doi:10.3390/APP9214663 Importante
-
[28]
Daniel Jackson. 2019. Alloy: a language and tool for exploring software designs.Commun. ACM62, 9 (2019), 66–76. doi:10.1145/3338843
-
[29]
Kwiatkowska, Gethin Norman, and David Parker
Marta Z. Kwiatkowska, Gethin Norman, and David Parker. 2007. Stochastic Model Checking. InFormal Methods for Performance Evaluation, 7th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2007, Bertinoro, Italy, May 28-June 2, 2007, Advanced Lectures (Lecture Notes in Computer Science, Vol. 4486), M...
-
[30]
Ang Li, Xiaowei Yang, Srikanth Kandula, and Ming Zhang. 2010. CloudCmp: comparing public cloud providers. InProceedings of the 10th ACM SIGCOMM Conference on Internet Measurement(Melbourne, Australia)(IMC ’10). Association for Computing Machinery, New York, NY, USA, 1–14. doi:10.1145/1879141.1879143
-
[31]
Sara Mahdavi-Hezavehi, Matthias Galster, and Paris Avgeriou. 2013. Variability in quality attributes of service- based software systems: A systematic literature review.Information and Software Technology55, 2 (2013), 320–343. J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2026. 111:30 Á.M. Aparicio-Morales et al. doi:10.1016/j.infsof.2012.08.010
-
[32]
Anne Martens, Heiko Koziolek, Steffen Becker, and Ralf Reussner. 2010. Automatically Improve Software Architecture Models for Performance, Reliability, and Cost Using Evolutionary Algorithms. InInt. Conf. on Performance Engineering (WOSP/SIPEW). ACM, San Jose, California, USA, 105–116. doi:10.1145/1712605.1712624
work page internal anchor Pith review Pith/arXiv arXiv doi:10.1145/1712605.1712624 2010
-
[33]
Nenad Medvidovic, David S. Rosenblum, David F. Redmiles, and Jason E. Robbins. 2002. Modeling software architectures in the Unified Modeling Language.ACM Trans. Softw. Eng. Methodol.11, 1 (2002), 2–57. doi:10.1145/504087.504088
-
[34]
Indika Meedeniya, Irene Moser, Aldeida Aleti, and Lars Grunske. 2011. Architecture-based reliability evaluation under uncertainty. In7th International Conference on the Quality of Software Architectures, QoSA 2011 and 2nd International Symposium on Architecting Critical Systems, ISARCS. ACM, Colorado, USA, 85–94. doi:10.1145/2000259.2000275
-
[35]
Juan Manuel Murillo, Jose Garcia-Alonso, Enrique Moguel, Johanna Barzen, Frank Leymann, Shaukat Ali, Tao Yue, Paolo Arcaini, Ricardo Pérez-Castillo, Ignacio García-Rodríguez de Guzmán, Mario Piattini, Antonio Ruiz-Cortés, Antonio Brogi, Jianjun Zhao, Andriy Miranskyy, and Manuel Wimmer. 2025. Quantum Software Engineering: Roadmap and Challenges Ahead.ACM ...
-
[36]
2403.10518,http://arxiv.org/abs/2403.10518
Hoa T. Nguyen, Prabhakar Krishnan, Dilip Krishnaswamy, Muhammad Usman, and Rajkumar Buyya. 2024. Quantum Cloud Computing: A Review, Open Problems, and Future Directions.CoRRabs/2404.11420 (2024). doi:10.48550/ARXIV. 2404.11420
work page internal anchor Pith review doi:10.48550/arxiv 2024
-
[37]
Hoa T Nguyen, Muhammad Usman, and Rajkumar Buyya. 2024. Qfaas: A serverless function-as-a-service framework for quantum computing.Future Generation Computer Systems154 (2024), 281–300. doi:10.1016/j.future.2024.01.018
-
[38]
Michael A. Nielsen and Isaac L. Chuang. 2016.Quantum Computation and Quantum Information (10th Anniversary edition). Cambridge University Press, Cambridge. doi:10.1017/CBO9780511976667
-
[39]
Ricardo Pérez-Castillo and Mario Piattini. 2022. Design of classical-quantum systems with UML.Computing104, 11 (2022), 2375–2403. doi:10.1007/S00607-022-01091-4
-
[40]
Pérez-Delgado
Carlos A. Pérez-Delgado. 2022. A Quantum Software Modeling Language. InQuantum Software Engineering, Manuel A. Serrano, Ricardo Pérez-Castillo, and Mario Piattini (Eds.). Springer International Publishing, Cham, 103–119. doi:10. 1007/978-3-031-05324-5_6
2022
-
[41]
Poria Pirozmand, Ali Asghar Rahmani Hosseinabadi, Maedeh Farrokhzad, Mehdi Sadeghilalimi, Seyedsaeid Mirkamali, and Adam Slowik. 2021. Multi-objective hybrid genetic algorithm for task scheduling problem in cloud computing. Neural Computing and Applications33 (10 2021). doi:10.1007/s00521-021-06002-w
-
[42]
Nils Quetschlich, Lukas Burgholzer, and Robert Wille. 2025. MQT Predictor: Automatic Device Selection with Device- Specific Circuit Compilation for Quantum Computing.ACM Transactions on Quantum Computing6, 1, Article 10 (Jan. 2025), 26 pages. doi:10.1145/3673241
-
[43]
Javier Romero-Álvarez, Jaime Alvarado-Valiente, Enrique Moguel, Jose Garcia-Alonso, and Juan M Murillo. 2024. Enabling continuous deployment techniques for quantum services.Software: Practice and Experience54, 8 (2024), 1491–1515. doi:10.1002/spe.3326
-
[44]
Marie Salm, Johanna Barzen, Uwe Breitenbücher, Frank Leymann, Benjamin Weder, and Karoline Wild. 2020. The NISQ Analyzer: Automating the Selection of Quantum Computers for Quantum Algorithms. InService-Oriented Computing - 14th Symposium and Summer School on Service-Oriented Computing, SummerSOC 2020, Crete, Greece, September 13-19, 2020 (Communications i...
-
[45]
Mennan Selimi, Llorenç Cerdà-Alabern, Marc Sánchez-Artigas, Felix Freitag, and Luís Veiga. 2017. Practical Service Placement Approach for Microservices Architecture. InProceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid ’17). IEEE Press, Madrid, Spain, 401–410. doi:10.1109/CCGRID.2017.28
-
[46]
1996.Software architecture - perspectives on an emerging discipline
Mary Shaw and David Garlan. 1996.Software architecture - perspectives on an emerging discipline. Prentice Hall, New Jersey, USA
1996
-
[47]
Peter W Shor. 1999. Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer.SIAM review41, 2 (1999), 303–332. doi:10.48550/arXiv.quant-ph/9508027
work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.quant-ph/9508027 1999
-
[48]
Charilaos Skandylas, Narges Khakpour, and Javier Cámara. 2022. Security Countermeasure Selection for Component- Based Software-Intensive Systems. In2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS). IEEE, IEEE, Guangzhou, China, 63–72. doi:10.1109/QRS57517.2022.00017
-
[49]
Tobias Stollenwerk, Bryan O’Gorman, Davide Venturelli, Salvatore Mandrà, Olga Rodionova, Hokkwan Ng, Banavar Sridhar, Eleanor Gilbert Rieffel, and Rupak Biswas. 2020. Quantum Annealing Applied to De-Conflicting Optimal Trajectories for Air Traffic Management.IEEE Trans. Intell. Transp. Syst.21, 1 (2020), 285–297. doi:10.1109/TITS.2019. 2891235
-
[50]
2003.The Object Constraint Language: Getting Your Models Ready for MDA
Jos Warmer and Anneke Kleppe. 2003.The Object Constraint Language: Getting Your Models Ready for MDA. Addison- Wesley, Boston, MA, USA
2003
-
[51]
Zhenyu Wen, Jacek Cała, Paul Watson, and Alexander Romanovsky. 2017. Cost Effective, Reliable and Secure Workflow Deployment over Federated Clouds.IEEE Transactions on Services Computing10, 6 (2017), 929–941. doi:10.1109/TSC. J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2026. Architecting Hybrid Quantum-Classical Software Systems 111:31 2...
work page doi:10.1109/tsc 2017
-
[52]
Karoline Wild, Uwe Breitenbücher, Lukas Harzenetter, Frank Leymann, Daniel Vietz, and Michael Zimmermann. 2020. TOSCA4QC: Two Modeling Styles for TOSCA to Automate the Deployment and Orchestration of Quantum Applications. In2020 IEEE 24th International Enterprise Distributed Object Computing Conference (EDOC). IEEE, Eindhoven, The Netherlands, 125–134. do...
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.