Quantum Software Ecosystem Design

TL;DR

The paper argues that realizing practical quantum computing requires a scientifically grounded quantum software ecosystem built around hardware-software co-design. It proposes a two-pronged framework: a conceptual view covering computational paradigms, algorithms, software engineering, and error handling, and a system-architecture view detailing interfaces, orchestration, data management, and simulators. Key contributions include a structured analysis of stakeholder needs, a detailed discussion of compiling and error-management pipelines, and architectural patterns for end-to-end platforms that integrate classical and quantum resources. The work aims to provide a practical, adaptable blueprint for developing quantum software ecosystems capable of enabling near-term quantum advantages and guiding future hardware evolution.

Abstract

The rapid advancements in quantum computing necessitate a scientific and rigorous approach to the construction of a corresponding software ecosystem, a topic underexplored and primed for systematic investigation. This chapter takes an important step in this direction: It presents scientific considerations essential for building a quantum software ecosystem that makes quantum computing available for scientific and industrial problem solving. Central to this discourse is the concept of hardware-software co-design, which fosters a bidirectional feedback loop from the application layer at the top of the software stack down to the hardware. This approach begins with compilers and low-level software that are specifically designed to align with the unique specifications and constraints of the quantum processor, proceeds with algorithms developed with a clear understanding of underlying hardware and computational model features, and extends to applications that effectively leverage the capabilities to achieve a quantum advantage. We analyze the ecosystem from two critical perspectives: the conceptual view, focusing on theoretical foundations, and the technical infrastructure, addressing practical implementations around real quantum devices necessary for a functional ecosystem. This approach ensures that the focus is towards promising applications with optimized algorithm-circuit synergy, while ensuring a user-friendly design, an effective data management and an overall orchestration. Our chapter thus offers a guide to the essential concepts and practical strategies necessary for developing a scientifically grounded quantum software ecosystem.

Figures (7)

• Figure 2: Conceptual stack of the components necessary to solve problems using qc.
• Figure 3: Visualization of an arbitrary qubit state called the Bloch sphere. The computational basis states $|0\rangle$ and $|1\rangle$ are mapped to the north pole and the south pole respectively. A general state $|\psi\rangle$ is fully determined by the angles $\theta$ and $\varphi$. Any quantum gate on a single qubit corresponds to a rotation of the state on that sphere. Graphic taken from Schuhmacher2021.
• Figure 4: An example of a circuit diagram, the most common way to represent quantum programs today. Horizontal lines correspond to qubits. Gates are represented by special symbols or boxes with labels. Double lines indicate classical information, which can represent results of the circuit. But they can also be used to condition the application of gates on measurement results, a technique called feed-forward.
• Figure 5: State of development of different hardware platforms according to BSI_study. In this study, the platforms are classified into five different levels from satisfying the DiVincenco criteria (level A), demonstration of high fidelities (level B) to the demonstration of quantum error correction (level C). The levels D (execution of fault-tolerant operations) and E (running fault-tolerant algorithms) have not been achieved by any platform so far.
• Figure 6: Sketch of the KQCircuits chip design by the company IQM Quantum Computers (courtesy of IQM Quantum Computers).