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In the ${\rm AdS}_3/{\rm CFT}_2$ setup we elucidate how gauge invariant boundary patterns of entanglement of the CFT vacuum are encoded into the bulk via the coefficient dynamics of an $A_{N-3}$, $N\geq 4$ cluster algebra. In the static…

High Energy Physics - Theory · Physics 2020-04-01 Péter Lévay , Bercel Boldis

In this work, we study an inverse problem of recovering a space-time dependent diffusion coefficient in the subdiffusion model from the distributed observation, where the mathematical model involves a Djrbashian-Caputo fractional derivative…

Numerical Analysis · Mathematics 2022-09-23 Bangti Jin , Zhi Zhou

The paper deals with the necessary and sufficient conditions for obtaining reconstruction formulae and sampling theorems for every function belonging to the principal shift invariant subspace of $L^2(\mathbb{H}^n)$, both in the time domain…

Functional Analysis · Mathematics 2019-02-06 S. Arati , R. Radha

We construct and analyze the Standard Model of electroweak and strong interactions in multiscale spacetimes with (i) weighted derivatives and (ii) $q$-derivatives. Both theories can be formulated in two different frames, called fractional…

High Energy Physics - Theory · Physics 2016-08-30 Gianluca Calcagni , Giuseppe Nardelli , David Rodríguez-Fernández

Longitudinal data are important in numerous fields, such as healthcare, sociology and seismology, but real-world datasets present notable challenges for practitioners because they can be high-dimensional, contain structured missingness…

Machine Learning · Computer Science 2024-07-01 Maksim Sinelnikov , Manuel Haussmann , Harri Lähdesmäki

In this paper, we investigate the stochastic differential equation on $\mathbb{R}^d,d\geq2$: \begin{align*} \dif X_t&=v(t,X_t)\dif t+\sqrt{2} \dif W_t. \end{align*} For any finite collection of initial probability measures…

Probability · Mathematics 2025-10-10 Huaxiang Lü , Michael Röckner

In many stochastic models, the observables of interest are naturally encoded in double transforms (e.g., Laplace transforms) that couple spatial and temporal variables. Notably, the double transform often provides the only analytically…

Probability · Mathematics 2026-05-21 Giampaolo Cristadoro , Gaia Pozzoli

The development of compact and energy-efficient wearable sensors has led to an increase in the availability of biosignals. To analyze these continuously recorded, and often multidimensional, time series at scale, being able to conduct…

Machine Learning · Computer Science 2022-08-02 Knut J. Strømmen , Jim Tørresen , Ulysse Côté-Allard

In this paper we analyze two-dimensional wavelet reconstructions from Fourier samples within the framework of generalized sampling. For this, we consider both separable compactly-supported wavelets and boundary wavelets. We prove that the…

Functional Analysis · Mathematics 2014-03-25 Ben Adcock , Anders C. Hansen , Gitta Kutyniok , Jackie Ma

We investigate the switching dynamics of multistable nematic liquid crystal devices. In particular we identify a remarkably simple 2-dimensional (2D) device which exploits hybrid alignment at the surfaces to yield a bistable response. We…

Soft Condensed Matter · Physics 2011-02-08 A. Tiribocchi , G. Gonnella , D. Marenduzzo , E. Orlandini

Accurate reconstruction of static environments from LiDAR scans of scenes containing dynamic objects, which we refer to as Dynamic to Static Translation (DST), is an important area of research in Autonomous Navigation. This problem has been…

Computer Vision and Pattern Recognition · Computer Science 2021-05-28 Prashant Kumar , Sabyasachi Sahoo , Vanshil Shah , Vineetha Kondameedi , Abhinav Jain , Akshaj Verma , Chiranjib Bhattacharyya , Vinay Viswanathan

Linear Canonical Transformations (LCTs) are known in signal processing and optics as the generalization of certain useful integral transforms. In quantum theory, they can be identified as the linear transformations which keep invariant the…

We provide an overview on how to use the measurable selection techniques to derive the dynamic programming principle for a general stochastic optimal control/stopping problem. By considering its martingale problem formulation on the…

Optimization and Control · Mathematics 2024-10-03 Nicole El Karoui , Xiaolu Tan

Cyclostationary linear inverse models (CS-LIMs), generalized versions of the classical (stationary) LIM, are advanced data-driven techniques for extracting the first-order time-dependent dynamics and random forcing relevant information from…

Numerical Analysis · Mathematics 2025-05-01 Justin Lien , Yan-Ning Kuo , Hiroyasu Ando

This paper presents a canonical dual approach for solving a nonlinear population growth problem governed by the well-known logistic equation. Using the finite difference and least squares methods, the nonlinear differential equation is…

Chaotic Dynamics · Physics 2012-06-13 Ning Ruan , David Y. Gao

The invariance for the equation of fast diffusion in the 2D coordinate space has been proved, and its reduction to the 1D (with respect to the spatial variable) analog is demonstrated. On the basis of these results, new exact…

Mathematical Physics · Physics 2007-05-23 E. I. Semenov

In optical diffraction tomography (ODT), a sample's 3D refractive-index (RI) is often reconstructed after illuminating it from multiple angles, with the assumption that the sample remains static throughout data collection. When the sample…

Optics · Physics 2024-12-13 Jeongsoo Kim , Shwetadwip Chowdhury

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

Building on an analogy with conformal invariance, local scale transformations consistent with dynamical scaling are constructed. Two types of local scale invariance are found which act as dynamical space-time symmetries of certain non-local…

Statistical Mechanics · Physics 2007-05-23 Malte Henkel

Long-term forecasting of multivariate urban data poses a significant challenge due to the complex spatiotemporal dependencies inherent in such datasets. This paper presents DST, a novel multivariate time-series forecasting model that…

Machine Learning · Computer Science 2025-08-28 Amirhossein Sohrabbeig , Omid Ardakanian , Petr Musilek
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