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zeekay abf99d05fc papers: reorganize into per-paper dirs, add Antje Worring as co-author
Restructured from flat .tex/.pdf files into per-paper subdirectories.
Added Antje Worring as co-author on all papers.
Synced PDFs to pdfs/ for download site.
2026-04-18 21:50:07 -07:00

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\section{Conclusion}
\label{sec:conclusion}
Fast Probabilistic Consensus represents a significant advance in Byzantine fault-tolerant consensus protocols. By introducing adaptive thresholds through a sigmoid cooling function, FPC prevents metastability while achieving rapid convergence. The protocol's phase-shift dynamics enable smooth transition from exploration to exploitation, ensuring both safety and liveness properties.
With message complexity of $O(k \log n)$, FPC scales to global networks of 100,000+ nodes while maintaining sub-second finality. The protocol tolerates up to $f < n/3$ Byzantine nodes with 99.999\% safety probability using modest committee sizes of 20-30 validators.
The Zero-copy Application Protocol (ZAP) eliminates serialization overhead by replacing gRPC+Protobuf with a zero-allocation binary wire format, achieving 9.69M messages/second---a $14\times$ improvement that confirms consensus message processing is network-bound rather than CPU-bound at scale.
FPC's core safety, liveness, and BFT tolerance properties have been formally verified in Lean~4 with machine-checked proofs that trace directly to the Go implementation. The proofs establish that no two honest nodes can finalize conflicting values, that finalization is guaranteed under honest majority, and that decisions are irrevocable once made.
Integration with the Lux blockchain demonstrates FPC's practical applicability, where it serves as the ``wave'' layer in a physics-inspired consensus architecture. Extensive simulations validate theoretical predictions, showing consistent performance across varied network conditions and adversarial scenarios.
FPC's adaptive threshold mechanism offers a blueprint for next-generation consensus protocols that balance the trade-offs between safety, liveness, and performance in large-scale distributed systems.