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AI tool lets researchers 'vibe code' in the quantum realm
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Quantum computers, such as this one shown at this year’s Mobile World Congress in Barcelona, Spain, could run programs that have been almost completely generated by artificial-intelligence tools. Credit: Angel Garcia/Bloomberg/Getty
‘Vibe coding’ is moving into quantum computing — a field in which programming has notoriously required sophisticated skills. To lower this barrier, researchers at Pasqal, a quantum-computing start-up company in Paris, have developed an artificial-intelligence tool that can turn an English-language prompt into quantum computing code and then autonomously run it on a quantum computer.
The agent, which is described in a preprint posted on the arXiv server last month1, often requires feedback from people with specialized knowledge to work properly. But its creators say that it still accelerates the work and it could make quantum computers — machines that can greatly speed up certain calculations by harnessing quantum phenomena — accessible to a wide range of researchers.
Christophe Jurczak, a co-author of the work and one of Pasqal’s co-founders, says the agent enabled him to run experiments that would commonly require a team of physicists who are highly specialized in quantum-computing. “And I can do it on my own, from my couch in Dallas, Texas.”
In classical, as opposed to quantum, computer programming, vibe coding refers to an extreme version of AI-aided software engineering, in which the user describes to an AI tool what they want a piece of software to do, and the machine — perhaps after a few adjustments according to the user’s feedback — produces and runs a fully working program.
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Frontier large language models (LLMs), such as Anthropic’s Claude, have displayed a grasp of quantum computing, and many researchers now use them to help write not just classical but also quantum code. To see whether such LLMs could go as far as quantum vibe coding, Jurczak and his collaborators familiarized frontier LLMs with the technical specifications of Pasqal’s quantum computers.
They aimed specifically at streamlining the development of one of the most promising applications of quantum computers — quantum simulations. These involve tuning a quantum computer to resemble the behaviour of another physical system, such as a catalyst or a material with unusual magnetic properties. The quantum machine running the simulation could then predict the materials’ properties with calculations that would overwhelm a classical computer.
In their study, the Pasqal team subjected the AI agent to three tests. In each case, they chose a physics paper describing a physical phenomenon that could, in principle, be simulated on a quantum computer, and asked the agent to write and execute the code to confirm this.