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We reformulate gauge theories in analogy with the vierbein formalism of general relativity. More specifically, we reformulate gauge theories such that their gauge dynamical degrees of freedom are local fields that transform linearly under…

High Energy Physics - Theory · Physics 2016-11-23 Daniel J. H. Chung , Ran Lu

A momentum dependent projection of the Wegner-Hougton equation is derived for a scalar theory coupled to an external field. This formalism is useful to discuss the phase diagram of the theory. In particular we study some properties of the…

High Energy Physics - Theory · Physics 2009-10-30 A. Bonanno , D. Zappala'

Observables in random tensor theory are polynomials in the entries of a tensor of rank $d$ which are invariant under $U(N)^d$. It is notoriously difficult to evaluate the expectations of such polynomials, even in the Gaussian distribution.…

Mathematical Physics · Physics 2014-11-26 Valentin Bonzom , Frédéric Combes

In this Note, a new approach to spacecraft positioning based on GGT inversion is presented. The gravity gradient tensor is initially measured in the gradiometer reference frame (GRF) and then transformed to the Earth-Centered Earth-Fixed…

Instrumentation and Methods for Astrophysics · Physics 2016-08-12 Pei Chen , Xiucong Sun , Chao Han

Series expansions of isotropic Gaussian random fields on $\mathbb{S}^2$ with independent Gaussian coefficients and localized basis functions are constructed. Such representations with multilevel localised structure provide an alternative to…

Probability · Mathematics 2022-06-27 Markus Bachmayr , Ana Djurdjevac

Anisotropic stress perturbations induced by primordial Gaussian vector fields create non-Gaussianity in curvature perturbations. We found that such non-Gaussianity closely resembles the local-type non-Gaussianity parametrized by $f_{\rm…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-14 Maresuke Shiraishi , Shuichiro Yokoyama , Kiyotomo Ichiki , Takahiko Matsubara

Motivated by the subordinated Brownian motion, we define a new class of (in general discontinuous) random fields on higher-dimensional parameter domains: the subordinated Gaussian random field. We investigate the pointwise marginal…

Probability · Mathematics 2022-08-26 Andrea Barth , Robin Merkle

We calculate correlation functions of the (signed) density of zeros of Gaussian distributed vector fields. We are able to express correlation functions of arbitrary order through the curvature tensor of a certain abstract Riemann-Cartan or…

Statistical Mechanics · Physics 2009-11-07 Georg Foltin

We study pathwise invariances of centred random fields that can be controlled through the covariance. A result involving composition operators is obtained in second-order settings, and we show that various path properties including…

Statistics Theory · Mathematics 2013-08-07 David Ginsbourger , Olivier Roustant , Nicolas Durrande

In this paper the localization properties of the spectral expansions of distributions related to the self adjoint extension of the Schrodinger operator are investigated. Spectral decompositions of the distributions and some classes of…

Mathematical Physics · Physics 2019-07-22 Abdumalik Rakhimov , Anvarjon Ahmedov , Hishamuddin Zainuddin

X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS) are powerful probes of electronic structure owing to their chemical and orbital selectivity. For powder samples, however, interpreting RIXS spectral…

Materials Science · Physics 2026-05-12 Sihan Zhang , Oana Bunău , Marius Retegan , Pieter Glatzel

We find that biorthogonal quantum mechanics with a scalar product that counts both absorbed and emitted particles leads to covariant position operators with localized eigenvectors. In this manifestly covariant formulation the probability…

Quantum Physics · Physics 2017-05-24 Margaret Hawton , Vincent Debierre

We introduce a geometrical framework for double field theory in which generalized Riemann and torsion tensors are defined without reference to a particular basis. This invariant geometry provides a unifying framework for the frame-like and…

High Energy Physics - Theory · Physics 2015-06-12 Olaf Hohm , Barton Zwiebach

Current statistics literature on statistical inference of random fields typically assumes that the fields are stationary or focuses on models of non-stationary Gaussian fields with parametric/semiparametric covariance families, which may…

Statistics Theory · Mathematics 2024-09-04 Yunyi Zhang , Zhou Zhou

A generator of spatio-temporal pseudo-random Gaussian fields that satisfy the "proportionality of scales" property (Tsyroulnikov, 2001) is presented. The generator is based on a third-order in time stochastic differential equation with a…

Data Analysis, Statistics and Probability · Physics 2018-05-15 Michael Tsyrulnikov , Dmitry Gayfulin

We propose an extension of the numerical approach for integrable Richardson-Gaudin models based on a new set of eigenvalue-based variables. Starting solely from the Gaudin algebra, the approach is generalized towards the full class of XXZ…

Statistical Mechanics · Physics 2015-04-08 Pieter W. Claeys , Stijn De Baerdemacker , Mario Van Raemdonck , Dimitri Van Neck

Continuing the analysis undertaken in previous articles, we discuss some features of non-self-adjoint operators and sesquilinear forms which are defined starting from two biorthogonal families of vectors, like the so-called generalized…

Mathematical Physics · Physics 2018-04-04 Fabio Bagarello , Hiroshi Inoue , Camillo Trapani

In a broad and fundamental type of ''inverse problems'' in science, one infers a spatially distributed physical attribute based on observations of processes that are controlled by the spatial attribute in question. The data-generating field…

Methodology · Statistics 2014-09-09 Zepu Zhang

In this paper, we investigate the spectral projection of density matrices in quantum field theory. With appropriate regularization, the spectral projectors of density matrices are expected to be well-defined. These projectors can be…

High Energy Physics - Theory · Physics 2025-08-29 Wu-zhong Guo

We present a family of generalized Hessian estimators of the objective using random direction stochastic approximation (RDSA) by utilizing only noisy function measurements. The form of each estimator and the order of the bias depend on the…

Machine Learning · Computer Science 2026-02-24 Soumen Pachal , Prashanth L. A. , Shalabh Bhatnagar , Avinash Achar