Unlike semiconductors, where the U.S. has a substantial lead, quantum is a new field where the competitive moat is small. This creates a thin margin for error in industrial policy and R&D strategy, demanding a higher degree of precision from the outset.
Similar to biotech, startups are the primary drivers of disruptive innovation in quantum. The 'neutral atoms' modality, once dismissed as science fiction, was championed by startups and is now a leading contender, forcing incumbents like Google to invest heavily to hedge against their established approaches.
The quantum industry's structure, with its various modalities (like drug types) and long, high-risk development cycles, mirrors biotech. Policies should adopt similar models, like advanced market commitments and support for phase-based trials, to accelerate commercialization.
The first quantum computer capable of breaking encryption will not enable mass surveillance. It will be highly inefficient, potentially taking months to break a single code. This forces adversaries to choose targets with extreme care, focusing on high-value assets like nuclear codes rather than decrypting everything at once.
Unlike AI, where software learnings diffuse rapidly, quantum progress is a 'hardware sport.' Tacit knowledge is deeply embedded in physical systems, making iteration times longer and knowledge transfer more difficult. This creates more defensible moats for companies and nations that achieve breakthroughs.
Classical computers fail at modeling molecular systems because complexity grows exponentially. Richard Feynman's insight was to build a computer that is itself quantum mechanical. This allows it to handle exponential complexity efficiently, using only 186 qubits for a task requiring more transistors than atoms in the universe for a classical machine.
The key inflection point for quantum was not a 'ChatGPT moment' but a foundational shift. Google's 2023 paper on error correction proved systems could become more stable as qubits are added, changing the question from 'if' to 'when' for useful quantum computers, similar to the 2017 paper that enabled LLMs.
An often overlooked indicator of national competitiveness in quantum is 'cycle time'—the duration from idea to testable prototype. While the US excels at research, long fabrication lead times (e.g., 18 months for a photonic circuit) create a major disadvantage compared to regions where it takes weeks, hindering the rate of innovation.
The US is missing a critical piece of infrastructure common in other leading tech ecosystems: an institution like Belgium's IMEC. These public-private entities focus on the pre-competitive phase between academic research and commercial development, de-risking technology and shortening cycle times—a crucial gap in the US quantum strategy.