QuEra Computing Uses AI to Automate a Critical Quantum Computer Subsystem, Enabling the Acceleration of Commercial-Grade Quantum Computing Deployments from QuEra

An AI agent, Anthropic's Claude, developed and validated the control logic for the laser system in a QuEra quantum computer, recovering it in seconds versus an expert needing minutes, and holding it steadier than a specialist's manual tune. QuEra plans to extend the approach to other subsystems.

BOSTON, Aug. 27, 2026 /PRNewswire/ -- QuEra Computing, the leader in quantum computing, today announced results from its work in the Model Hardware Standard (MHS) research preview, in which an AI agent, Anthropic's Claude, performed one of the most expert-dependent jobs in operating a quantum computer: keeping its laser system on target. The agent wrote and validated its own control software, which now recovers the system in seconds with no manual intervention, obviating the need for manual work that previously required a specialist on site.

Quantum computers are moving from laboratory instruments to products customers buy and operate themselves. That transition depends less on physics than on whether a machine runs reliably without the people who built it standing next to it. QuEra's systems use lasers held at precise frequencies to control atomic qubits. Those lasers drift, and when one drifts far enough the machine stops until someone with deep and specific expertise brings it back. Every generation of machine carries more lasers than the last, and every machine at a customer site sits further from the engineers who know them best.

Automating a Critical Subsystem

QuEra has automated recovery from common laser disturbances for years, and Aquila, its 256-qubit system on Amazon Braket, runs with uptime above 99%. The more complex laser failures are rarer and more severe, and have resisted automation to date because recovery calls for human expert judgment rather than a fixed sequence of steps.

A QuEra team of four specialists spent two to three weeks writing a recovery script by hand, and it handled only the failures its authors thought to list. The team then gave the same problem to Claude, working through the MHS, a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. MHS started as a collaboration between Anthropic and HHMI Janelia Research Campus and is currently in a limited research preview, in which QuEra is a participant. MHS let the agent run its own experiments on a dedicated testbed and propose a fix, try it, read the result, refine. It ran that loop continuously, including overnight, covering hundreds of failure cases that no team of specialists would have time to work through by hand.

Engineers set the scope, reviewed every step, and decided what counted as proof of success. The software the agent produced is a conventional, fully inspectable program, not a model making decisions at runtime. And the work stayed safe by design: devices declare bounds, interlocks, and emergency stops in the standard itself, and AI agents inherit and operate within them by default.

What the Pilot Proved

• It recovered reliably. Given no information about what had gone wrong, the controller returned the system to target in 695 of 700 timed trials across seven fault types, and never reported success when it had not succeeded. The five misses traced to a rig condition rather than the software.
• It recovered in seconds. Most faults cleared in under six seconds and the hardest in roughly 10 to 14 seconds, against five to 10 minutes for an expert.
• It handled real faults, not only test cases. The testbed sits in a working lab with ordinary foot traffic and real environmental sources of error. Over the pilot the AI agent recovered every time without help, regardless of the cause.
• It improved on expert tuning. Asked to improve the quality of the lock rather than recover it, the AI agent cut residual noise by a factor of five and stopped the system dropping out during unattended runs. Measured afterward on an independent instrument it could not influence, its settings matched an experienced specialist's manual tune and corrected a flaw the manual tune had left behind.
• It transferred. Pointed at a second laser wavelength, the AI agent worked out the settings from scratch in one unattended overnight run, a job that normally takes weeks of hands-on commissioning.

Why It Matters for Deployment

Prior to this pilot, every laser used to carry a standing claim on scarce human expert time. On-site recovery was required at any hour, taking up to half an hour per tuning session, and commissioning a new operating point took weeks. Given the increased number of lasers per computer and additional deployments in the field, manual expert labor becomes a limit on how many systems can be deployed and properly supported, and a barrier to fault-tolerant quantum computing at scale.

"For years the hardest part of scaling quantum computers wasn't the physics, it was the people driving at 2 am to fix a laser lock. We built a solution using the Model Hardware Standard to fix that: the lock recovers itself in seconds, verified every time, catching noise that's easy to miss by hand. We're building quantum computers that fix themselves," said Sergio H. Cantu, Vice President of Quantum Systems, QuEra Computing.

After the pilot, little or no expert guidance is required. For an HPC center or national laboratory installing a system on-premises, that is the difference between needing a resident neutral-atom laser specialist and needing very little of one's time.

Why QuEra Partners

The laser in this pilot is one of many subsystems in a quantum computer that are precise, fragile, and demanding of expert attention. QuEra expects the same AI automation approach to apply to others, and the pilot leaves behind the safety practices and measurements that enabled the second campaign to take one night where the first took weeks.

"We are among the best in the world at developing and operating quantum computers, and even for us, the cost of keeping these machines at peak performance is high," said Takuya Kitagawa, President of QuEra. "A customer expects the entire computer, and thus every subsystem, to hold itself together without a specialist in the room. This is why the results from the MHS research preview and Anthropic's frontier AI models are so meaningful. We are making it far easier and cheaper to keep our computers running at their best."

QuEra works deeply with a small number of companies chosen for strategic capabilities: Amazon Web Services for cloud delivery of Libra on Amazon Braket in 2028, HPE for on-premises HPC integration, and NVIDIA for accelerated computing. QuEra's participation in the Model Hardware Standard research preview, applying AI agents to the control of quantum computing hardware, is an early example of AI partnerships.

Learn More

• Read Anthropic's MHS announcement 
• Read the full technical write-up, with measurement detail and animations 
• Explore the roadmap, covering Libra and QuEra's next-generation gigaquop-class system 
• Apply to the FTQC Founders Circle

About the Model Hardware Standard

The Model Hardware Standard (MHS) is a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. It started as a collaboration between Anthropic and HHMI Janelia Research Campus and is currently in a limited research preview, with access by application while the safety design is validated. Devices declare bounds, interlocks, and emergency stops in the standard itself; AI agents inherit and operate within them by default.

About QuEra Computing

QuEra is putting quantum to work. As the scientific and commercial leader in neutral-atom quantum computing, we help enterprise innovators leverage quantum to gain competitive advantage, support HPC centers as their users tackle classically intractable problems, and enable government programs to build national and sovereign capabilities. We do this by combining our quantum systems, available on-premises and via the cloud, with application co-design and collaborative research. Born at Harvard and MIT and still advancing together, QuEra builds neutral-atom systems on a public, peer-reviewed path to fault tolerance, and operates globally from Boston, New Mexico, Tokyo, Zurich, and the United Kingdom. As quantum computing moves from "one day" to "Day One," QuEra delivers practical impact today while leading the path toward large-scale, fault-tolerant systems. See what's possible at www.quera.com.

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SOURCE QuEra Computing