Berkeley Lab Researchers Use 7,000 GPUs to Simulate Quantum Chip in Extreme Detail

Detailed computer modeling allows scientists to predict chip behavior before fabrication, speeding up quantum hardware development.

Mar. 18, 2026 at 3:36am

Got story updates? Submit your updates here. ›

Researchers at Lawrence Berkeley National Laboratory have developed an advanced computer simulation that models every physical detail of a quantum chip, including materials, layouts, and qubit behavior. Using nearly 7,000 GPUs on the Perlmutter supercomputer, the team was able to discretize the chip into 11 billion grid cells and run over a million time steps in just seven hours, evaluating three circuit configurations in a single day. This unprecedented level of detail allows them to catch potential issues early and confirm designs will perform as expected, accelerating the development of next-generation quantum hardware.

Why it matters

Creating detailed computer models of quantum chips helps scientists predict how they will behave before manufacturing begins. This approach allows researchers to catch potential issues early and confirm that designs will perform as expected, speeding up the development of practical quantum computing hardware. The ability to simulate the physical structure and behavior of a quantum chip in such fine detail is a significant advancement over previous 'black box' approaches that simplified the complexities.

The details

The researchers used the ARTEMIS exascale modeling tool to simulate and refine a quantum chip developed through a collaboration between UC Berkeley's Quantum Nanoelectronics Laboratory and Berkeley Lab's Advanced Quantum Testbed. The simulation captures the chip's physical structure down to the micron level, including the materials, layouts, and how qubits interact with each other and the rest of the circuit. By using Maxwell's equations in the time domain, the simulation can also account for nonlinear effects and track how signals evolve in real time.

  • The simulation was run over 24 hours, using nearly all 7,168 NVIDIA GPUs on the Perlmutter supercomputer.
  • The researchers were able to evaluate three circuit configurations within a single day on Perlmutter.

The players

Zhi Jackie Yao

Researcher in the Applied Mathematics and Computational Research (AMCR) Division at Lawrence Berkeley National Laboratory.

Andy Nonaka

Researcher in the Applied Mathematics and Computational Research (AMCR) Division at Lawrence Berkeley National Laboratory.

Irfan Siddiqi

Director of the Quantum Nanoelectronics Laboratory at the University of California, Berkeley.

Bert de Jong

Director of the Quantum Systems Accelerator (QSA) at Lawrence Berkeley National Laboratory.

Katie Klymko

Quantum computing engineer at the National Energy Research Scientific Computing Center (NERSC).

Got photos? Submit your photos here. ›

What they’re saying

“The computational model predicts how design decisions affect electromagnetic wave propagation in the chip, to make sure proper signal coupling occurs and avoid unwanted crosstalk.”

— Andy Nonaka, Researcher, Applied Mathematics and Computational Research Division

“We do full-wave physical-level simulation, meaning that we care about what material you use on the chip, the layout of the chip, how you wire the metal -- the niobium or other type of metal wires -- how you build the resonators, what's the size, what's the shape, what material you use. We care about those physical details, and we include them in our model.”

— Zhi Jackie Yao, Researcher, Applied Mathematics and Computational Research Division

“This unprecedented simulation, made possible by a broad partnership among scientists and engineers, is a critical step forward to accelerate the design and development of quantum hardware. More powerful, more performant quantum chips will unlock new capabilities for researchers and open up new avenues in science.”

— Bert de Jong, Director, Quantum Systems Accelerator

What’s next

The team plans to expand their simulations to gain a more precise understanding of the chip's spectral behavior and how it performs within larger systems. Once the chip is fabricated and experimentally evaluated, the researchers will compare the results with their predictions and refine the simulation accordingly.

The takeaway

This unprecedented simulation of a quantum chip at the physical level, leveraging the massive computing power of the Perlmutter supercomputer, represents a significant advancement in the ability to model and predict the behavior of quantum hardware before it is even fabricated. This approach has the potential to dramatically accelerate the development of practical quantum computing technologies.