This monograph establishes a rigorous thermodynamic, computational, and fiduciary critique of extraterrestrial (lunar and orbital) classical AI data center initiatives (such as Project Suncatcher) in contrast to terrestrial Fault-Tolerant Quantum Computing (FTQC) anchored by Google's 105-qubit Willow superconducting processor. While classical AI scaling confronts severe terrestrial power grid bottlenecks, relocating high-TDP classical accelerators (TPUs/GPUs) into vacuum environments violates fundamental radiative heat transfer economics governed by the Stefan-Boltzmann law (Prad = ε σ A T⁴), alongside prohibitive launch mass penalties, high-G mechanical stress, and cosmic-ray Single-Event Upsets (SEUs). Conversely, Willow demonstrates exponential below-threshold error suppression (Λ = 2.14 ± 0.02) across 3× 3, 5× 5, and 7× 7 surface code lattices, achieving in under five minutes random circuit sampling (RCS) benchmarks requiring 10²⁵ years on classical exascale supercomputers, supplemented by verifiable 13,000× Quantum Echoes speedups and $99.99%$ magic state cultivation fidelity. By coupling Willow's cryogenic topological scaling with neural syndrome decoders (AlphaQubit) and deterministic cryptographic verification over the 64-bit Goldilocks prime field (Fₚ, p = 2⁶⁴ - 2³² + 1) under QFS-zkVM and PHOENIX_ROUTER Human-in-Command (HIC) interlocks, full-spectrum breakthroughs in de novo molecular drug discovery, room-temperature superconductor catalysis, and post-LLM quantum AI can be achieved on Earth at a fraction of the capital expenditure. 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Yoko(洋子) Hasebe(長谷部) (2026) studied this question.
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