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Many mathematical models of evolution assume that all individuals experience the same environment. Here, we study the Moran process in heterogeneous environments. The population is of finite size with two competing types, which are exposed…

Populations and Evolution · Quantitative Biology 2018-12-19 Kamran Kaveh , Alex McAvoy , Martin A. Nowak

Motivated by the question of the impact of selective advantage in populations with skewed reproduction mechanims, we study a Moran model with selection. We assume that there are two types of individuals, where the reproductive success of…

Probability · Mathematics 2024-01-08 Adrián González Casanova , Noemi Kurt , José Luis Pérez

We study diffusion-type equations supported on structures that are randomly varying in time. After settling the issue of well-posedness, we focus on the asymptotic behavior of solutions: our main result gives sufficient conditions for…

Dynamical Systems · Mathematics 2020-04-28 Stefano Bonaccorsi , Francesca Cottini , Delio Mugnolo

We consider a diffusion on a bounded domain, assuming that the system is irreducible inside the domain and that the diffusion has varying degree of degeneracy on the domain's boundary. The long-term statistical properties of typical…

Probability · Mathematics 2025-08-29 Yuri Bakhtin , Renaud Raquépas , Lai-Sang Young

We study the common ancestor type distribution in a $2$-type Moran model with population size $N$, mutation and selection, and in the deterministic limit regime arising in the former when $N$ tends to infinity, without any rescaling of…

Probability · Mathematics 2018-04-05 Fernando Cordero

We present a new class of evolution equations which govern the high-energy behavior of power-suppressed scattering amplitudes. The equations can be viewed as a renormalization group flow with respect to the relevant effective field theory…

High Energy Physics - Phenomenology · Physics 2025-10-10 Maximilian Delto , Alexander Penin , Lorenzo Tancredi

We study inductive bias in Transformers in the infinitely over-parameterized Gaussian process limit and argue transformers tend to be biased towards more permutation symmetric functions in sequence space. We show that the representation…

Machine Learning · Computer Science 2024-05-29 Itay Lavie , Guy Gur-Ari , Zohar Ringel

In nature, most microbial populations have complex spatial structures that can affect their evolution. Evolutionary graph theory predicts that some spatial structures modelled by placing individuals on the nodes of a graph affect the…

Populations and Evolution · Quantitative Biology 2024-12-30 Alia Abbara , Lisa Pagani , Celia García-Pareja , Anne-Florence Bitbol

One of the classical results of mathematical population genetics states that the frequency of a beneficial mutant's offspring, on its way to fixation in a large population, looks like a logistic curve. A logarithmic scaling (both in height…

Probability · Mathematics 2026-05-12 Florin Boenkost , Felix Hermann , András Tóbiás , Anton Wakolbinger

We study the number of occurrences of any fixed vincular permutation pattern. We show that this statistics on uniform random permutations is asymptotically normal and describe the speed of convergence. To prove this central limit theorem,…

Combinatorics · Mathematics 2023-06-22 Lisa Hofer

We derived a new speed limit in population dynamics, which is a fundamental limit on the evolutionary rate. By splitting the contributions of selection and mutation to the evolutionary rate, we obtained the new bound on the speed of…

Populations and Evolution · Quantitative Biology 2023-01-13 Masahiro Hoshino , Ryuna Nagayama , Kohei Yoshimura , Jumpei F. Yamagishi , Sosuke Ito

To understand the effect of assortative mating on the genetic evolution of a population, we consider a finite population in which each individual has a type, determined by a sequence of n diallelic loci. We assume that the population…

Probability · Mathematics 2023-11-30 Alison M. Etheridge , Sophie Lemaire

One of the most fundamental concepts of evolutionary dynamics is the "fixation" probability, i.e. the probability that a mutant spreads through the whole population. Most natural communities are geographically structured into habitats…

Populations and Evolution · Quantitative Biology 2013-05-01 Bahram Houchmandzadeh , Marcel Vallade

In this article, we consider limit theorems for some weighted type random sums (or discrete rough integrals). We introduce a general transfer principle from limit theorems for unweighted sums to limit theorems for weighted sums via rough…

Probability · Mathematics 2017-07-07 Yanghui Liu , Samy Tindel

We consider infinitely-wide multi-layer perceptrons (MLPs) which are limits of standard deep feed-forward neural networks. We assume that, for each layer, the weights of an MLP are initialized with i.i.d. samples from either a light-tailed…

Machine Learning · Statistics 2021-06-22 Paul Jung , Hoil Lee , Jiho Lee , Hongseok Yang

We prove a central limit theorem for network formation models with strategic interactions and homophilous agents. Since data often consists of observations on a single large network, we consider an asymptotic framework in which the network…

Econometrics · Economics 2026-03-11 Michael P. Leung , Hyungsik Roger Moon

We consider uniform random permutations in proper substitution-closed classes and study their limiting behavior in the sense of permutons. The limit depends on the generating series of the simple permutations in the class. Under a mild…

In this article, we study the extremal processes of branching Brownian motions conditioned on having an unusually large maximum. The limiting point measures form a one-parameter family and are the decoration point measures in the extremal…

Probability · Mathematics 2020-09-01 Julien Berestycki , Éric Brunet , Aser Cortines , Bastien Mallein

We prove limit theorems of an entirely new type for certain long memory regularly varying stationary infinitely divisible random processes. These theorems involve multiple phase transitions governed by how long the memory is. Apart from one…

Probability · Mathematics 2018-05-23 Gennady Samorodnitsky , Yizao Wang

Deep neural nets have caused a revolution in many classification tasks. A related ongoing revolution -- also theoretically not understood -- concerns their ability to serve as generative models for complicated types of data such as images…

Machine Learning · Computer Science 2021-04-20 Holden Lee , Rong Ge , Tengyu Ma , Andrej Risteski , Sanjeev Arora