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We apply the heat kernel method to relations between covariant and consistent currents in anomalous chiral gauge theories. Banerjee et al. have shown that the relation between these currents is expressed by a "functional curl" of the…

High Energy Physics - Theory · Physics 2019-12-06 Masaharu Takeuchi , Ryusuke Endo

We study reflected diffusion on uniform domains where the underlying space admits a symmetric diffusion that satisfies sub-Gaussian heat kernel estimates. A celebrated theorem of Jones (Acta Math. 1981) states that uniform domains in…

Probability · Mathematics 2024-01-29 Mathav Murugan

We present a detailed study of the real-time dynamics and spectral properties of the one-dimensional fermionic Hubbard model at infinite temperature. Using tensor network simulations in Liouville space, we compute the single-particle…

Strongly Correlated Electrons · Physics 2025-09-26 Cătălin Paşcu Moca , Ovidiu I. Patu , Balázs Dóra , Gergely Zaránd

We consider general Markov processes with absorption and provide criteria ensuring the exponential convergence in total variation of the distribution of the process conditioned not to be absorbed. The first one is based on two-sided…

Probability · Mathematics 2018-01-18 Nicolas Champagnat , Koléhè Coulibaly-Pasquier , Denis Villemonais

The first heat kernel coefficients are calculated for a dispersive ball whose permittivity at high frequency differs from unity by inverse powers of the frequency. The corresponding divergent part of the vacuum energy of the electromagnetic…

High Energy Physics - Theory · Physics 2008-11-26 M. Bordag , K. Kirsten

Upper and lower bounds on the heat kernel on complete Riemannian manifolds were obtained in a series of pioneering works due to Cheng-Li-Yau, Cheeger-Yau and Li-Yau. However, these estimates do not give a complete picture of the heat kernel…

Analysis of PDEs · Mathematics 2017-05-29 Xi Chen , Andrew Hassell

We study gradient bounds and other functional inequalities for the diffusion semigroup generated by Kolmogorov type operators. The focus is on two different methods: coupling techniques and generalized $\Gamma$-calculus techniques. The…

Probability · Mathematics 2019-03-20 Fabrice Baudoin , Maria Gordina , Phanuel Mariano

We prove that a metric measure space equipped with a Dirichlet form admitting an Euclidean heat kernel is necessarily isometric to the Euclidean space. This helps us providing an alternative proof of Colding's celebrated almost rigidity…

Metric Geometry · Mathematics 2020-02-04 Gilles Carron , David Tewodrose

A common tool in Casimir physics (and many other areas) is the asymptotic (high-frequency) expansion of eigenvalue densities, employed as either input or output of calculations of the asymptotic behavior of various Green functions. Here we…

Mathematical Physics · Physics 2015-06-22 S. A. Fulling , Y. Yang

This paper is an exposition of several questions linking heat kernel measures on infinite dimensional Lie groups, limits associated with critical Sobolev exponents, and Feynmann-Kac measures for sigma models.

Functional Analysis · Mathematics 2007-11-06 Doug Pickrell

We prove that homological filling functions over a ring $R$ equipped with the discrete norm are quasi-isometry invariants for all groups of type $\mathrm{FP}_n$. This confirms a conjecture of Bader-Kropholler-Vankov in the case of discrete…

Group Theory · Mathematics 2026-03-10 Jannis Weis

A quasi-infinitely divisible distribution on $\mathbb{R}^d$ is a probability distribution $\mu$ on $\mathbb{R}^d$ whose characteristic function can be written as the quotient of the characteristic functions of two infinitely divisible…

Probability · Mathematics 2021-01-08 David Berger , Merve Kutlu , Alexander Lindner

In this paper, we consider the following symmetric Dirichlet forms on a metric measure space $(M,d,\mu)$: $$\mathcal{E}(f,g) = \mathcal{E}(^{(c)}(f,g)+\int_{M\times M} (f(x)-f(y))(g(x)-g(y))\,J(dx,dy),$$ where $\mathcal{E}(^{(c)}$ is a…

Probability · Mathematics 2019-08-22 Zhen-Qing Chen , Takashi Kumagai , Jian Wang

We prove that for a finite collection of real-valued functions $f_{1},...,f_{n}$ on the group of complex numbers of modulus 1 which are derivable with Lipschitz continuous derivative, the distribution of $(\tr f_{1},...,\tr f_{n})$ under…

Probability · Mathematics 2011-09-12 Thierry Lévy , Mylène Maïda

In this paper, we present two infinite-dimensional Kolmogorov theorems based on non-resonant frequencies of Bourgain's Diophantine type or even weaker conditions. To be more precise, under a Legendre-type nondegeneracy condition for an…

Dynamical Systems · Mathematics 2026-04-01 Zhicheng Tong , Yong Li

We introduce the concept of quasi-inverse of quantum and classical channels, prove general properties of these inverses and determine them for a large class of channels acting in an arbitrary finite dimension. Therefore we extend the…

Quantum Physics · Physics 2021-08-11 Fereshte Shahbeigi , Koorosh Sadri , Morteza Moradi , Karol Życzkowski , Vahid Karimipour

Accurate numerical results are derived for transport properties of Kondo impurity systems with potential scattering and orbital degeneracy. Using the continuous-time quantum Monte Carlo (CT-QMC) method, static and dynamic physical…

Strongly Correlated Electrons · Physics 2015-07-30 Annamaria Kiss , Yoshio Kuramoto , Shintaro Hoshino

We present a stable characterization of on-diagonal upper bounds for heat kernels associated with regular Dirichlet forms on metric measure spaces satisfying the volume doubling property. Our conditions include integral bounds on the jump…

Analysis of PDEs · Mathematics 2025-01-14 Soobin Cho

We construct a family of infinite-dimensional reduced Heisenberg groups which can be viewed as infinite-dimensional homogeneous spaces. Such a space is an analogue of finite-dimensional reduced Heisenberg groups in infinite dimensions. We…

Probability · Mathematics 2025-12-04 Maria Gordina , Liangbing Luo

Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector…

Machine Learning · Statistics 2018-08-07 Chenchao Zhao , Jun S. Song