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A review of methods for finding general expressions for matrix elements (non-diagonal with respect to configurations included) of any one- and two-particle operator for an arbitrary number of shells in an atomic configuration is given.…

Atomic Physics · Physics 2007-05-23 G. Gaigalas

The tensorial form of the spin-other-orbit interaction operator in the formalism of second quantization is presented. Such an expression is needed to calculate both diagonal and off-diagonal matrix elements according to an approach, based…

Atomic Physics · Physics 2009-11-10 G. Gaigalas , A. Bernotas , Z. Rudzikas , C. Froese Fischer

A general method is described for finding algebraic expressions for matrix elements of any one- and two-particle operator for an arbitrary number of subshells in an atomic configuration, requiring neither coefficients of fractional…

Atomic Physics · Physics 2009-11-10 G. Gaigalas , Z. Rudzikas , C. Froese Fischer

A covariant hamiltonian formalism for the dynamics of compact spinning bodies in curved space-time in the test-particle limit is described. The construction allows a large class of hamiltonians accounting for specific properties and…

General Relativity and Quantum Cosmology · Physics 2016-12-21 J. W. van Holten

The alternative to the standard formulation of the quark-parton model is proposed. Our relativistically covariant approach is based on the solution of the master equations relating the structure and distribution functions, which…

High Energy Physics - Phenomenology · Physics 2007-05-23 Petr Zavada

Deformed correlated Gaussian basis functions are introduced and their matrix elements are calculated. These basis functions can be used to solve problems with nonspherical potentials. One example of such potential is the dipole…

Chemical Physics · Physics 2021-12-22 Matthew Beutel , Alexander Ahrens , Chenhang Huang , Yasuyuki Suzuki , Kalman Varga

A new formula for the heavy quark-antiquark spin dependent potential is given by using the techniques developed in the heavy quark effective theory. The leading logarithmic quark mass terms emerging from the loop contributions are…

High Energy Physics - Phenomenology · Physics 2008-11-26 Yu-Qi Chen , Yu-Ping Kuang , Robert J. Oakes

Following on from our recent work, we investigate a stochastic approach to non-equilibrium quantum spin systems. We show how the method can be applied to a variety of physical observables and for different initial conditions. We provide…

Statistical Mechanics · Physics 2020-01-24 S. De Nicola , B. Doyon , M. J. Bhaseen

We introduce stochastic variational inference for Gaussian process models. This enables the application of Gaussian process (GP) models to data sets containing millions of data points. We show how GPs can be vari- ationally decomposed to…

Machine Learning · Computer Science 2013-09-27 James Hensman , Nicolo Fusi , Neil D. Lawrence

We generalize entanglement detection with covariance matrices for an arbitrary set of observables. A generalized uncertainty relation is constructed using the covariance and commutation matrices, then a criterion is established by…

Quantum Physics · Physics 2018-06-12 Vinay Tripathi , Chandrashekar Radhakrishnan , Tim Byrnes

We present an alternative formalism for modeling spin. The ontological elements of this formalism are base-2 sequences of length $n$. The machinery necessary to model physics is then developed by considering correlations between base-2…

Quantum Physics · Physics 2022-12-15 Sam Powers , Dejan Stojkovic

We prove that the {\em gauge dependent} gluon spin, gluon and quark orbital angular momenta operators have {\em gauge invariant} expectation values on hadron states with {\em definite} momentum and polarization, therefore the conventional…

High Energy Physics - Phenomenology · Physics 2007-05-23 Xiang-Song Chen , Fan Wang

The authors of that work [Phys. Rev. D 88, 084014 (2013)], arXiv:1308.4552, derive quantum-mechanical equations valid for the covariant Dirac equation by restricting the choice of the tetrad field through the use of the "Schwinger gauge".…

General Physics · Physics 2013-12-25 Mayeul Arminjon

The integration of physical relationships into stochastic models is of major interest e.g. in data assimilation. Here, a multivariate Gaussian random field formulation is introduced, which represents the differential relations of the…

Applications · Statistics 2018-02-14 Rüdiger Hewer , Petra Friederichs , Andreas Hense , Martin Schlather

Since the discovery a century ago, spin describing the intrinsic angular momentum of massive elementary particles has exposed its nature and significant roles in wide ranges of (relativistic) quantum phenomena and practical applications for…

Quantum Physics · Physics 2016-10-12 Taeseung Choi , Sam Young Cho

We derive a formalism, the separation method, for the efficient and accurate calculation of two-body matrix elements for a Gaussian potential in the cylindrical harmonic-oscillator basis. This formalism is of critical importance for…

Nuclear Theory · Physics 2010-11-02 W. Younes

Variational approximation methods have proven to be useful for scaling Bayesian computations to large data sets and highly parametrized models. Applying variational methods involves solving an optimization problem, and recent research in…

Methodology · Statistics 2017-01-13 Victor M. -H. Ong , David J. Nott , Michael S. Smith

Accurate exchange-correlation (XC) potentials are essential for density functional theory, yet reliable approximations remain challenging for strongly correlated systems. In this work, we present a quantum algorithmic framework to determine…

Strongly Correlated Electrons · Physics 2026-03-18 H. Arslan Hashim , Volodymyr M. Turkowski , Eduardo R. Mucciolo

Extending the Gaussian covariant hydrodynamics approach [1] using torsion as an auxiliary field we formulate a fluctuating hydrodynamics with spin which is covariant with respect to pseudo-gauge transformations as well as generally…

High Energy Physics - Theory · Physics 2026-04-10 David Montenegro , Mariana Julia Pereira Dos Dores Savioli , Giorgio Torrieri

Spectral approximation and variational inducing learning for the Gaussian process are two popular methods to reduce computational complexity. However, in previous research, those methods always tend to adopt the orthonormal basis functions,…

Machine Learning · Statistics 2021-07-15 Wenqi Fang , Guanlin Wu , Jingjing Li , Zheng Wang , Jiang Cao , Yang Ping