State of the Quantum Software Engineering Ecosystem
Nazanin Siavash, Armin Moin
TL;DR
The paper investigates the current state of the Quantum Software Engineering (QSE) ecosystem by identifying active academia, industry, and entrepreneurial players. It introduces an AI-assisted data collection pipeline powered by GPT-5 to extract publications, affiliations, company activity, and venture funding signals across curated venues, with a QSE-only focus. The authors present a global mapping of universities, research centers, and industrial participants, plus a list of quantum software startups that have raised at least $1M. They discuss limitations, notably reproducibility and prompt variability of LLMs, and propose future work to strengthen validation and broaden data sources.
Abstract
We study the current state of the Quantum Software Engineering (QSE) ecosystem, focusing on the achievements, activities, and engagements from academia and industry, with a special focus on successful entrepreneurial endeavors in this arena. Our research methodology is a novel one, featuring the state-of-the-art in Artificial Intelligence (AI), namely Large Language Models (LLMs), especially Generative Pretrained Transformers (GPT). We use one of such models, namely the OpenAI GPT-5 model, through the ChatGPT tool. The goal is to identify institutions and companies that are highly active and have achieved distinguished results in QSE, evidenced by peer-reviewed publications or raised capital in the venture capital market.