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The fits of 0.4 Ca(NO_3)_2 0.6 K(NO_3) (CKN) by schematic mode-coupling models [V. Krakoviack and C. Alba-Simionesco, J. Chem. Phys. 117, 2161-2171 (2002)] are analyzed by asymptotic expansions. The validity of both the power-law and the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Matthias Sperl

In recent years, there is a growing need for processing methods aimed at extracting useful information from large datasets. In many cases the challenge is to discover a low-dimensional structure in the data, often concealed by the existence…

Statistics Theory · Mathematics 2019-06-05 Yariv Aizenbud , Boris Landa , Yoel Shkolnisky

In this paper, we consider measure-theoretical restricted sensitivity and topological restricted sensitivities by restricting the first sensitive time. For a given topological dynamical system, we define measure-theoretical restricted…

Dynamical Systems · Mathematics 2020-10-23 Kairan Liu , Leiye Xu , Ruifeng Zhang

We prove that the Sinkhorn algorithm converges at a rate of $O(k^{-1} \log k)$ in $\ell_1$-norm marginal error, in the asymptotically scalable case. This almost closes the gap between the lower bound $\Omega(k^{-1})$ (Qu et al., 2025) and…

Optimization and Control · Mathematics 2026-05-15 Guillaume Wang

We present and discuss a general density-matrix description of energy-dissipation and decoherence phenomena in open quantum systems, able to overcome the intrinsic limitations of the conventional Markov approximation. In particular, the…

Quantum Physics · Physics 2015-05-30 Michele Pepe , David Taj , Rita Claudia Iotti , Fausto Rossi

We propose and analyze an approximate message passing (AMP) algorithm for the matrix tensor product model, which is a generalization of the standard spiked matrix models that allows for multiple types of pairwise observations over a…

Machine Learning · Statistics 2023-06-28 Riccardo Rossetti , Galen Reeves

For polynomial $ P (x,y)$, and any Calder\'{o}n-Zygmund kernel, $K$, the operator below satisfies a $ (1,r)$ sparse bound, for $ 1< r \leq 2$. $$ \sup _{\epsilon >0} \Bigl\lvert \int_{|y| > \epsilon} f (x-y) e ^{2 \pi i P (x,y) } K(y) \; dy…

Classical Analysis and ODEs · Mathematics 2018-05-23 Ben Krause , Michael T. Lacey

We consider the question of quantitative stability of minimisers for a well-known variational problem for which the infimum of the energy is not achieved in the classical sense, namely for the Dirichlet energy of degree $1$ maps from closed…

Analysis of PDEs · Mathematics 2026-03-27 Melanie Rupflin , Sebastian Woodward

Asymptotics are given for the number of rational points in the domain of a morphism of weighted projective stacks whose images have bounded height and satisfy a (possibly infinite) set of local conditions. As a consequence we obtain results…

Number Theory · Mathematics 2026-03-25 Tristan Phillips

We consider weak solutions of the adjoint equation for an elliptic operator in nondivergent form, and their asymptotic properties at an interior point. We assume that the coefficients a_{ij} are bounded, measurable, complex-valued functions…

Analysis of PDEs · Mathematics 2007-05-23 Vladimir Maz'ya , Robert McOwen

A method to study strongly interacting quantum many-body systems at and away from criticality is proposed. The method is based on a MERA-like tensor network that can be efficiently and reliably contracted on a noisy quantum computer using a…

Quantum Physics · Physics 2017-11-22 Isaac H. Kim , Brian Swingle

Compressed Counting (CC), based on maximally skewed stable random projections, was recently proposed for estimating the p-th frequency moments of data streams. The case p->1 is extremely useful for estimating Shannon entropy of data…

Data Structures and Algorithms · Computer Science 2009-10-09 Ping Li

Estimating the number of spikes in a spiked model is an important problem in many areas such as signal processing. Most of the classical approaches assume a large sample size $n$ whereas the dimension $p$ of the observations is kept small.…

Statistics Theory · Mathematics 2014-06-04 Damien Passemier , Jian-Feng Yao

We investigate the asymptotic mean squared error of kernel estimators of the intensity function of a spatial point process. We show that when $n$ independent copies of a point process in $\mathbb R^d$ are superposed, the optimal bandwidth…

Statistics Theory · Mathematics 2019-04-11 M. N. M. van Lieshout

We describe five types of results concerning information and concentration of discrete random variables, and relationships between them, motivated by their counterparts in the continuous case. The results we consider are information…

Probability · Mathematics 2017-04-25 Oliver Johnson

In "Random complex fewnomials, I," B. Shiffman and S. Zelditch determine the limiting formula as N goes to infinity of the (normalized) expected distribution of complex zeros of a system of k random n-nomials in m variables where the…

Complex Variables · Mathematics 2013-12-02 Timothy Tran

We provide the first PDE proof of the celebrated Bramson's $o(1)$ results in 1983 concerning the large time asymptotics for the KPP equation under front-like initial data of types $x^{k+1}e^{-\lambda_*x}$ and $x^{\boldsymbol{\nu}}…

Analysis of PDEs · Mathematics 2025-06-12 Mingmin Zhang

This paper deals with diffusive limit of the p-system with damping and its approximation by an Asymptotic Preserving (AP) Finite Volume scheme. Provided the system is endowed with an entropy-entropy flux pair, we give the convergence rate…

Numerical Analysis · Mathematics 2016-09-07 Christophe Berthon , Marianne Bessemoulin-Chatard , Hélène Mathis

We consider covariance asymptotics for linear statistics of general stationary random measures in terms of their truncated pair correlation measure. We give exact infinite series-expansion formulas for covariance of smooth statistics of…

Probability · Mathematics 2024-11-14 Manjunath Krishnapur , D. Yogeshwaran

Sharpness Aware Minimization (SAM) enhances performance across various neural architectures and datasets. As models are continually scaled up to improve performance, a rigorous understanding of SAM's scaling behaviour is paramount. To this…

Machine Learning · Computer Science 2025-02-12 Moritz Haas , Jin Xu , Volkan Cevher , Leena Chennuru Vankadara