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arXiv · 2608.05461

Quantifying Bitcoin Network Resilience Through Critical Scenario Discovery: A Dual-Layer Framework for Discovering Contentious Fork Conditions in Decentralized Consensus

Peter Foytik·Sachin Shetty·Ross Gore·Eranga Bandara
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Abstract

Bitcoin's consensus depends not only on protocol rules but on the emergent behavior of a heterogeneous network of nodes with divergent economic stakes. Whether a contentious soft fork resolves cleanly or fractures into a persistent chain split is difficult to predict analytically but can be explored through controlled experimentation. This paper applies Scenario Discovery, an ensemble-simulation methodology using the Patient Rule Induction Method (PRIM), to identify the configuration regions that produce contentious fork outcomes. Using Warnet to run real bitcoind nodes across 1,330 valid scenarios spanning economic weight, mining-pool commitment, pool ideology, hashrate, and difficulty-retarget regime, we identify the parameter thresholds separating clean resolution from contested split. We show that economic weight distribution across a partition, not hashrate majority, is the primary determinant of resolution under Bitcoin's operational retarget interval and moderate price divergence. Three findings follow: an economic-support floor (0.45-0.50) and override ceiling (0.78-0.82) bound the contested space, with an Economic Self-Sustaining Point (0.74) between them; a pool-commitment "flip-point" (0.214 of committed hashrate) at which committing the largest pool to the upgrading chain paradoxically reverses the outcome; and outcomes resolve on two independent layers, hashrate and economic adoption, governed by different parameters. Individual user nodes show no detectable influence on fork outcomes under the modeled economic weightings. We close with three monitoring questions, answerable from public data, that translate these thresholds into operational guidance.

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Peter Foytik, Sachin Shetty, Ross Gore, Eranga Bandara. 2026-08-05. Quantifying Bitcoin Network Resilience Through Critical Scenario Discovery: A Dual-Layer Framework for Discovering Contentious Fork Conditions in Decentralized Consensus. https://arxiv.org/abs/2608.05461

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