How a Convening at UC San Diego Could Help Shape California’s Quantum Future

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• Mika Ono - [email protected]

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Qualcomm Institute: What is the backstory of this event?

Riley Need: Late last year, California Governor Gavin Newsom announced the statewide Quantum California initiative, a public-private initiative meant to solidify California as a global leader in quantum computing, sensing, networking and materials. Related state legislation (AB 940) instructed the California Governor's Office of Business and Economic Development (GO-Biz) to put together a strategic framework to help policy makers understand the California quantum ecosystem: What are our strengths? What are our weaknesses? What are our opportunities? What should state legislators focus on in terms of funding or legislation that will help the state not only be part of the quantum revolution, but a leader nationally and globally? A convening was held at UC Berkeley to kick off Quantum California and have discussions that would contribute to this report. The report is due to the State legislature by the end of June.

QI: Tell me more about the convenings.

Need: The first two convenings were largely word of mouth. Ramesh Rao [director of the UC San Diego Qualcomm Institute] attended the event in Berkeley, and he got talking with Keith Wright, who does business development for Quantum Machines, and Namit Anand, a research scientist at Hewlett Packard Enterprise (HPE). The San Diego event, whose sponsors include Quantum Machines and HPE, was born out of those conversations.

The idea is that the San Diego gathering will be a recurring annual event, regardless of what happens to Quantum California. Of course, we hope the state will continue to keep that initiative going and money will come from the State legislature, not only for reports and ecosystem building, but for research and infrastructure. However, this report will come out after this year's budget has been decided and before a new governor takes office next year, so we'll see where this all goes.

QI: What's drawing people to the room this time?

Need: Participants may want to be part of the conversations contributing to the report. We also have Nobel laureates, company CEOs, CTOs and major players attending, so that's a draw. When you look at the major quantum companies in California and across the US, most of them are sending someone to either give a talk or participate in the discussions.

QI: What are your goals here?

Need: Big picture, I'd say there are two main challenges for the quantum R&D community: applications and scaling. We'll set aside, for a moment, the technical difficulty of building large-scale quantum machines. Even if we can build them, we need compelling applications that justify a multi-year, multi-billion-dollar investment. What will these systems do that classical computers cannot?

There's still a lot of debate about which applications will ultimately dominate, but three areas often rise to the top: materials discovery, cryptography and logistics.

First is materials discovery, which spans everything from drug design to high-temperature materials for aerospace. Accurately predicting molecular structure and properties requires solving quantum mechanical equations. Classical computers approximate these calculations, which introduces errors and limits scalability. Quantum computers, in principle, can model quantum systems more naturally, offering the potential for higher accuracy.

That said, current quantum hardware can only handle small systems (e.g., simple molecules like hydrogen, water or methane). While that is a major scientific achievement, scaling both hardware and algorithms is essential before this becomes transformative. Still, many engineering challenges ultimately come down to material limits like heat tolerance, conductivity, durability. If quantum computing can accelerate materials discovery, the long-term impact could be substantial.

Second is cryptography. This is one of the earliest and most well-understood applications. In the 1990s, Shor's algorithm showed that a sufficiently large quantum computer could break widely used public-key cryptosystems like RSA. In response, the field of post-quantum cryptography developed classical algorithms believed to be resistant to quantum attacks. These are now being standardized and adopted, although the transition is slow due to cost and complexity. So the issue is not that encryption is "unsolved," but that large-scale quantum computers could render current systems insecure, requiring a global migration to new standards.

Third is optimization and logistics. Problems like routing (e.g., the traveling salesman problem), supply chain optimization and scheduling become exponentially harder as they expand. Quantum algorithms may offer advantages for certain classes of these problems, although in many cases the advantage is expected to be incremental or problem-specific rather than universal. Still, even modest improvements could have a large economic impact in industries like transportation and manufacturing.

QI: The second problem is scaling?

Need: Right. Even with a decent sense of where quantum computers might be useful, actually getting there depends on whether and how we can build machines at the right scale and quality.

Today's quantum computers are still relatively small - on the order of hundreds, maybe a few thousand, qubits. And just as importantly, those qubits are what we call "noisy."

What that means, in plain terms, is that they're very fragile. They lose information easily, they make mistakes, and their calculations can drift off course if you don't constantly correct them. So even if you have a few hundred qubits, you can't yet rely on them to carry out long, complex computations accurately.

To do the kinds of useful things we talked about, like designing new materials, you likely need much larger, more stable systems. That usually means building in error correction, where many imperfect qubits work together to act like one reliable "logical" qubit. Accounting for that overhead, people often estimate you'd need millions of physical qubits to do something truly transformative.

Now, some recent developments could change that timeline. For example, one of our keynote speakers is from a startup called Oratomic, a Caltech spinout. They recently published a paper suggesting that certain applications, like running Shor's algorithm, might be possible with far fewer qubits, perhaps as few as 10,000, if you design the system in a particular way. That's an exciting idea, but it's still early. The results haven't been independently confirmed yet, so the field is watching closely but cautiously.

So when we talk about scaling, it's really two things at once: Can we build bigger systems, and can we make them reliable enough to actually be useful?

Those two challenges are tightly connected, which is why people often call this a co-design problem. The way we build the hardware impacts what algorithms will work, and vice versa.

As a historical analogy, I'd compare where we are today to classical computing in the 1950s and early 1960s. Back then, we were transitioning from vacuum tubes to early transistors, and nothing was fully settled. Different technologies were competing, reliability was a major issue, and people were still figuring out what these machines would ultimately be good for.

Quantum computing feels similar right now - there's real progress, but also a lot of uncertainty about which approaches will scale and where the biggest impact will land.

QI: It's a fascinating time to bring people together.

Need: Agreed. Overcoming challenges around applications and scaling is going to require real coordination across industry, academia, government and the nonprofit sector. My hope is that the upcoming event at QI can serve as a space to bring those stakeholders together and to gather input, build alignment and strengthen connections, both across regions and between sectors.

A good example of where that coordination really matters is workforce development. The companies building quantum technologies need highly trained researchers and engineers, which means universities play a critical role in creating teaching and research opportunities that prepare students for those jobs. But there's a tension: industry moves quickly and often can't share proprietary details, while academia needs enough visibility to design relevant, forward-looking programs. Bridging that gap requires a relationship that's genuinely collaborative, adaptive and reciprocal.

At the same time, this is expensive work. It requires significant investment in shared infrastructure - facilities, equipment and programs that can both attract industry to California and help train and retain a skilled workforce here.

QI: How is the event shaping up with respect to your hopes for the sector?

Need: There's a lot of potential upside in aligning California's quantum ecosystem, but it's also a large, complex system with competing priorities. We're trying to address that head-on in how we've designed the program.

Our opening keynote is from Nobel laureate John Martinis, an industry leader who's deeply engaged in the scaling challenge, and one goal is for the group to dig into what it will take to move these technologies forward in practical ways: what's helping, what's holding things back, and where we should be focusing our efforts. Later that same day, GO-Biz Deputy Director for Innovation and Emerging Technologies Trelynd Bradley will speak about what California is doing through the Quantum California initiative and how the state is thinking about these same challenges. After lunch, we'll shift into small-group roundtable discussions. Participants will work through targeted questions that we're developing in coordination with the Governor's office - aligned with what GO-Biz is looking to include in its report. We'll have note-takers in each group so we can synthesize that input and share it back, helping inform the broader alignment effort.

QI: The stakes for quantum seem pretty high.

Need: They are. If you think about one of those "hockey stick" curves, quantum is right at the point where things could start accelerating quickly. There's a real sense of exponential potential.

It's an exciting moment from a scientific research perspective because the tools we're building could open up entirely new ways of understanding and interacting with the physical world. But it's also a big opportunity for industry: new companies, new markets, and a growing demand for talent.

This isn't something that's going to settle down anytime soon. We're likely looking at a sustained period - easily the next decade - of rapid development, experimentation and investment.

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