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51 lines
2.2 KiB
TeX
51 lines
2.2 KiB
TeX
\section{Safety and Liveness}
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\label{sec:safety}
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\begin{theorem}[Nebula Safety]
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\label{thm:nebula-safety}
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Under the Nebula protocol with $f < n/3$ Byzantine validators, the probability of
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conflicting finalizations is bounded by:
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\[
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\Pr[\text{safety violation}] \leq \left(\frac{q_0}{q_1}\right)^{\beta} + n \cdot e^{-\Omega(\xi k)}
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\]
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where the second term accounts for incomplete information propagation in sparse networks.
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\end{theorem}
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\begin{proof}
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The first term is the standard Wave safety bound: with threshold $\beta$, the probability
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of the minority color overtaking the majority is $(q_0/q_1)^\beta$.
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The second term arises because in sparse networks, local neighborhoods may temporarily
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disagree with the global majority. If validator $v$'s neighborhood has a local majority
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for color 0 while the global majority is color 1, $v$ might incorrectly finalize color 0.
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The probability of this local disagreement persisting for $\beta$ rounds is bounded by
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the probability that bridge information fails to correct the local bias. Each bridge
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sample of size $k_b$ carries global information with accuracy $O(\sqrt{1/k_b})$. Over
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$\beta$ rounds, the cumulative bridge information has accuracy $O(\sqrt{\beta / k_b}) = O(\sqrt{1/\xi k})$.
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For this local bias to persist despite bridge information, the bridge samples must
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all fail to reflect the global majority, with probability $\leq e^{-\Omega(\xi k)}$ per
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round and $\leq e^{-\Omega(\xi k \beta)}$ over $\beta$ rounds.
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A union bound over $n$ validators gives the stated result.
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\end{proof}
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\begin{lemma}[Nebula Liveness]
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\label{lem:nebula-liveness}
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After GST, every valid transaction is finalized within $O(\log n / \xi + \beta)$ rounds.
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\end{lemma}
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\begin{proof}
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After GST, messages are delivered within $\Delta$. Bridge validators propagate
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information across the network in $O(1/\xi)$ hops per round. The global convergence
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takes $O(\log n / \xi)$ rounds (Theorem~\ref{thm:nebula-convergence}), and the
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confidence counter reaches $\beta$ in an additional $O(\beta)$ rounds. Total:
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$O(\log n / \xi + \beta)$.
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\end{proof}
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%% -----------------------------------------------------------------------
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%% 6. PARTITION RECOVERY
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%% -----------------------------------------------------------------------
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