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We study two-point correlation functions of a massive free scalar field in de Sitter space using the heat kernel formalism. Focusing on two operators in conjugate static patches we derive a geodesic approximation to the two-point correlator…

High Energy Physics - Theory · Physics 2023-08-17 Lars Aalsma , Mir Mehedi Faruk , Jan Pieter van der Schaar , Manus Visser , Job de Witte

Many scientific problems require identifying a small set of covariates that are associated with a target response and estimating their effects. Often, these effects are nonlinear and include interactions, so linear and additive methods can…

Computation · Statistics 2022-12-02 Raj Agrawal , Tamara Broderick

We investigate quantum correlations in time in different approaches. We assume that temporal correlations should be treated in an even-handed manner with spatial correlations. We compare the pseudo-density matrix formalism with several…

Quantum Physics · Physics 2020-12-23 Tian Zhang , Oscar Dahlsten , Vlatko Vedral

Hagedorn functions are carefully constructed generalizations of Hermite functions to the setting of many-dimensional squeezed and coupled harmonic systems. Wavepackets formed by superpositions of Hagedorn functions have been successfully…

Quantum Physics · Physics 2025-08-18 Jiří J. L. Vaníček , Zhan Tong Zhang

The standard formulation of quantum theory assumes a predefined notion of time. This is a major obstacle in the search for a quantum theory of gravity, where the causal structure of space-time is expected to be dynamical and fundamentally…

Quantum Physics · Physics 2016-07-29 Ognyan Oreshkov , Nicolas J. Cerf

Scrambling and thermalisation are topics of intense study in both condensed matter and high energy physics. Random unitary dynamics form a simple testing-ground for our theoretical understanding of these processes. In this work, we derive…

Quantum Physics · Physics 2021-10-29 Ewan McCulloch

Using the theory of generalized hydrodynamics (GHD), we derive exact Euler-scale dynamical two-point correlation functions of conserved densities and currents in inhomogeneous, non-stationary states of many-body integrable systems with weak…

Mathematical Physics · Physics 2018-11-28 Benjamin Doyon

We put forward a functional renormalisation group approach for the direct computation of real time correlation functions, also applicable at finite temperature and density. We construct a general class of regulators that preserve the…

High Energy Physics - Phenomenology · Physics 2017-07-07 Jan M. Pawlowski , Nils Strodthoff

We explore in stochastic gravity theory whether non-Gaussian noises from the higher order correlation functions of the stress tensor for quantum matter fields when back-reacting on the spacetime may reveal hints of multi-scale structures.…

General Relativity and Quantum Cosmology · Physics 2017-09-13 B. L. Hu

We present a general formalism based on scattering theory to calculate quantum correlation functions involving several time-dependent current operators. A key ingredient is the causality of the scattering matrix, which allows one to deal…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 J. Salo , F. W. J. Hekking , J. P. Pekola

Graph-based methods pervade the inference toolkits of numerous disciplines including sociology, biology, neuroscience, physics, chemistry, and engineering. A challenging problem encountered in this context pertains to determining the…

Machine Learning · Computer Science 2018-09-25 Daniel Romero , Vassilis N. Ioannidis , Georgios B. Giannakis

Gaussian process (GP) regression provides a flexible, nonparametric framework for probabilistic modeling, yet remains computationally demanding in large-scale applications. For one-dimensional data, state space (SS) models achieve…

Machine Learning · Statistics 2025-11-07 Liang Ding , Rui Tuo , Lu Zhou

Physically motivated Gaussian process (GP) kernels for stellar variability, like the commonly used damped, driven simple harmonic oscillators that model stellar granulation and p-mode oscillations, quantify the instantaneous covariance…

Instrumentation and Methods for Astrophysics · Physics 2026-05-14 Jacob K. Luhn , Ryan A. Rubenzahl , Samuel Halverson , Lily L. Zhao

We introduce a constructive procedure that maps all spatial correlations of a broad class of states into temporal correlations between general quantum measurements. This allows us to present temporal phenomena analogous to genuinely…

Quantum Physics · Physics 2014-06-25 Marcin Markiewicz , Anna Przysiezna , Stephen Brierley , Tomasz Paterek

We compute the late-time correlation functions on three-dimensional de Sitter spacetime for a higher-spin gravity theory. For this, we elaborate on the formulation to obtain the wave functional of universe from a dual conformal field…

High Energy Physics - Theory · Physics 2023-02-22 Heng-Yu Chen , Shi Chen , Yasuaki Hikida

Gaussian processes (GPs) provide a principled and direct approach for inference and learning on graphs. However, the lack of justified graph kernels for spatio-temporal modelling has held back their use in graph problems. We leverage an…

Machine Learning · Computer Science 2024-12-30 Alexander Nikitin , ST John , Arno Solin , Samuel Kaski

The absolute/relative debate on the nature of space and time is ongoing for thousands of years. Here we attempt to investigate space and time from the information theoretic point of view to understand spatial and temporal correlations under…

Quantum Physics · Physics 2021-01-22 Tian Zhang

In this paper we present the concept of description of random processes in complex systems with the discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations…

Statistical Mechanics · Physics 2009-10-31 Renat Yulmetyev , Reter Hanggi , Fail Gafarov

The next to leading order chiral corrections to the $SU(2)\times SU(2)$ Gell-Mann-Oakes-Renner (GMOR) relation are obtained using the pseudoscalar correlator to five-loop order in perturbative QCD, together with new finite energy sum rules…

High Energy Physics - Phenomenology · Physics 2012-01-25 J. Bordes , C. A. Dominguez , P. Moodley , J. Peñarrocha , K. Schilcher

We investigate spatio-temporal event analysis using point processes. Inferring the dynamics of event sequences spatiotemporally has many practical applications including crime prediction, social media analysis, and traffic forecasting. In…

Machine Learning · Computer Science 2021-02-17 Fatih Ilhan , Suleyman Serdar Kozat