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A key step in the origin of life is the emergence of a primitive metabolism. This requires the formation of a subset of chemical reactions that is both self-sustaining and collectively autocatalytic. A generic theory to study such processes…

Molecular Networks · Quantitative Biology 2019-10-22 Oliver Weller-Davies , Mike Steel , Jotun Hein

We consider the maximal p-norm associated with a completely positive map and the question of its multiplicativity under tensor products. We give a condition under which this multiplicativity holds when p = 2, and we describe some maps which…

Quantum Physics · Physics 2009-01-14 Christopher King , Mary Beth Ruskai

Markov random fields (MRFs) are a powerful tool for modelling statistical dependencies for a set of random variables using a graphical representation. An important computational problem related to MRFs, called maximum a posteriori (MAP)…

Data Structures and Algorithms · Computer Science 2017-08-11 Alexander Bauer , Shinichi Nakajima , Nico Görnitz , Klaus-Robert Müller

We study the joint probability density of the eigenvalues of a product of rectangular real, complex or quaternion random matrices in a unified way. The random matrices are distributed according to arbitrary probability densities, whose only…

Mathematical Physics · Physics 2014-03-17 J. R. Ipsen , M. Kieburg

The objective of this paper is to examine the restriction of a right process on a Radon topological space, excluding a negligible set, and investigate whether the restricted object can induce a Markov process with desirable properties. We…

Probability · Mathematics 2023-06-16 Liping Li , Michael Röckner

We calculate exact convergence times to reach random bipartite entanglement for various random protocols. The eigenproblem of a Markovian chain governing the process is mapped to a spin chain, thereby obtaining exact expression for the gap…

Quantum Physics · Physics 2008-09-26 Marko Znidaric

We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

In this paper we study sets of points in the plane with rational distances from r prescribed points P_1, ...,P_r. A crucial case arises for r = 3, where we provide simple necessary and sufficient conditions for the density of this set in…

Number Theory · Mathematics 2025-06-24 Pietro Corvaja , Amos Turchet , Umberto Zannier

We study a class of dynamical systems generated by random substitutions, which contains both intrinsically ergodic systems and instances with several measures of maximal entropy. In this class, we show that the measures of maximal entropy…

Dynamical Systems · Mathematics 2026-03-26 Philipp Gohlke , Andrew Mitchell

The rational covariance extension problem to determine a rational spectral density given a finite number of covariance lags can be seen as a matrix completion problem to construct an infinite-dimensional positive-definite Toeplitz matrix…

Optimization and Control · Mathematics 2012-08-31 Anders Lindquist , Giorgio Picci

A \emph{rational orthogonal matrix} $Q$ is an orthogonal matrix with rational entries, and $Q$ is called \emph{regular} if each of its row sum equals one, i.e., $Qe = e$ where $e$ is the all-one vector. This paper presents a method for…

Combinatorics · Mathematics 2024-10-16 Quanyu Tang , Wei Wang , Hao Zhang

MAP is the problem of finding a most probable instantiation of a set of variables given evidence. MAP has always been perceived to be significantly harder than the related problems of computing the probability of a variable instantiation…

Artificial Intelligence · Computer Science 2011-07-04 A. Darwiche , J. D. Park

When is a topological branched self-cover of the sphere equivalent to a rational map on CP^1? William Thurston gave one answer in 1982, giving a negative criterion (an obstruction to a map being rational). We give a complementary, positive…

Dynamical Systems · Mathematics 2020-07-23 Dylan P. Thurston

Estimating a Gibbs density function given a sample is an important problem in computational statistics and statistical learning. Although the well established maximum likelihood method is commonly used, it requires the computation of the…

Machine Learning · Computer Science 2023-03-14 Eldad Haber , Moshe Eliasof , Luis Tenorio

Let $R=K[[x_1,...,x_s]]$ be the ring of formal power series with maximal ideal $\mathfrak{m}$ over a field $K$ of arbitrary characteristic. On the ring $M_{m,n}$ of $m\times n$ matrices $A$ with entries in $R$ we consider several…

Algebraic Geometry · Mathematics 2016-09-19 Gert-Martin Greuel , Thuy Huong Pham

Under GRH, any element in the multiplicative group of a number field $K$ that is globally primitive (i.e., not a perfect power in $K^*$) is a primitive root modulo a set of primes of $K$ of positive density. For elliptic curves $E/K$ that…

Number Theory · Mathematics 2026-04-22 Nathan Jones , Francesco Pappalardi , Peter Stevenhagen

When the linear measurements of an instance of low-rank matrix recovery satisfy a restricted isometry property (RIP)---i.e. they are approximately norm-preserving---the problem is known to contain no spurious local minima, so exact recovery…

Machine Learning · Computer Science 2018-11-01 Richard Y. Zhang , Cédric Josz , Somayeh Sojoudi , Javad Lavaei

MAP is the problem of finding a most probable instantiation of a set of nvariables in a Bayesian network, given some evidence. MAP appears to be a significantly harder problem than the related problems of computing the probability of…

Artificial Intelligence · Computer Science 2013-01-07 James D. Park

We analyze the connections between the non-Markovianity degree of the most general phase-damping qubit maps and their legitimate mixtures. Using the results for image non-increasing dynamical maps, we formulate the necessary and sufficient…

Quantum Physics · Physics 2022-05-25 Katarzyna Siudzińska

Entropic regularization is quickly emerging as a new standard in optimal transport (OT). It enables to cast the OT computation as a differentiable and unconstrained convex optimization problem, which can be efficiently solved using the…

Machine Learning · Statistics 2018-02-21 Mathieu Blondel , Vivien Seguy , Antoine Rolet
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