标题： 选民投票率支配关键选举统计 显示英文标题

标题： Voter Turnouts Govern Key Electoral Statistics

摘要： 选举是民主社会的基石，通常由于在不同层次上塑造它们的复杂互动而被视为不可预测的。 在这项工作中，我们表明选民投票率包含关键信息，可以用来准确预测几个重要的选举统计数据。 使用最近提出的随机投票模型，我们分析推导出获胜者、第二名和胜利差距的缩放投票分布，并证明它们与投票率分布有很强的相关性。 通过分析印度的选举数据——跨越多个十年和选举规模——我们在所有尺度上都实证验证了这些预测，从大的议会选区到投票站。 此外，我们发现了一个令人惊讶的尺度不变行为，即缩放胜利差距的分布，这是印度选举的一个特征性标志。 最后，我们展示了缩放胜利差距与投票率比率的分布具有强大的普遍性。 显示英文摘要

摘要： Elections, the cornerstone of democratic societies, are usually regarded as unpredictable due to the complex interactions that shape them at different levels. In this work, we show that voter turnouts contain crucial information that can be leveraged to predict several key electoral statistics with remarkable accuracy. Using the recently proposed random voting model, we analytically derive the scaled distributions of votes secured by winners, runner-ups, and margins of victory, and demonstrating their strong correlation with turnout distributions. By analyzing Indian election data -- spanning multiple decades and electoral scales -- we validate these predictions empirically across all scales, from large parliamentary constituencies to polling booths. Further, we uncover a surprising scale-invariant behavior in the distributions of scaled margins of victory, a characteristic signature of Indian elections. Finally, we demonstrate a robust universality in the distribution of the scaled margin-to-turnout ratios.