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Variational quantum algorithms have been proposed to solve static and dynamic problems of closed many-body quantum systems. Here we investigate variational quantum simulation of three general types of tasks---generalised time evolution with…

Quantum Physics · Physics 2020-07-01 Suguru Endo , Jinzhao Sun , Ying Li , Simon Benjamin , Xiao Yuan

We propose in this paper a quantization scheme for real Klein-Gordon field in de Sitter spacetime. Our scheme is generally covariant with the help of vierbein, which is necessary usually for spinor field in curved spacetime. We first…

High Energy Physics - Theory · Physics 2023-09-06 Sze-Shiang Feng

This paper presents a method for generating a turbulent velocity field that can be used as an input for the temporal simulation in wind excited structure problems. Temporal simulations become necessary when nonlinear behaviour, in the…

Fluid Dynamics · Physics 2023-12-15 Pascal Hémon , Françoise Santi

Although the Schr{\"o}dinger and Heisenberg pictures are equivalent formulations of quantum mechanics, simulations performed choosing one over the other can greatly impact the computational resources required to solve a problem. Here we…

Quantum Physics · Physics 2024-02-27 Dario Cilluffo , Nicola Lorenzoni , Martin B. Plenio

Multivariate spatial field data are increasingly common and whose modeling typically relies on building cross-covariance functions to describe cross-process relationships. An alternative viewpoint is to model the matrix of spectral…

Statistics Theory · Mathematics 2015-05-07 William Kleiber

A linear Gaussian state-space smoothing algorithm is presented for estimation of derivatives from a sequence of noisy measurements. The algorithm uses numerically stable square-root formulas, can handle simultaneous independent measurements…

Methodology · Statistics 2016-10-17 Robert Piche

In the framework of the theory of scale relativity, we suggest a solution to the cosmological problem of the formation and evolution of gravitational structures on many scales. This approach is based on the giving up of the hypothesis of…

Astrophysics · Physics 2015-06-24 Daniel da Rocha , Laurent Nottale

A spatial curve dynamical model framework is adopted for functional prediction of counts in a spatiotemporal log-Gaussian Cox process model. Our spatial functional estimation approach handles both wavelet-based heterogeneity analysis in…

Methodology · Statistics 2020-10-09 Torres-Signes , M. P. Frías , J. Mateu , M. D. Ruiz-Medina

Covariant phase space quantization attempts to quantize the full space of classical solutions, leading to a quantum theory in which the usual time coordinate is missing. In this paper we explore how the time evolution of the quantum states…

General Relativity and Quantum Cosmology · Physics 2022-12-15 Weixuan Hu

We consider the problem of joint estimation of structured covariance matrices. Assuming the structure is unknown, estimation is achieved using heterogeneous training sets. Namely, given groups of measurements coming from centered…

Statistics Theory · Mathematics 2016-04-20 Ilya Soloveychik , Ami Wiesel

We consider a quantization of relativistic wave equations which allows to treat quantum fields together with interacting particles at a finite time. We discuss also a dissipative interaction with the environment. We introduce a stochastic…

High Energy Physics - Theory · Physics 2007-05-23 Z. Haba

We present an efficient method for simulating a stationary Gaussian noise with an arbitrary covariance function and then study numerically the impact of time-correlated noise on the time evolution of a 1 + 1 dimensional generalized Langevin…

Statistical Mechanics · Physics 2015-11-09 Julian Schmidt , Alex Meistrenko , Hendrik van Hees , Carsten Greiner

We describe how a model of effective interactions between quantum fluctuations under certain assumptions can be constructed in a way so that the large-scale limit gives an effective theory that matches general relativity in vacuum regions.…

High Energy Physics - Theory · Physics 2025-11-11 Anna Karlsson

We study non-linear additive functionals of stationary Gaussian fields over anisotropically growing domains in $\mathbb{R}^d$, including spatiotemporal settings, and establish Gaussian and non-Gaussian limit theorems under non-separable…

Probability · Mathematics 2026-03-10 Nikolai Leonenko , Leonardo Maini , Ivan Nourdin , Francesca Pistolato

We propose a novel methodology for forecasting spatio-temporal data using supervised semi-nonnegative matrix factorization (SSNMF) with frequency regularization. Matrix factorization is employed to decompose spatio-temporal data into…

Machine Learning · Statistics 2024-06-21 Keunsu Kim , Hanbaek Lyu , Jinsu Kim , Jae-Hun Jung

This review article focuses on regularised estimation procedures applicable to geostatistical and spatial econometric models. These methods are particularly relevant in the case of big geospatial data for dimensionality reduction or model…

Methodology · Statistics 2026-04-30 Philipp Otto , Alessandro Fassò , Paolo Maranzano

We present here the first lattice simulation of symplectic quantization, a new functional approach to quantum field theory which allows to define an algorithm to numerically sample the quantum fluctuations of fields directly in Minkowski…

High Energy Physics - Lattice · Physics 2025-09-24 Martina Giachello , Francesco Scardino , Giacomo Gradenigo

The spatial mode is an essential component of an electromagnetic field description, yet it is challenging to characterize it for optical fields with low average photon number, such as in a squeezed vacuum. We present a method for…

We propose an aggregated random-field model, and investigate the scaling limits of the aggregated partial-sum random fields. In our model, each copy of the random field in the aggregation is built from two correlated one-dimensional random…

Probability · Mathematics 2019-07-29 Yi Shen , Yizao Wang

We discuss how the ideal formalism of Computational Mechanics can be adapted to apply to a non-infinite series of corrupted and correlated data, that is typical of most observed natural time series. Specifically, a simple filter that…

Statistical Mechanics · Physics 2007-05-23 Richard W. Clarke , Mervyn P. Freeman , Nicholas W. Watkins