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Kernel embeddings have emerged as a powerful tool for representing probability measures in a variety of statistical inference problems. By mapping probability measures into a reproducing kernel Hilbert space (RKHS), kernel embeddings enable…

Machine Learning · Statistics 2024-10-31 Dino Sejdinovic

We introduce a general method for transforming the equations of motion following from a Das-Jevicki-Sakita Hamiltonian, with boundary conditions, into a boundary value problem in one-dimensional quantum mechanics. For the particular case of…

High Energy Physics - Theory · Physics 2009-10-31 L. D. Paniak

We consider the quantum sinh-Gordon model in this paper. Using known formulae for form factors we sum up all their contributions and obtain a closed expression for a correlation function. This expression is a determinant of an integral…

High Energy Physics - Theory · Physics 2008-11-26 V. E. Korepin , N. A. Slavnov

We develop a systematic field-theoretical approach to open quantum systems based on condensed-matter many-body methods. The time evolution of the reduced density matrix for the open quantum system is determined by a transmission matrix.…

Quantum Physics · Physics 2022-08-09 Hans C. Fogedby

Many scientific problems involve data exhibiting both temporal and cross-sectional dependencies. While linear dependencies have been extensively studied, the theoretical analysis of regression estimators under nonlinear dependencies remains…

Statistics Theory · Mathematics 2025-02-27 Marie-Christine Düker , Adam Waterbury

We analyze the long-time asymptotics for the Degasperis--Procesi equation on the half-line. By applying nonlinear steepest descent techniques to an associated $3 \times 3$-matrix valued Riemann--Hilbert problem, we find an explicit formula…

Analysis of PDEs · Mathematics 2018-01-15 A. Boutet de Monvel , J. Lenells , D. Shepelsky

We present a quantum algorithm for the dynamical simulation of time-dependent Hamiltonians. Our method involves expanding the interaction-picture Hamiltonian as a sum of generalized permutations, which leads to an integral-free Dyson series…

Quantum Physics · Physics 2021-09-15 Yi-Hsiang Chen , Amir Kalev , Itay Hen

In this work, a kernel-based surrogate for integrating Hamiltonian dynamics that is symplectic by construction and tailored to large prediction horizons is proposed. The method learns a scalar potential whose gradient enters a…

Numerical Analysis · Mathematics 2026-01-27 Robin Herkert , Tobias Ehring , Bernard Haasdonk

Hermite processes are a class of self-similar processes with stationary increments. They often arise in limit theorems under long-range dependence. We derive new representations of Hermite processes with multiple Wiener-It\^o integrals,…

Probability · Mathematics 2020-05-11 Shuyang Bai

We obtain asymptotic formulas for the partition function of the six-vertex model with domain wall boundary conditions and half-turn symmetry in each of the phase regions. The proof is based on the Izergin--Korepin--Kuperberg determinantal…

Mathematical Physics · Physics 2017-11-06 Pavel Bleher , Karl Liechty

Both Sawada-Kotera (SK) equation and Kaup-Kupershmidt (KK) equation are integrable systems with third-order Lax operator. Moreover, they are related with the same modified nonlinear equation (called modified SK-KK equation) by Miura…

Exactly Solvable and Integrable Systems · Physics 2023-07-18 Deng-Shan Wang , Xiaodong Zhu

Implicit neural representations (INRs) have recently emerged as a powerful tool that provides an accurate and resolution-independent encoding of data. Their robustness as general approximators has been shown in a wide variety of data…

Machine Learning · Computer Science 2022-08-12 Elizabeth Fons , Alejandro Sztrajman , Yousef El-laham , Alexandros Iosifidis , Svitlana Vyetrenko

We consider unitary invariant random matrix ensembles which obey spectral statistics different from the Wigner-Dyson, including unitary ensembles with slowly (~(log x)^2) growing potentials and the finite-temperature fermi gas model. If the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Shinsuke M. Nishigaki

The rigorous asymptotic analysis for the Riemann problem of the defocusing nonlinear Schr\"{o}dinger hydrodynamics is a very interesting problem with many challenges. To date, the full analysis of this problem remains open. In this work,…

Analysis of PDEs · Mathematics 2026-03-31 Deng-Shan Wang , Peng Yan

Representations of probability measures in reproducing kernel Hilbert spaces provide a flexible framework for fully nonparametric hypothesis tests of independence, which can capture any type of departure from independence, including…

Computation · Statistics 2018-06-11 Qinyi Zhang , Sarah Filippi , Arthur Gretton , Dino Sejdinovic

Analyzing the structure of sampled features from an input data distribution is challenging when constrained by limited measurements in both the number of inputs and features. Traditional approaches often rely on the eigenvalue spectrum of…

Machine Learning · Computer Science 2025-02-11 Chanwoo Chun , SueYeon Chung , Daniel D. Lee

A general unifying framework for integrable soliton-like systems on time scales is introduced. The $R$-matrix formalism is applied to the algebra of $\delta$-differential operators in terms of which one can construct infinite hierarchy of…

Exactly Solvable and Integrable Systems · Physics 2016-02-18 Maciej Blaszak , Burcu Silindir , Blazej M. Szablikowski

The generalized Weyl transform of index $\alpha$ is used to implement the time-slice definition of the phase space path integral yielding the Feynman kernel in the case of noncommutative quantum mechanics. As expected, this representation…

Quantum Physics · Physics 2009-11-13 F. S. Bemfica , H. O. Girotti

In this paper we study the spectra of bounded self-adjoint linear operators that are related to finite Hilbert transforms $\mathcal{H}_L:L^2([b_L,0])\to L^2([0,b_R])$ and $\mathcal{H}_R:L^2([0,b_R])\to L^2([b_L,0])$. These operators arise…

Classical Analysis and ODEs · Mathematics 2019-09-20 Marco Bertola , Elliot Blackstone , Alexander Katsevich , Alexander Tovbis

We provide a unified framework for independence and mean independence tests based on the Hilbert-Schmidt independence criterion, extending some previous results in the literature to hold in general topological spaces. We also present a…

Methodology · Statistics 2026-05-01 Daniel Diz-Castro , Manuel Febrero-Bande , Wenceslao González-Manteiga