Study Maps 11 Types of Future Quantum Computer Users

Say there were a chemist and a bank executive approaching the same quantum computer. The chemist focuses on molecules and orbitals, whereas the executive concerns himself with costs and delivery times. They both need the machine, but for entirely different purposes. Now, what if there were ten more individuals, each with unique demands, all expecting the computer to speak their specific language?

This scenario forms the basis of a new study from several European institutions and Argonne National Laboratory. It addresses a question the quantum field has largely overlooked as it concentrated on hardware: Who will actually use these machines? The researchers identified eleven distinct user types, which they term “personas.”

It’s important to note that this is a preprint, available on arXiv, and slated for the MODELS Companion 2026 workshop. This is a venue for early-stage work and workshops, not a fully peer-reviewed flagship paper. The authors themselves acknowledge this, so keep that in mind.

Eleven personas, defined by their proximity to the hardware

The researchers categorize eleven personas by their proximity to the quantum machine itself.

At one extreme are users who never wish to interact with qubits. This group includes business users driven by profit and scalability, as well as early adopters aiming to establish business models. Government contractors represent a unique case; their security requirements necessitate transparency, which means they must inspect the software’s inner workings even if they’d prefer not to.

In the middle are scientific users. This includes physicists verifying theories, chemists investigating molecules and materials, and simulation engineers. These users often navigate between high-level interfaces for exploration and lower-level hardware interactions when developing new applications.

Finally, at the deepest level, are those responsible for maintaining the system. This encompasses platform builders who create SDKs and APIs (the toolkits and connection points for other users), quantum algorithm designers, HPC engineers integrating quantum processors into classical computing systems, and embedded quantum developers working on system-level components and distributed machines. These individuals require detailed, low-level access, much like a mechanic needs to see inside an engine.

The researchers further categorize these eleven personas by their motivations: commercial, technical, or scientific, highlighting their diverse goals and requirements.

The core challenge: Deciding what to abstract

The central concept of this paper is abstraction, or the degree to which users are exposed to system complexity.

Abstraction is ubiquitous in technology, often unnoticed. Spreadsheet users don’t need to understand transistor operations, and cloud programmers don’t know which physical server runs their code. Complexities are hidden behind user-friendly interfaces.

Quantum software, however, hasn’t yet reached this level of abstraction. Though frameworks like Qiskit and Cirq enable programming without direct hardware operation, achieving optimal results often requires knowledge of the specific machine. Hardware details frequently “leak” through the interface.

The study argues that the appropriate level of abstraction is entirely dependent on the user. A business user desires complete abstraction, whereas an HPC engineer requires exposed details because those details are integral to their work. Algorithm designers seek portable code but still need to understand machine limitations. A single interface can’t serve all these varied needs.

The authors propose a five-layer software architecture, ranging from end-user applications at the top to hardware development at the bottom, with algorithm development and compilation in between. Some personas operate within a single layer, while others frequently move between them.

Methodology

It’s crucial to be transparent about the study’s methodology, which is relatively small-scale, as the authors openly state.

The research employed two qualitative approaches. First, a focus group was conducted at a 2024 Dagstuhl seminar on quantum software engineering, involving eight to ten experts. Second, the researchers recruited the practitioners at the QCE 2025 conference, where eleven individuals provided demographic information, and nine participated in semi-structured interviews lasting fifteen to forty minutes.

These nine interviews weren’t audio-recorded due to time and confidentiality constraints; data was collected through handwritten notes. Convenience sampling was used, which means participants were selected based on availability. All participants were already part of the quantum community. The authors explicitly acknowledge that individuals attending a quantum conference are not representative of future mainstream users, highlighting this bias.

Consequently, the authors do not present this as a definitive map but rather as a “persona hypothesis.” As lead author Lukas Schmidbauer and his colleagues caution in the paper:

“The identified personas should be understood as a hypothesis that requires refinement through broader future user studies.”

Still, they do note two encouraging points: the independent focus group and interview findings showed a higher-than-expected degree of agreement, and the interviews exhibited early signs of saturation, which means later participants generally reinforced existing personas as opposed to introducing new ones. These are encouraging indicators, but not conclusive proof.

Reality versus forecast

What is real: Eleven personas, identified from a documented workshop group and nine interviews, categorized by the level of machine interaction each requires. This offers a valuable framework for anyone developing quantum software who might otherwise default to designing solely for physicists.

What is a forecast: The long-term vision of a business application seamlessly interacting with a quantum computer, where internal stakeholders remain unaware or unconcerned, evaluating results based on cost and runtime, just like any other service. This represents the researchers’ scenario for a mature market. Today, qubit details often remain exposed, and this study provides an initial outline of the individuals who will eventually require these complexities to be hidden.