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We consider a branching population where individuals live and reproduce independently. Their lifetimes are i.i.d. and they give birth at a constant rate b. The genealogical tree spanned by this process is called a splitting tree, and the…

Probability · Mathematics 2016-09-05 Nicolas Champagnat , Benoît Henry

Assume that individuals alive at time $t$ in some population can be ranked in such a way that the coalescence times between consecutive individuals are i.i.d. The ranked sequence of these branches is called a coalescent point process. We…

Probability · Mathematics 2009-02-09 Amaury Lambert

A density-dependent branching process is a particle system in which individuals reproduce independently, but in a way that depends on the current population size. This feature can model a wide range of ecological interactions at the cost of…

Probability · Mathematics 2026-01-23 Mathilde André , Félix Foutel-Rodier , Emmanuel Schertzer

Consider a population where individuals give birth at constant rate during their lifetimes to i.i.d. copies of themselves. Individuals bear clonally inherited types, but (neutral) mutations may happen at the birth events. The smallest…

Probability · Mathematics 2013-05-29 Cécile Delaporte

Many imaging techniques for biological systems -- like fixation of cells coupled with fluorescence microscopy -- provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics…

Subcellular Processes · Quantitative Biology 2024-05-15 Christopher E. Miles , Scott A. McKinley , Fangyuan Ding , Richard B. Lehoucq

We demonstrate an approach to solving the coagulation equation that involves using a finite number of moments of the particle size distribution. This approach is particularly useful when only general properties of the distribution, and…

Astrophysics · Physics 2009-11-13 Paul R. Estrada , Jeffrey N. Cuzzi

We consider the "moment vanishing problem" for a general class of piecewise-analytic functions which satisfy on each continuity interval a linear ODE with polynomial coefficients. This problem, which essentially asks how many zero first…

Classical Analysis and ODEs · Mathematics 2013-02-06 Dmitry Batenkov , Gal Binyamini

We consider the problem of exact reconstruction of univariate functions with jump discontinuities at unknown positions from their moments. These functions are assumed to satisfy an a priori unknown linear homogeneous differential equation…

Classical Analysis and ODEs · Mathematics 2009-09-18 Dmitry Batenkov

The coalescent is a stochastic process representing ancestral lineages in a population undergoing neutral genetic drift. Originally defined for a well-mixed population, the coalescent has been adapted in various ways to accommodate spatial,…

Populations and Evolution · Quantitative Biology 2024-07-02 Benjamin Allen , Alex McAvoy

We consider the rate of piecewise constant approximation to a locally stationary process $X(t),t\in [0,1]$, having a variable smoothness index $\alpha(t)$. Assuming that $\alpha(\cdot)$ attains its unique minimum at zero and satisfies the…

Probability · Mathematics 2015-11-19 Enkelejd Hashorva , Mikhail Lifshits , Oleg Seleznjev

Power moments, modified moments, and optimized moments are powerful tools for solving microscopic models of macroscopic systems; however the expansion of the density of states as a continued fraction does not converge to the macroscopic…

Materials Science · Physics 2009-11-11 Roger Haydock , C. M. M. Nex

We define a doubly infinite, monotone labeling of Bienayme-Galton-Watson (BGW) genealogies. The genealogy of the current generation backwards in time is uniquely determined by the coalescent point process $(A_i; i\ge 1)$, where $A_i$ is the…

Probability · Mathematics 2015-03-17 Amaury Lambert , Lea Popovic

The moment problem in probability theory asks for criteria for when there exists a unique measure with a given tuple of moments. We study a variant of this problem for random objects in a category, where a moment is given by the average…

Probability · Mathematics 2024-05-10 Will Sawin , Melanie Matchett Wood

We study lower bounds for the problem of approximating a one dimensional distribution given (noisy) measurements of its moments. We show that there are distributions on $[-1,1]$ that cannot be approximated to accuracy $\epsilon$ in…

Data Structures and Algorithms · Computer Science 2023-07-04 Yujia Jin , Christopher Musco , Aaron Sidford , Apoorv Vikram Singh

The problem of recovering a moment-determinate multivariate function $f$ via its moment sequence is studied. Under mild conditions on $f$, the point-wise and $L_1$-rates of convergence for the proposed constructions are established. The…

Statistics Theory · Mathematics 2023-12-08 Robert Mnatsakanov , Rafik Aramyan , Farhad Jafari

In population genetics, diffusions on the unit interval are often used to model the frequency path of an allele. In this setting we derive approximations for fixation probabilities, expected hitting times and the expected…

Probability · Mathematics 2018-09-18 Peter Pfaffelhuber , Anton Wakolbinger

We register a random sequence which has the following properties: it has three segments being the homogeneous Markov processes. Each segment has his own one step transition probability law and the length of the segment is unknown and…

Probability · Mathematics 2011-11-21 Krzysztof Szajowski

We calculate, for a branching random walk $X_n(l)$ to a leaf $l$ at depth $n$ on a binary tree, the positive integer moments of the random variable $\frac{1}{2^{n}}\sum_{l=1}^{2^n}e^{2\beta X_n(l)}$, for $\beta\in\mathbb{R}$. We obtain…

Mathematical Physics · Physics 2021-01-15 E. C. Bailey , J. P. Keating

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its…

Populations and Evolution · Quantitative Biology 2014-12-02 Anand Bhaskar , Yun S. Song

We consider the problem of identifying, from its first $m$ noisy moments, a probability distribution on $[0,1]$ of support $k<\infty$. This is equivalent to the problem of learning a distribution on $m$ observable binary random variables…

Machine Learning · Computer Science 2020-09-08 Spencer Gordon , Bijan Mazaheri , Leonard J. Schulman , Yuval Rabani
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