Nullspace software uses quantum standing waves to cool trapped ions

Researchers at Cornell University, led by Professor Karan Mehta, have achieved the first experimental demonstration of standing-wave electromagnetically-induced-transparency (EIT) cooling for trapped ions using Nullspace ES software, building on theoretical work from 1992, the company says. Nullspace ES simulated the electrostatic fields generated by the chip surface electrodes, providing voltage calculations critical for axial confinement, radial mode rotation, and precise ion positioning.

This new cooling approach delivered higher cooling rates and addressed a broader range of modes than conventional methods; Masha Petrova, CEO of Nullspace, states that Cornell’s work demonstrates why simulation must advance alongside hardware, if not ahead of it.

Nullspace ES Simulates Electrostatics for Precise Trapped-Ion Control

The Mehta Group previously relied on COMSOL and a custom Python toolkit, but these proved insufficient. COMSOL’s comprehensive physics modeling slowed iteration, while the toolkit lacked the fidelity required for the experiment’s precision. The successful demonstration builds on theoretical predictions for standing-wave EIT cooling first made in 1992, realizing a long-sought advancement in trapped-ion technology.

These improvements are not merely incremental; they represent a step toward faster and more scalable quantum systems, facilitated by the ability to simulate increasingly complex chip-scale architectures. Petrova also noted that the need for advanced simulation tools is driven by the accelerating pace of quantum hardware development, explaining that as quantum hardware grows more complex, researchers are under pressure to iterate at a faster pace, emphasizing the importance of simulation keeping pace with, or even exceeding, hardware advancements.

Cornell Professor Karan Mehta, principal investigator of the study, affirmed the value of Nullspace ES in streamlining the research process. He stated that Nullspace ES has proven valuable in allowing his team to carry out accurate trap simulations efficiently, which is essential to effective design and simulation of devices at the precision important for these kinds of experiments. The Mehta Group integrated Nullspace ES into an automated pipeline, linking chip design directly to experimentally usable voltage sets, a workflow that significantly reduced development time, according to the company.

This integration highlights a broader trend toward tighter coupling between simulation and fabrication in quantum computing, where rapid prototyping and optimization are paramount. The software’s ability to deliver high-fidelity simulations with faster iteration times positions it as a key enabler for future advancements in trapped-ion quantum computing and beyond.

Nullspace ES has proven highly valuable in allowing us to carry out accurate trap simulations efficiently, which is essential to effective design and simulation of devices at the precision important for these kinds of experiments.

Cornell Professor Karan Mehta, principal investigator of the study
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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