Peking University PhD Team Crosses the Quantum Valley of Death: 8 Years of Refinement from Laboratory to Engineering

Background

In July 2026, a quantum computing company called "Nakai Quantum," established just three months prior, announced completing tens of millions of yuan in Series A funding, led by Hillhouse Capital. This sounds like routine tech startup news—until you look at what this company actually does.

Nakai Quantum focuses on two technical tracks: "ultracold atom quantum simulation" and "neutral atom universal quantum computing." If you know anything about quantum computing, you understand both tracks are in "cutting-edge but far from commercialized" territory—they remain primarily confined to academic papers and national laboratories. What's more absurd is that the company's founder and CEO, Fan Yaoyuan, was born in 1998, graduated with his PhD just years ago, yet has already pulled off engineering feats like "China's first ultracold atom interferometric gyroscope" and "China's first ultracold atom Bloch oscillation gravimeter"—these names sound academic, but translated they mean: he has turned "what only academic laboratories can do" into "repeatable, verifiable, deliverable engineering products."

The final sentence of the financing announcement is the real thunderbolt: "Projected full-year 2026 revenue reaching tens of millions of yuan." How can a quantum startup established just three months ago, with no commercialized quantum computing chip deliveries, possibly have "million-yuan market orders" and "projected revenue of tens of millions?"

The Formation of Death Valley

Before understanding the "Nakai phenomenon," we must first understand why most top scientific discoveries ultimately disappear.

In the 2020s, over a hundred quantum computing startups emerged globally. IBM, Google, IonQ, Rigetti, D-Wave—these names represent different technical routes: superconducting qubits, ion traps, photonics, neutral atoms, and more. Many of these companies were founded by academic heavyweights in the field—professors from MIT, Caltech, Oxford, and ETH Zurich.

By the logic of "celebrity effect" and "scientific breakthrough," these companies should all commercialize smoothly. But reality presents a bizarre predicament—

"We can build it, but not well; we can repeat it, but not fast; we can prove it works, but can't scale it."

This is the infamous "Death Valley." It doesn't occur in the early, capital-starved startup phase, but rather in the second and third stages—where funding is abundant, papers exist, and prototypes are working.

Here's a concrete example: In 2023, a mainstream American ion trap quantum computing company delivered its first "commercial" quantum computer to a customer. What happened? After three months, the customer found the machine's reliability and maintenance costs made it an "expensive exhibit." The company's problem was no longer "can it compute" (that was proven in papers long ago), but rather "how do we let engineers, not physicists, maintain this machine on a daily basis?"

That's the essence of Death Valley: Scientific problems and engineering problems exist in two different universes.

Why Nakai Is Different

Nakai Quantum's core team comes from Peking University's Cold Atom and Precision Measurement research group—which itself reveals something important: they are not academics who merely "publish papers," but engineers who understand "how to do physics-based engineering."

Fan Yaoyuan's eight-year career in cold atom research wasn't hidden in papers, but rather involved "leading the construction of China's first ultracold atom interferometric gyroscope" and "jointly constructing China's first ultracold atom Bloch oscillation gravimeter." These unfamiliar-sounding names translate in engineering terms to:

• Interferometric Gyroscope: Using quantum interference to measure rotation, with precision 1000 times higher than conventional gyroscopes, but requiring extremely precise optical alignment, temperature control, and magnetic field isolation.
• Bloch Oscillation Gravimeter: Using quantum oscillations to measure gravitational acceleration, with precision to detect microgram-level changes.

Both require this combined skill set: 1. Deep quantum physics intuition (how to design pulse sequences) 2. Precision optical engineering (laser alignment, frequency locking) 3. Electronic circuit design (nanosecond-level timing control) 4. Vacuum system management (ultracold atoms require extremely high vacuum) 5. Software and control systems (integrating all of the above into an automated system)

This skill combination is extremely rare in academia. Most professors excel either in physics design or circuits, rarely both. But Fan Yaoyuan did his PhD in the School of Electronics Engineering, meaning his training itself was a physics-plus-engineering hybrid.

Because of this, Nakai Quantum's "full-stack product matrix" (quantum computing systems, cold/ultracold atom experimental systems, critical subsystems and modular control circuits) wasn't patchworked together afterward, but designed as an "engineering system" from the start. This enables them to have "million-yuan market orders" just three months after founding—because they're not doing "theoretical verification," but rather building "deliverable, maintainable, upgradeable" products.

The Business Logic of Death Valley

Why is Death Valley so hard to cross? On the surface it's a technical problem, but at its core it's an organizational structure and incentive mechanism problem.

Academic Incentives: Publishing in top journals, securing research funding, building scholarly reputation. The optimal strategy is pursuing "novelty" and "theoretical elegance," even if engineering implementation is crude.

Engineering Incentives: Reducing costs, improving reliability, simplifying maintenance. The optimal strategy is pursuing "stability, reproducibility, batch-scalability," even if it means sacrificing some theoretical perfection.

These two incentive systems are nearly opposite. One pursues "breakthrough innovation," the other pursues "engineering excellence."

The traditional Silicon Valley path is: Scientists make discoveries at universities → found a spinoff company → raise funding to build an engineering team → hire experienced operating executives. The problem is this process typically takes 5-10 years and requires "extraordinarily patient capital" for continuous infusions. Moreover, many scientists psychologically resist "simplified engineering solutions"—because it means abandoning some academic elegance.

Nakai's innovation is: From the start, there was no separation between "scientist" and "engineer." Fan Yaoyuan is both. This means—

1. Engineering decisions need no translation: No communication barriers between academic and engineering personnel 2. Cost sensitivity is internalized: Every physics design decision considers engineering implementation difficulty 3. Rapid iteration is possible: No need to wait for the next funding round to hire engineers; the team itself understands engineering

Hillhouse's investment in Nakai is essentially betting on "a quantum team that's already crossed halfway through Death Valley," not "an academic startup with papers but no engineering capability." This explains why Hillhouse was willing to invest tens of millions into a three-month-old company.

The Pattern Behind the Phenomenon

This is not merely a quantum computing story. The same pattern is repeating across "frontier technology" fields like synthetic biology, neural chips, high-temperature superconductivity, and nuclear fusion:

• Ginkgo Bioworks (synthetic biology): Founder comes from MIT's synthetic biology lab, but personally understands fermentation engineering
• Paradromics (neural chips): Founder is both a neuroscientist and has Silicon Valley chip design background
• Commonwealth Fusion Systems (fusion energy): Chief scientist is an MIT plasma physics professor, but the team mixes industrial energy and manufacturing experts

The common thread: Their founders or core team members have themselves experienced the complete journey "from paper to product," rather than having purely academic backgrounds.

This raises a crucial question for China's tech sector: Are we forming a new "tech talent ecosystem"? One that can simultaneously accommodate "the pursuit of scientific breakthroughs" and "the constraints of engineering feasibility" within its thinking framework and organizational model?

Nakai Quantum's successful funding and Hillhouse's investment decision are telling us: such talent and such companies are now highly sought after by markets and capital. Because they represent not "scientific progress" itself, but the channel through which scientific progress converts into wealth and social value.

Conclusion

Fan Yaoyuan was born in 1998 and completed his funding round at age 28 in 2026. He proved over eight years that: if a person understands both the frontier of science and the constraints of engineering, Death Valley can be crossed by one person, one small team. No need to wait a decade, no need to go through multiple financing rounds and restructuring, and no need to bring in outside engineering teams.

This offers China's tech entrepreneurship a two-layered lesson:

First layer (short-term): Quantum computing, chips, biotech manufacturing and other frontier fields are shifting from "paper competitions" to "engineering competitions." Entrepreneurs with both academic strength and engineering mindset will be the winners.

Second layer (long-term): Can China's higher education and research system systematically cultivate "science-engineering hybrid" talent? If yes, we would have structural advantages in commercializing frontier technology. If not, no matter how many papers we produce, we're merely providing inspiration for American Silicon Valley.