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The sparse polynomial approximation of continuous functions has emerged as a prominent area of interest in function approximation theory in recent years. A key challenge within this domain is the accurate estimation of approximation errors.…

Numerical Analysis · Mathematics 2025-06-10 Renzhong Feng , Bowen Zhang

We prove uniform synchronisation by noise with rates for the stochastic quantisation equation in dimensions two and three. The proof relies on a combination of coming down from infinity estimates and the framework of order-preserving Markov…

Probability · Mathematics 2019-10-18 Benjamin Gess , Pavlos Tsatsoulis

Consider an unknown smooth function $f: [0,1] \rightarrow \mathbb{R}$, and say we are given $n$ noisy$\mod 1$ samples of $f$, i.e., $y_i = (f(x_i) + \eta_i)\mod 1$ for $x_i \in [0,1]$, where $\eta_i$ denotes noise. Given the samples…

Machine Learning · Statistics 2018-04-04 Mihai Cucuringu , Hemant Tyagi

Quantum noise in a model of singly resonant frequency doubling including phase mismatch and driving in the harmonic mode is analyzed. The general formulae about the fixed points and their stability as well as the squeezing spectra…

Quantum Physics · Physics 2007-05-23 C. Cabrillo , J. L. Roldan , P. Garcia-Fernandez

This paper investigates the theoretical guarantees of L1-analysis regularization when solving linear inverse problems. Most of previous works in the literature have mainly focused on the sparse synthesis prior where the sparsity is measured…

Information Theory · Computer Science 2012-10-03 Samuel Vaiter , Gabriel Peyré , Charles Dossal , Jalal Fadili

A Boolean function $f:V \to \{-1,1\}$ on the vertex set of a graph $G=(V,E)$ is locally $p$-stable if for every vertex $v$ the proportion of neighbours $w$ of $v$ with $f(v)=f(w)$ is exactly $p$. This notion was introduced by Gross and…

Combinatorics · Mathematics 2022-03-01 Asier Calbet

We consider the family of stochastic partial differential equations indexed by a parameter $\eps\in(0,1]$, \begin{equation*} Lu^{\eps}(t,x) = \eps\sigma(u^\eps(t,x))\dot{F}(t,x)+b(u^\eps(t,x)), \end{equation*} $(t,x)\in(0,T]\times\Rd$ with…

Probability · Mathematics 2015-03-25 Marta Sanz-Solé , André Süß

In this paper we study the one-dimensional Kardar-Parisi-Zhang equation (KPZ) with correlated noise by field-theoretic dynamic renormalization group techniques (DRG). We focus on spatially correlated noise where the correlations are…

Statistical Mechanics · Physics 2018-06-20 Oliver Niggemann , Haye Hinrichsen

The standard model of Boolean function property testing is not well suited for testing $\textit{sparse}$ functions which have few satisfying assignments, since every such function is close (in the usual Hamming distance metric) to the…

Computational Complexity · Computer Science 2025-09-03 Xi Chen , Anindya De , Yizhi Huang , Yuhao Li , Shivam Nadimpalli , Rocco A. Servedio , Tianqi Yang

We show that perturbing ill-posed differential equations with (potentially very) smooth random processes can restore well-posedness -- even if the perturbation is (potentially much) more regular than the drift component of the solution. The…

Probability · Mathematics 2024-09-25 Máté Gerencsér

We consider perturbations of closed Friedmann universes. Perturbation modes of two lowest wavenumbers ($L=0$ and $1$) are generally known to be fictitious, but here we show that both are physical. The issue is more subtle in Einstein static…

General Relativity and Quantum Cosmology · Physics 2020-07-07 Hyerim Noh , Jai-chan Hwang , John D. Barrow

We study active learning of homogeneous $s$-sparse halfspaces in $\mathbb{R}^d$ under the setting where the unlabeled data distribution is isotropic log-concave and each label is flipped with probability at most $\eta$ for a parameter $\eta…

Machine Learning · Computer Science 2021-08-16 Chicheng Zhang , Jie Shen , Pranjal Awasthi

We consider a discrete one-dimensional random interface on the half-space whose height at any positive point is composed of a function of the heights at its two closest neighbours and an independent random noise background. In [AC24],…

Probability · Mathematics 2025-08-26 Yiming Tang

Based on the Heisenberg-picture analog of the master equation, we develop a method for computing the exact time dependence of noise-averaged observables for general noninteracting fermionic systems with noisy fluctuations. Upon noise…

Quantum Gases · Physics 2015-10-22 Armin Rahmani

In metrological tasks, employing entanglement can quantitatively improve the precision of parameter estimation. However, susceptibility of the entanglement to decoherence fades this capability in the realistic metrology and limits ultimate…

Quantum Physics · Physics 2017-05-04 R. Yousefjani , S. Salimi , A. S. Khorashad

We study the one-dimensional stochastic wave equation driven by a Gaussian multiplicative noise which is white in time and has the covariance of a fractional Brownian motion with Hurst parameter $H\in [1/2,1)$ in the spatial variable. We…

Probability · Mathematics 2020-10-27 Francisco Delgado-Vences , David Nualart , Guangqu Zheng

We illustrate a counter-intuitive effect of an additive stochastic force, which acts independently on each element of an ensemble of globally coupled oscillators. We show numerically and semi-analytically that a very small white noise is…

Adaptation and Self-Organizing Systems · Physics 2017-06-27 Pau Clusella , Antonio Politi

Let $f: T\to \{ 0,1 \}$ be a Boolean function on the Boolean half-slice, $T$, \ie elements of $\{0,1\}^n$ with Hamming weight $n/2$. We show that if $f(x)+f(y)=f(x+y)$ holds with probability $\frac{1+\delta}{2}$ over a uniform pair $(x,y)$…

Computational Complexity · Computer Science 2026-05-27 Haakon Larsen , Tushant Mittal , Silas Richelson , Sourya Roy

Consistency regularization is a commonly-used technique for semi-supervised and self-supervised learning. It is an auxiliary objective function that encourages the prediction of the network to be similar in the vicinity of the observed…

Machine Learning · Computer Science 2021-10-05 Erik Englesson , Hossein Azizpour

Recent research on the dynamics of certain fluid dynamical instabilities shows that when there is a slow invariant manifold subject to fast timescale instability the dynamics are extremely sensitive to noise. The behaviour of such systems…

adap-org · Physics 2009-10-30 G. D. Lythe , M. R. E. Proctor