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UCLA scientists lead $75M push to build reliable quantum computers

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August 27, 2026 by Ivy Delaney

Jason Cong and Jens Palsberg of UCLA will co-lead national quantum computing efforts following the distribution of $290 million in funding from the National Science Foundation. The funding is distributed among eight institutes, with each scientist heading separate institutes focused on overcoming critical barriers to reliable quantum computation.

Cong will direct UCLA’s development of AI-based tools to improve quantum computer efficiency, while Palsberg will co-lead a UC Berkeley-based network including UCLA Samueli, UC Santa Barbara, Caltech, and Stanford. “Quantum computers have the potential to solve problems that are out of reach for today’s computers, but we still have a lot of work to do to get there,” Palsberg said.

Fault-Tolerant Systems Research Led by Harvard, UCLA, and MIT

Cong will spearhead UCLA’s development of artificial intelligence-based tools designed to enhance the reliability and efficiency of quantum computers, addressing the pervasive issue of errors in these nascent systems. This work forms a core component of the newly established Institute for Fault-Tolerant Quantum Systems, Architectures and Applications, a collaborative effort led by Harvard University with UCLA Samueli and MIT as key partners.

Researchers aim to create quantum computers capable of performing calculations reliably despite inherent noise and instability. The NSF Quantum Leap Challenge Institutes are among eight institutes receiving more than $290 million in new funding to advance U.S. quantum science and accelerate the development of technologies with practical applications.

The Institute for Quantum Computation, renewed with a five-year, $37.5 million grant, will investigate the potential of quantum computation and develop new technologies, with the UCLA team concentrating on resolving bottlenecks within trapped-ion quantum computing systems and creating software to evaluate diverse quantum technologies. The UCLA researchers anticipate their contributions will pinpoint areas where quantum computers can deliver the most substantial impact, moving beyond theoretical potential toward practical applications. Cong’s focus on AI-driven solutions suggests a shift toward automated error mitigation, while Palsberg’s work on software comparison aims to establish benchmarks for evaluating the performance of different quantum platforms.

Quantum computers have the potential to solve problems that are out of reach for today’s computers, but we still have a lot of work to do to get there.

Jens Palsberg, Professor at UCLA Samueli School of Engineering
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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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