Certain physics-based technologies (quantum computing, fusion energy, advanced materials, brain–computer interfaces) have remained “five years away” for decades. This paper argues that this perpetual horizon is not a forecasting failure but the temporal signature of Perpetual Five-Year Technologies (PFYTs): technologies of atoms, not bits, whose technical object and enabling ecosystem must co-develop. Drawing on philosophy of technology and sociology of scientific practice, and grounded in quantitative analysis of cross-platform performance data and high-impact research across hardware architectures, the paper shows that PFYT temporality is endogenous, produced by concretization dynamics and recursive constraint discovery rather than by market failures or insufficient funding. Quantum computing provides the paradigmatic case. Treating the quantum processor as a technical individual in active individuation explains why multiple computing paradigms persist and why each breakthrough resets rather than collapses the horizon. The convergence of machine learning and quantum hardware into pipelines for drug and materials discovery shows how Physical AI reshapes PFYT dynamics, compressing some cycles while introducing new forms of co-individuation between intelligence and matter. The framework generates diagnostics for physics-based frontiers where technical objects and milieus co-produce developmental time.
Quantum computers are moving from research laboratories to industrial machines accessible via the cloud and integrated into high-performance computing facilities. However, translating theoretical quantum protocols into hardware experiments remains a major bottleneck, requiring expertise across protocol design, compilation, simulation, and cloud execution. Here, we introduce an agentic workflow that automates this pipeline on neutral-atom quantum processors (here two Pasqal QPUs available on the cloud) while keeping the researcher in the loop for critical validation. In three case studies from many-body physics and optimization, the agent went from published paper or patent to a QPU campaign run overnight. In particular, human intervention was crucial to ensure scientific validity: the agent selected an inadequate observable in one experiment and constructed a plausible but incorrect hardware diagnosis in another, with both failures detected only through domain-expert review. Finally, we use a second agent to classify a corpus of 633 Rydberg-array arXiv papers and show that nearly half are implementable on present-day QPUs while identifying specific hardware upgrades needed for the rest. Together, these results demonstrate that agentic workflows provide a practical bridge between theoretical ideas and physical hardware, opening quantum experimentation to a much broader scientific community.
Constantin Dalyac, A. Dauphin, L. Henriet et al.· 0 citations
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