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We report results of a restricted mathematical computation that may berelevant in various contexts, including the evolution of sexual reproduction.The computation is an iterative probabilistic replication of sets of realnumbers. Given a set of random values sampled from a certain interval, wereplicate it probabilistically by encoding it as its arithmetic mean and thensampling a random same-size set of real numbers using uniform distribution overthe same interval length around that mean. The encoded set and its code areconsidered the parent of the sampled one. We first sample a cohort of severalsuch sets around an initial code, and probabilistically replicate each setonce, creating a new same-size cohort, which we then subject to the sameprocess. In a bi-parental variant of the above mono-parental process, we use apair of codes rather than a single one for sampling a new set: each parentcontributes half of the elements of the child set. Neither variant depends onjudging properties as harmful, or on selection: all individuals are paired andreproduced. Comparing the two variants over many iterations, bi-parentalprocessing shows enhanced fidelity and consistency, where fidelity is definedas the mean of the distances between a cohort's codes and the initial code, andconsistency is the standard deviation of code values within a cohort. We do notattempt here to directly mimic natural reproduction, which includes copying andrecombination of DNA codes subject to mutations. Still, the result intuitivelyaligns with the idea that sexual reproduction in nature helps preserve, andperhaps even define, core traits of each species. The cause for the prevalence,in eukaryotic species, of sexual reproduction over asexual, despite increasedcomplexity and unpredictability, is subject to debate and diverse theories. Themathematical phenomenon reported here might be part of the answer.

Fidelity and Consistency in Iterative Probabilistic Set Replication: Comparing Bi-Parental and Mono-Parental Methods