Toolchain for Faster Iterations in Quantum Software Development

2025-07-10

AI Summary

Quantum software development faces significant challenges, including scarce quantum hardware access, high computational overhead in classical simulation, and complex integration with heterogeneous accelerators. To address these issues, this paper proposes a quantum software toolchain designed for efficient iterative development. Our approach introduces three key innovations: (1) a lightweight remote computation scheduling mechanism enabling seamless switching between local development environments and remote quantum or simulation resources; (2) a plugin-based Jupyter kernel architecture supporting plug-and-play extensibility; and (3) integration of a high-performance distributed quantum simulator, extending scalable simulation capacity to 21–29 qubits. Experimental evaluation demonstrates up to 5× speedup on representative quantum circuit workloads, while maintaining robust support for complex circuit design and high-frequency iterative development. The toolchain significantly enhances quantum software engineering productivity and scalability.

Technology Category

• Machine Learning: Quantum Machine Learning
• Constraint Satisfaction and Optimization: Solvers and Tools
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. To realize this promise, these new capabilities need software solutions that are able to effectively harness its power. However, developers may face significant challenges when developing and executing quantum software due to the limited availability of quantum computer hardware, high computational demands of simulating quantum computers on classical systems, and complicated technology stack to enable currently available accelerators into development environments. These limitations make it difficult for the developer to create an efficient workflow for quantum software development. In this paper, we investigate the potential of using remote computational capabilities in an efficient manner to improve the workflow of quantum software developers, by lowering the barrier of moving between local execution and computationally more efficient remote hardware and offering speedup in execution with simulator surroundings. The goal is to allow the development of more complex circuits and to support an iterative software development approach. In our experiment, with the solution presented in this paper, we have obtained up to 5 times faster circuit execution runtime, and enabled qubit ranges from 21 to 29 qubits with a simple plug-and-play kernel for the Jupyter notebook.

Problem

• Addressing limited quantum hardware access for developers
• Reducing computational demands of quantum simulation
• Simplifying quantum software development workflow complexity

Innovation

• Remote computational capabilities for efficiency
• Plug-and-play Jupyter notebook kernel
• Faster execution with simulator surroundings