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In previous papers, we have investigated the classical theory of Barut and Zanghi (BZ) for the electron spin [which interpreted the Zitterbewegung (zbw) motion as an internal motion along helical paths], and its "quantum" version, by using…

High Energy Physics - Theory · Physics 2017-12-19 Erasmo Recami , Giovanni Salesi

The canonical structure of theories whose Lagrangian contains higher powers of time derivatives is often obscured by the nonlinear relationship between the velocities and momenta. We use the Dirac formalism and define a generalized Legendre…

High Energy Physics - Theory · Physics 2015-06-18 Eran Avraham , Ram Brustein

Symplectic unitary representations for the Poincar\'{e} group are studied. The formalism is based on the noncommutative structure of the star-product, and using group theory approach as a guide, a consistent physical theory in phase space…

Mathematical Physics · Physics 2016-03-30 R. G. G. Amorim , S. C. Ulhoa , Edilberto O. Silva

A physics informed neural network (PINN) incorporates the physics of a system by satisfying its boundary value problem through a neural network's loss function. The PINN approach has shown great success in approximating the map between the…

Numerical Analysis · Mathematics 2022-03-17 Revanth Mattey , Susanta Ghosh

We establish improved uniform error bounds on time-splitting methods for the long-time dynamics of the Dirac equation with small electromagnetic potentials characterized by a dimensionless parameter $\varepsilon\in (0, 1]$ representing the…

Numerical Analysis · Mathematics 2021-12-08 Weizhu Bao , Yue Feng , Jia Yin

We derive an equivalent traveling wave form description for Dirac field. In the non-relativistic limit, such form can reduce to inverse-Galilean transformed Schrodinger-type equation. We find that, the resulting two-component…

Quantum Physics · Physics 2022-03-18 Fei Wang

As artificial intelligence (AI) advances into diverse applications, ensuring reliability of AI models is increasingly critical. Conventional neural networks offer strong predictive capabilities but produce deterministic outputs without…

We study normal diffusive and subdiffusive processes in a harmonic potential (Ornstein-Uhlenbeck process) on a uniformly growing/contracting domain. Our starting point is a recently derived fractional Fokker-Planck equation, which covers…

Statistical Mechanics · Physics 2019-07-31 F. Le Vot , S. B. Yuste , E. Abad

Computing the partition function, $Z$, of an Ising model over a graph of $N$ \enquote{spins} is most likely exponential in $N$. Efficient variational methods, such as Belief Propagation (BP) and Tree Re-Weighted (TRW) algorithms, compute…

Machine Learning · Computer Science 2024-11-14 Hamidreza Behjoo , Michael Chertkov

Diagnosis and prediction in some domains, like medical and industrial diagnosis, require a representation that combines uncertainty management and temporal reasoning. Based on the fact that in many cases there are few state changes in the…

Artificial Intelligence · Computer Science 2013-01-30 Gustavo Arroyo-Figueroa , Luis Enrique Sucar

We present a Parametrization of the Physics Informed Neural Network (P-PINN) approach to tackle the problem of uncertainty quantification in reservoir engineering problems. We demonstrate the approach with the immiscible two phase flow…

Computational Engineering, Finance, and Science · Computer Science 2022-05-26 Cedric Fraces Gasmi , Hamdi Tchelepi

We propose a new binary classification model called Phase Separation Binary Classifier (PSBC). It consists of a discretization of a nonlinear reaction-diffusion equation coupled with an Ordinary Differential Equation, and is inspired by…

Machine Learning · Statistics 2021-09-21 Rafael Monteiro

In the realm of relativistic quantum mechanics, we address a fundamental question: Which one, between the Dirac or the Foldy-Wouthuysen density, accurately provide a probability density for finding a massive particle with spin $1/2$ at a…

Quantum Physics · Physics 2025-01-14 Taeseung Choi , Yeong Deok Han

A physics-informed convolutional neural network is proposed to simulate two phase flow in porous media with time-varying well controls. While most of PICNNs in existing literatures worked on parameter-to-state mapping, our proposed network…

Machine Learning · Computer Science 2024-10-24 Jungang Chen , Eduardo Gildin , John E. Killough

In one-dimensional systems, the dynamics of a Brownian particle are governed by the force derived from a potential as well as by diffusion properties. In this work, we obtain the first-passage-time statistics of a Brownian particle driven…

Statistical Mechanics · Physics 2015-11-25 Eugenio Urdapilleta

One of the most popular time-frequency representation is certainly the Wigner distribution. To reduce the interferences coming from its quadratic nature, several related distributions have been proposed, among which the so-called…

Functional Analysis · Mathematics 2018-03-23 Elena Cordero , Maurice de Gosson , Fabio Nicola

We present a significant improvement to a time-dependent WKB (TDWKB) formulation developed by Boiron and Lombardi [JCP {\bf108}, 3431 (1998)] in which the TDWKB equations are solved along classical trajectories that propagate in the complex…

Quantum Physics · Physics 2009-11-13 Yair Goldfarb , Jeremy Schiff , David J Tannor

The Dirac equation is a cornerstone in the history of physics, merging successfully quantum mechanics with special relativity, providing a natural description of the electron spin and predicting the existence of anti-matter. Furthermore, it…

Quantum Physics · Physics 2010-01-08 R. Gerritsma , G. Kirchmair , F. Zähringer , E. Solano , R. Blatt , C. F. Roos

The Weyl-Wigner formalism for evaluating the intrinsic information of Dirac bispinors as correlated qubits (localized) in a magnetic field is investigated in the extension to statistical ensembles. The confining external field quantizes the…

Quantum Physics · Physics 2024-02-01 C. F. Silva , A. E. Bernardini

Oscillations are ubiquitous wave phenomena in physical systems ranging from electromagnetic and acoustic to gravitational waves. The behavior of finite-size systems is traditionally understood to be governed by fundamental oscillatory modes…