Serendipity Capital's Rob Jesudason discusses how investors and governments can evaluate quantum computing, sensing, and communications companies as the field moves from laboratory science to large-scale engineering and operational execution
As quantum technologies transition from laboratory prototypes to engineered systems, the challenge of evaluating quantum computing, sensing, and communications companies has become increasingly complex. In a recent discussion, Rob Jesudason, CEO and founder of Serendipity Capital, outlined the practical and technical considerations that now shape investment and policy decisions in the quantum sector. Serendipity Capital, a $1.3 billion permanent capital vehicle, has invested in companies such as Quantinuum, Monarch Quantum, Delta g, and QuantX, each pursuing different quantum hardware and application modalities.
Evaluating Competing Quantum Modalities
One of the central difficulties for investors and policymakers is comparing quantum hardware platforms-such as superconducting qubits, trapped ions, neutral atoms, and photonic systems-when each approach is championed by its own technical community. Jesudason emphasized that no single expert or group can provide a definitive assessment of which modality will ultimately prove most scalable or commercially viable. Instead, he advocates for triangulating across multiple independent technical perspectives, recognizing that each platform's proponents are often deeply invested in their own approach. This diversity of opinion reflects the current state of the field, where no hardware platform has yet demonstrated clear, reproducible superiority across all relevant benchmarks.
From Laboratory Science to Engineering Execution
The quantum industry's maturation is marked by a shift from physics-driven research to the demands of engineering scale and operational management. As companies move beyond proof-of-principle demonstrations, the ability to manufacture, calibrate, and maintain large numbers of high-fidelity qubits becomes a decisive factor. This transition requires teams with expertise in systems engineering, supply chain management, and large-scale device integration, in addition to quantum physics. The need for operational talent is now as acute as the need for scientific innovation, and the industry's bottlenecks increasingly reflect engineering and manufacturing constraints rather than fundamental physics.
Government and Policy Roles
Jesudason argues that governments should avoid acting as the first source of capital for quantum startups, instead partnering with private investors once technical feasibility and commercial potential have been partially established. He suggests that public funding is most effective when it validates and scales promising technologies, rather than attempting to pick winners at the earliest stage. For countries without the resources to build a full-stack quantum hardware ecosystem-such as Australia, Canada, or Singapore-he recommends focusing on rapid integration and deployment of leading technologies developed elsewhere, rather than attempting to compete directly in hardware innovation.
Public Markets and Investment Challenges
The complexity of quantum hardware and the diversity of technical approaches present significant challenges for both institutional and retail investors. Public market vehicles such as SPACs and IPOs have provided some access to quantum companies, but the lack of standardized benchmarks and the long timelines to commercial utility make due diligence difficult. Investors must assess not only the underlying physics but also the engineering roadmap, manufacturing scalability, and the ability to attract and retain multidisciplinary talent. As the field matures, the distinction between laboratory achievement and operational reliability will become increasingly important for investment decisions.
Recent industry partnerships, such as the collaboration between Quantinuum and Quanta Computer to develop modular trapped-ion quantum computing hardware, illustrate the sector's movement toward scalable, manufacturable systems. These efforts highlight the need for robust engineering and supply chain integration, as discussed in coverage of modular trapped-ion hardware development.
As quantum companies seek to demonstrate practical utility, the industry's progress will depend on transparent reporting of device performance, reproducible benchmarks, and realistic assessments of engineering limitations. The balance between scientific innovation and operational execution will define which platforms and companies achieve lasting impact as quantum technologies move closer to deployment.
Understanding the distinction between physical and logical qubits is essential for evaluating quantum hardware claims. A physical qubit is a single controllable quantum system, such as a superconducting circuit or trapped ion, while a logical qubit encodes information redundantly across many physical qubits to detect and correct errors. Achieving fault-tolerant quantum computation requires not only high-fidelity physical qubits but also robust error correction, which imposes significant overhead. The number of physical qubits required per logical qubit depends on the error rates and the chosen error-correcting code. As a result, claims of large-scale quantum computation must be scrutinized for both the quality and quantity of physical qubits, as well as the demonstrated ability to implement error correction in hardware.
