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Quantum Information Processing

Layer model for gate-based modular quantum computers

Rob F. M. van den Brink, Juan Carlos Boschero, Michele Amoretti

Published Mar 17, 2026• 0 citations
Publisher

Abstract

This paper elaborates on a consensus view from the standardization body JTC22/WG3 on a layer model that offers a high-level hierarchical description of hardware and software modules to support the development of modular quantum computers. The group of lower layers covers multiple stacks, one for each hardware architecture, while the upper layers are defined around a common software stack. A hardware abstraction layer connects the two. The addition of a separate communication unit offers a robust separation between the stack and the outside world and allows controlled access for multiple users, as well as serving hybrid computing systems.

DOI
10.1007/s11128-026-05119-y

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This paper elaborates on a consensus view from the standardization body JTC22/WG3 on a layer model that offers a high-level hierarchical description of hardware and software modules to support the development of modular quantum computers. The group of lower layers covers multiple stacks, one for each hardware architecture, while the upper layers are defined around a common software stack. A hardware abstraction layer connects the two. The addition of a separate communication unit offers a robust separation between the stack and the outside world and allows controlled access for multiple users, as well as serving hybrid computing systems.
Abstract We propose a layer model to specify functionality and interfacing for hardware and software modules, to enable modular quantum computers. The group of lower layers covers multiple stacks, one for each hardware architecture, while the upper layers are defined around a common software stack. A hardware abstraction layer connects the two. The addition of a separate communication unit offers a robust separation between the stack and the outside world, and allows controlled access for multiple users as well as for being a server to hybrid computing systems.
Quantum computing is advancing rapidly, with notable progress in both hardware and algorithm development. However, to make quantum computing truly accessible and usable across disciplines, a comprehensive, efficient and unified software stack is essential. Such a software stack must be flexible enough to support diverse hardware platforms and evolving algorithms, while enabling programming models for a wide range of users from quantum specialists to users without deep quantum expertise. Additionally, a software stack must support dynamic resource management for efficient system utilization as well as seamless integration with classical High-Performance Computing (HPC) environments. The latter is key, as quantum systems are increasingly envisioned as accelerators within hybrid workflows, supporting various levels of integration from loosely to tightly coupled. Despite numerous discussions, conceptual proposals, and initial efforts in recent years, few tangible implementations of such full-featured software stacks currently exist.
In a world of various competing quantum computing architectures, hardware-agnostic, full-stack platforms are necessary to bring the full power of quantum computing hardware to domain experts via the cloud. QCI Connect and its Software Development Kit provide a reference architecture for a full-stack platform with a modular design and open-source interface definitions, built to facilitate a community-driven application ecosystem. Here, we present its overall design and features, central interfaces, and lessons learned, both for users of the platform and as a reference guide for future developments.
Abstract Steady progress is being made in the development of quantum computing platforms based on different types of qubit technologies. Each platform requires bespoke strategies to maximise the efficiency of the quantum/classical interface when operating close to the qubits. At a higher level, however, a shared interface allowing portability of quantum algorithms across all the available quantum platforms is preferred. Striking the right balance between portability and performance of the algorithm as implemented on quantum hardware remains a major challenge for this field. Here, we propose a quantum hardware abstraction layer (QHAL) providing a multi-level intermediate representation of the quantum stack. A collaborative effort between software specialists and quantum hardware developers operating on four major qubit technologies (photonics, silicon, superconducting and trapped ions) led to the identification of a minimum common set of instructions and metadata allowing the QHAL to interact efficiently with multiple platforms. Access to the stack from the higher levels increases latency yet minimises the amount of hardware architecture parameters to be handled by the algorithm developer, thus simplifying code development and reducing security threats from misuse or malicious access for hardware developers. Access to the stack from the lowest—closest to the qubits—level provides the highest hardware responsiveness, suitable for algorithms requiring minimum latency for data and instruction transfer. With respect to existing quantum assembly languages, the QHAL extends further down in the stack by defining an application-binary interface to interact with the quantum hardware. By defining a standard representation of the quantum stack, a common reference framework is provided to both software and hardware developers which would ensure future integration of their R&D efforts.
Fault tolerance is an indispensable prerequisite for constructing large-scale universal quantum computers. Drawing philosophies from classical computer architecture, this paper presents a hardware-agnostic three-layer high-level architectural framework for generic fault-tolerant quantum computation. Guided by the real execution workflows of fault-tolerant quantum algorithms, the proposed model is decoupled from specific physical qubit hardware platforms and quantum error correction codes, serving as a universal abstract standard rather than a platform-specific implementation scheme. Special attention is devoted to the intermediate Fault-Tolerance Layer, which serves as the architectural bridge between application-level logical programs and hardware-level execution. We systematically characterize its five internal components, the interfaces and data exchanged among them, and the execution, correction, and adaptation paths that together enable logical synthesis, fault-tolerant resources management, decoding, and runtime fault-tolerant control. An end-to-end example is further provided to illustrate the full-stack operating pipeline of fault-tolerant quantum algorithms under this framework. Given the increasing emphasis on modular, heterogeneous, and cross-layer fault-tolerant quantum systems, our architecture provides a unified foundational model for organizing such designs.
This paper presents a layered architecture QC-Stack for the quantum computing domain. It is a comprehensive framework explaining quantum computing systems by identifying three fundamental layers: the physical, system, and application layers. Each plays a crucial role in implementing quantum computing systems in practice. The physical layer evaluates quantum hardware technologies based on crucial performance parameters such as qubit quality, connectivity, and scalability. The system layer, which includes quantum firmware, compilers, operating systems, and software development tools, bridges the gap between the physical and application layers. The application layer incorporates Quantum Programming Languages and algorithms, emphasizing their significance in leveraging quantum computing potential across various domains. The paper provides a comparative analysis at a higher level of existing quantum algorithms, protocols, and hardware and software technologies within each sub-layer. It also highlights the strengths and weaknesses of different technologies at each layer. This holistic model can guide researchers and practitioners, offering insights into the ever-evolving landscape of quantum technology.