JIJ Inc. is a Japan-based company focused on optimization technologies that span both classical and quantum computing. Its work centres on developing methods and tools for tackling complex optimization problems in areas such as logistics, manufacturing, energy, and finance, while adapting to the capabilities and limitations of today’s quantum hardware. Founded in 2018, the company has expanded to the UK, Germany, and the US, and is partnering with organizations such as the UK National Quantum Computing Centre (NQCC) to further its mission of applying optimization technologies to real-world problems.
Hiro Nakata is the Chief Operating Officer (COO) of JIJ and CEO of JIJ Europe. He also holds a concurrent role as Board Member of Japan’s quantum consortium Quantum STrategic industry Alliance for Revolution (Q-STAR), and supports Japan’s collaborations with the UK and European quantum ecosystems.
On the sidelines of LEAP East in Hong Kong, we spoke with Nakata on a wide range of topics spanning quantum optimization and Japan’s quantum industry. Below is the first part of the interview, focusing on JIJ’s work and the future of quantum optimization.
Quantum optimization: A case study from the telco industry
As industries grow in scale and complexity, organizations increasingly face the challenge of finding the best solution from a vast number of possible combinations. Collectively, these challenges fall within the field of mathematical optimization, which is used to solve problems such as assigning tasks efficiently or finding the best delivery routes. Yet, because many types of optimization problems become exponentially harder as they grow, today’s computational resources are hard-pressed to find solutions.
Quantum computing, however, may help address these computational limitations. Optimization — particularly a subfield known as combinatorial optimization, in which the variables are discrete — is widely regarded as one of the most promising near-term applications of quantum computing.
“Combinatorial optimization is already widely used in practical industries such as manufacturing, logistics, and energy,” said Nakata, adding that JIJ’s work with companies such as Toray, Toyota Motor Corporation, and SoftBank is already producing “tangible business impact.”
To illustrate this, Nakata cited a recently announced proof of concept (PoC) by JIJ and SoftBank, which used an Ising machine—a quantum-inspired optimisation technology—together with a specially developed mathematical model, to optimize mobile networks in selected areas of Tokyo.
“In our publicly announced work with SoftBank, we formulated base-station configuration as a combinatorial optimization problem under existing infrastructure constraints, and the published PoC results reported outcomes including an approximately 10% improvement in downlink speed,” explained Nakata.
In this example, SoftBank aimed to expand the coverage area of carrier aggregation (CA), a technology that enables high-speed, stable communication by simultaneously utilizing multiple frequency bands. This requires predefined associations between base stations, referred to as CA links. Within the coverage area, determining the optimal CA link configuration becomes exponentially more complex as the number of base stations increases. Using the optimization model and the Ising machine, a CA link configuration was generated and applied to 5G base stations operating in a specific area of Tokyo. The results showed that the CA coverage area expanded and the average downlink data speed improved by approximately 10%. In addition, both the CA utilization ratio (the proportion of connections utilizing CA) and the amount of data transmitted via secondary cells increased by up to 50%.
The next phase: Hybrid quantum-classical optimization
With quantum optimization already showing promising results, Nakata believes the next phase will focus on solving real-world applications using hybrid quantum-classical computing.
He said, “Quantum computing is now moving into the next stage of practical application. Over the next five years, I believe we will see more areas where quantum computers can demonstrate clear advantages. Hybrid optimization, combining classical and quantum computing, will gradually become an important standard for real-world industrial applications.”
This is already being demonstrated, said Nakata, in a recent PoC that JIJ conducted under the UK National Quantum Computing Centre’s (NQCC) SparQ programme, which ‘aims to support the pathway to quantum readiness by building knowledge and expertise in applications discovery, and developing the UK quantum computing user community’.
The PoC, conducted jointly with photonic quantum computer company ORCA Computing and oil giant BP, demonstrated a next-generation quantum-classical hybrid optimization workflow for the energy sector. Specifically, it benchmarked a quantum-classical hybrid approach for the Unit Commitment Problem, which refers to the large-scale optimization task of deciding when power generators should start up or shut down to meet power demand at minimal cost. In the tests, JIJ used a hybrid decomposition method to break down the overall optimization horizon into smaller, tractable subproblems, and then converted the subproblems into quantum circuits that were fed into ORCA’s photonic system. The resulting outputs were then recombined using a hybrid quantum–classical approach to produce a global optimization plan.
Nakata described the Unit Commitment Problem as “one of the most economically significant operational challenges in the power sector”, and commented that this case study “demonstrates that quantum optimization is beginning to move beyond one-off PoCs and into a realistic cycle of evaluation and improvement for industry-scale problems”.
He continued, “Over the next five years, I do not expect ‘quantum alone’ to suddenly replace existing systems. Instead, quantum optimization will progress step-by-step as part of a practical workflow that combines classical optimisation/HPC (High-Performance Computing), quantum-inspired methods, and quantum hardware where it adds measurable value.”
Challenges in scaling quantum optimization
Although there are early glimmers of quantum optimization’s potential in industry, the path from a successful POC to an enterprise-grade deployment is often far from straightforward. In Nakata’s view, there remain challenges and bottlenecks that must be overcome for quantum to be widely adopted.
The biggest barrier is not the algorithm alone, but ‘making it work in the field’ with reliability, integration, operability, and measurable business impact. In enterprise environments, constraints and exceptions are numerous, data quality is uneven, and solutions must satisfy reproducibility, explainability/auditability, integration with existing systems, and operational processes. Quantum computing is only one component—what is required is an end-to-end implementation architecture.
He added, “The key going forward is not only QPU (Quantum Processing Unit) performance, but also ‘implementation thickness’: (1) translating business challenges into solvable mathematical models, (2) incorporating data, constraints, and operational KPIs, and (3) integrating into existing IT and operating the workflow continuously.”
Growing beyond technology: Attracting the right talent
According to Nakata, one of the greatest challenges facing the quantum industry today is not only advancing the technology itself, but also building the talent needed to bring it into the real world. Success, he said, requires much more than deep academic or technical expertise.
Nakata explained, “One of the biggest challenges is building a highly diverse team and integrating it into one coherent business. Commercializing quantum technology requires expertise not only in a specific research field, but also in quantum algorithms, software development, classical optimization, mathematical modeling, and an understanding of hardware.”
He continued, “However, that alone is not enough. We also need project managers and delivery teams who can work directly with customers, sales teams to expand the business, communication and marketing capabilities, recruitment and finance functions, and people who can integrate the business globally. At the same time, local expertise in each country and region is also essential.”
Showing that the company is able to contribute to both research and commercialization, Nakata said, is crucial to attracting and retaining the right talent.
He said, “Going forward, I believe the most important strategy for attracting and retaining top talent is to provide an environment where people can challenge themselves in both research and commercialization
In our hiring, we clearly communicate not only the opportunity to work on cutting-edge research, but also the mission of implementing quantum technology in society together with companies around the world. I feel this message resonates strongly with many candidates.
While it is often said that the quantum industry struggles to attract talent, JIJ’s hiring experience indicates that there is no shortage of people eager to join the field.
“Recently, we received more than 330 applications for three internship positions. This shows that there are many people who want not only to publish research papers, but also to create real impact in industry and society,” he says. “In competitive talent markets, compensation alone is not enough—mission and real-world impact matter. People want to work on challenges that go beyond prototypes and change real decision-making in industry and society,” Nakata explained.
However, he noted that more needs to be done particularly in improving talent mobility, using Japan as an example.
“In Japan, it is also important to increase mobility across academia, startups, large enterprises, and international projects. The more we build an environment where mission-driven talent can gain cross-border experience, the stronger the overall ecosystem becomes,” he said.
The role of government in supporting quantum startups
In June, Japan’s Takaichi administration announced a growth strategy targeting ¥370 trillion (app. US$2.3 trillion) in combined public and private sector investment into 17 key strategic areas, including quantum, by the year 2040. Of this, about ¥13.2 trillion (app. USD 84.4 billion) is expected to go to quantum — ¥10.3 trillion (app. USD 61.42 billion) for quantum computing, ¥1.5 trillion (app. USD 9.59 billion) for quantum communications and networking, and ¥1.4 trillion (USD 8.95 billion) for quantum sensing.
JIJ, which has already participated in multiple public projects in hybrid optimisation and middleware, aims to “help ensure that this national investment translates not only into research outputs, but into deployable industrial systems.”
Said Nakata, “The scale of investment (e.g., ¥10.3T in quantum computing) can only be realised if it is supported not just by hardware development, but also by software, middleware, and practical use-case creation that make quantum technologies usable in real operations. Among the 16 projects publicly announced last year, two were middleware-related projects, and JIJ is participating in both of them. In particular, the fact that we secured both joint projects with AIST (the National Institute of Advanced Industrial Science and Technology) , which is driving the industrialization of quantum computing in Japan, indicates that JIJ is becoming a central player in software and middleware within Japan’s quantum ecosystem.”
Looking ahead, argued Nakata, sustained progress will depend on creating an ecosystem where innovation can successfully reach the market. While Japan has made significant investments in quantum research, there is still an opportunity for the government to strengthen support for the commercialization journey.
He concluded, “At the same time, there is still room for improvement in government support. The industrialization and commercialization of quantum technology cannot be completed by government agencies or public research institutions alone. In areas closer to customer development, productization, real-world operation, and global expansion, private companies need to be utilized more actively.”
