Fuxi Quantum is developing algorithms and software to bring quantum computing closer to practical applications in materials science, energy and drug discovery.
When will quantum computers actually help companies develop new materials, better batteries or new drugs? It is a question the industry has debated for years — and one a Shanghai startup founded just six months ago is trying to answer.
Founded in April 2026 by Zhao Qi, an assistant professor at the University of Hong Kong, Fuxi Quantum Technology has raised three funding rounds in three months. The company focuses on quantum algorithms and applications rather than hardware.
Battery giant CATL (3750.HK) (300750.SZ) has led two consecutive rounds, making Fuxi Quantum the only quantum computing company in its sector investment portfolio. The backing reflects growing interest in software that could make quantum computers useful before hardware advances far enough to overcome today’s limitations. The latest fundraising round attracted investors including Huakong Fund, SMIC Capital, TCL Ventures, Pudong Venture Capital and Koal Software. Existing investor Muhua Sci-Tech Innovation Fund, a venture capital fund affiliated with the Tsinghua University alumni network, increased its investment in all three rounds.
Algorithms not hardware
Unlike many startups focused on quantum chips and hardware, Fuxi Quantum is attacking the problem from quantum algorithms and industrial applications, building a platform aimed at industrial R&D. As hardware advances, the key commercialization question is how algorithmic innovation can lower resource requirements, improve efficiency and turn quantum power into practical capability.
That choice reflects founder Zhao Qi’s long record in quantum simulation algorithms. Zhao is an assistant professor at the University of Hong Kong, holds a bachelor’s degree and PhD from Tsinghua University, has conducted researched at the University of Science and Technology of China and the University of Maryland, and was named to the MIT Technology Review’s Asia-Pacific “35 Innovators Under 35” list in 2024. His work has focused on lowering the resource barriers to quantum computing.
In 2025, Zhao was first author of a quantum simulation study published in Nature Physics and selected for the journal cover. It showed that under certain conditions, quantum entanglement—which normally makes classical simulation harder—can instead reduce the error and resource requirements of quantum simulation algorithms. His team has since published further work in Physical Review Letters and Science Advances on simulation errors, stability and scalability — the core challenges on the road to practical use.
Together, the research addresses three challenges facing practical quantum computing: efficiency, reliability and scalability.
CATL backing helps identify industrial use cases
Zhao founded Fuxi Quantum to bring his research into commercial applications. He says access to industrial partners is as important as funding because companies must understand real research problems to identify where quantum computing offers an advantage.
“I have accumulated substantial expertise in quantum simulation and quantum algorithms,” Zhao said, emphasizing that his background is in computing rather than chemistry or battery technology.
Working with CATL has helped the startup explore industrial research needs, particularly in battery materials. Its ambitions extend to energy, biomedicine, finance and information security.
The company targets three customer groups: large enterprises like CATL, for customized algorithms and private deployment; researchers and enterprise clients, for a quantum application computing platform; and hardware makers, whom it helps use existing devices more efficiently. Zhao said the cloud platform has taken initial shape, with ease of use as its core feature — customers won’t need to write quantum circuits themselves.
Fuxi Quantum also plans to introduce an AI assistant that translates natural-language questions into computing tasks. It would clarify research objectives and parameters through dialogue, prepare a proposed solution and submit it for execution after user approval.
The approach reflects the company’s central proposition: better algorithms and software could make existing quantum hardware more useful without requiring a major leap in hardware performance.
What can quantum computing offer in the age of AI?
As AI enters materials science, chemistry and drug discovery, a key question is what additional value can quantum computing deliver?
AI systems can predict material properties, screen candidate molecules and help solve complex research problems using classical computing resources and patterns learned from existing data. Zhao argues that AI and quantum computing are more likely to complement each other than compete directly.
Classical computers struggle to simulate certain complex quantum systems, while a lack of high-quality data can limit AI predictions. Quantum computers could eventually simulate the behavior of molecules, atoms and electrons more directly, tackling problems that challenge classical methods and potentially generating new scientific data for AI.
“You could think of one as making a guess, and the other as generating or solving the answer itself,” Zhao said.
Fuxi Quantum is pursuing two related research directions. One uses AI to explore quantum algorithm designs and find ways to reduce the number of qubits and computing steps required. The other combines quantum computing and AI to address scientific problems in materials, energy and medicine.
International research is beginning to demonstrate the potential of AI-assisted quantum development. In October, Anthropic announced research conducted with Harvard physicists Mikhail Lukin and Susanne Yelin in which its Claude large language model proposed and refined more resource-efficient quantum circuit designs. Across eight test tasks covering chemistry, optimization and quantum simulation, seven required fewer Toffoli gates — operations used in quantum circuits — and fewer qubits, the basic units of quantum information.
For Fuxi Quantum, such work supports the idea that AI-assisted algorithm development could reduce resource requirements and bring some applications within reach sooner.
Nevertheless, Zhao says quantum computing remains in a transitional phase between laboratory experiments and engineering applications. Hardware technologies are advancing at different rates, and better algorithms are needed to make effective use of available machines.
“If you suddenly gave me a 50-qubit or 100-qubit quantum computer today, I wouldn’t necessarily know how to use it most efficiently,” he said.
China’s algorithm and software gap
Zhao sees materials science and drug discovery as particularly promising because many problems involve atomic and molecular behavior, making them natural candidates for quantum simulation. But not every problem is suitable: the key is establishing whether quantum methods can outperform classical computing.
He also sees an imbalance in China’s quantum computing development. Hardware achievements, including the Zuchongzhi quantum processor and Jiuzhang photonic quantum computer, have attracted international attention, but quantum algorithms and software remain comparatively underdeveloped.
More researchers with international experience have returned to China in recent years, strengthening the field. Even so, relatively few teams have developed long-term expertise in quantum simulation algorithms.
Some in industry underestimate the difficulty, Zhao said, assuming that quantum algorithms are straightforward to develop. In his view, efficient algorithms require deep theoretical research and cannot simply be devised after the hardware has been built.
He hopes eventually to develop a new quantum algorithm comparable in significance to Shor’s algorithm, which demonstrated that quantum computers could potentially solve certain mathematical problems exponentially faster than classical computers.
His ambition is for Fuxi Quantum to become an internationally recognized quantum algorithm company, combining original research with practical computing solutions. He acknowledges that Google and IBM have substantial head starts.
For now, the priority is to work with CATL and quantum hardware companies to demonstrate tangible benefits in real research tasks.
“People need to see that quantum computing can genuinely help, and that this new form of computing power has real value,” Zhao said.
Source:
DeepTech
