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Explore how extremal statistical events govern the inference of population growth rates in exponentially proliferating microbial populations through this 32-minute conference talk. Discover why the population doubling rate differs from the average single-cell doubling time due to single-cell level variability, and learn why generation time distributions from single lineages are generally insufficient for determining population growth rates. Examine two methods that connect population growth rates to single lineage statistics, both rooted in large deviation principles that characterize exponentially proliferating populations. Understand the counterintuitive finding that the number of lineages required for accurate growth rate estimation depends exponentially on lineage duration, resulting in nonmonotonic convergence patterns verified through both synthetic and experimental datasets. Investigate the fascinating connection between this biological inference problem and phase transitions in the Random Energy Model, an exactly solvable disordered system where partition functions at low temperatures are dominated by rare, anomalously deep energy traps.
