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We present a method to estimate the probabilities of outcomes of a quantum observable, its mean value, and higher moments by measuring any other observable. This method is general and can be applied to any quantum system. In the case of…

Quantum Physics · Physics 2023-08-16 Dominik Šafránek , Dario Rosa

We introduce a linearized version of group field theory. It can be viewed either as a group field theory over the additive group of a vector space or as an asymptotic expansion of any group field theory around the unit group element. We…

High Energy Physics - Theory · Physics 2014-11-20 Joseph Ben Geloun , Thomas Krajewski , Jacques Magnen , Vincent Rivasseau

We elucidate the counting of the relevant small parameters in inflationary perturbation theory. Doing this allows for an explicit delineation of the domain of validity of the semi-classical approximation to gravity used in the calculation…

High Energy Physics - Theory · Physics 2018-02-21 Peter Adshead , C. P. Burgess , R. Holman , Sarah Shandera

In the latest version of the QMC model, QMC$\pi$-III-T, the density functional is improved to include the tensor component quadratic in the spin-current and a pairing interaction derived in the QMC framework. Traditional pairing strengths…

The newly derived relativistic energy density functional [\textcolor{blue}{ Phys. Rev. C \textbf{103}, 024305 (2021)}], which stems from the effective field theory motivated relativistic mean-field (E-RMF) is employed to establish the…

Nuclear Theory · Physics 2022-01-24 Jeet Amrit Pattnaik , T. M. Joshua , Ankit Kumar , M. Bhuyan , S. K. Patra

We revisit the power counting of the Higgs Effective Field Theory (HEFT) from first principles, by requiring that predictions for physical observables follow a series expansion in small, dimensionless quantities. Depending on whether HEFT…

High Energy Physics - Phenomenology · Physics 2026-04-30 Ilaria Brivio , Ramona Gröber , Konstantin Schmid

Machine learning is applied to derive microscopically parameters of the interacting boson model for nuclear spectroscopy. A physics-guided neural network is proposed, which is trained to map the potential energy landscapes that are…

Nuclear Theory · Physics 2026-05-18 Y. Obata , K. Nomura

A Fortran program for the calculation of the ground state properties of axially deformed even-even nuclei in the relativistic framework is presented. In this relativistic mean field (RMF) approach a set of coupled differential equations…

Nuclear Theory · Physics 2009-10-30 P. Ring , Y. K. Gambhir , G. A. Lalazissis

The differences between the experimental and the theoretically calculated binding energies in Relativistic Mean Field (RMF) approach have been calculated for a large number of odd-$Z$ nuclei from $A=47$ to 229. Neutron-proton (n-p)…

Nuclear Theory · Physics 2011-03-28 G. Gangopadhyay

In this work, we propose a meta-modelling technique to nuclear matter on the basis of a relativistic density functional with density-dependent couplings. Identical density dependence for the couplings both in the isoscalar and isovector…

Nuclear Theory · Physics 2023-10-31 Prasanta Char , Chiranjib Mondal , Francesca Gulminelli , Micaela Oertel

A formulation towards quantifying resource count used in a measurement, that is independent of the model of the measurement dynamics(Quantum/Classical), is considered. For any general measurement with $(M+1)$ discrete outcomes, it is found…

Quantum Physics · Physics 2014-06-16 H. M. Bharath , Saikat Ghosh

Nuclear physics can be applied in various ways to the study of neutron stars. This thesis reports on one such application, where the relativistic mean-field approximation has been employed to calculate the equations of state of matter in…

Nuclear Theory · Physics 2010-06-28 J. P. W. Diener

We study the predictions of three mean-field theoretical approaches in the description of the ground state properties of some spherical nuclei far from the stability line. We compare binding energies, single particle spectra, density…

Nuclear Theory · Physics 2015-06-04 G. Co' , V. De Donno , P. Finelli , M. Grasso , M. Anguiano , A. M. Lallena , C. Giusti , A. Meucci , F. D. Pacati

The relativistic mean-field theory provides a framework in which the nuclear many-body problem is described as a self-consistent system of nucleons and mesons. In the mean-field approximation, the self-consistent time evolution of the…

Nuclear Theory · Physics 2007-05-23 Dario Vretenar

In this work, we explore two classes of density dependent relativistic mean-field models, their predictions of proton fractions at high densities and neutron star structure. We have used a metamodelling approach to these relativistic…

Nuclear Theory · Physics 2025-02-07 Prasanta Char , Chiranjib Mondal

A simultaneous description of non-strange nuclei, hypernuclei and multiply-strange nuclear systems is provided by a single mass formula which is shown to be useful for estimating binding energies of nuclear systems over a wide mass range,…

Nuclear Theory · Physics 2015-05-18 C. Samanta

Scalar fields aptly describe equation of state of dark energy. The scalar field models were initially proposed to circumvent the fine tuning problem of cosmological constant. However, the model parameters also need a fine tuning of their…

Cosmology and Nongalactic Astrophysics · Physics 2018-06-19 Archana Sangwan , Ashutosh Tripathi , H. K. Jassal

Most parameterizations of the dark energy equation of state do not reflect realistic underlying physical models. Here, we develop a relatively simple description of dark energy based on the dynamics of a scalar field which is exact in the…

Astrophysics · Physics 2008-11-26 Robert Crittenden , Elisabetta Majerotto , Federico Piazza

Explaining observed properties in terms of underlying shape degrees of freedom is a well--established prism with which to understand atomic nuclei. Self--consistent mean--field models provide one tool to understand nuclear shapes, and their…

Nuclear Theory · Physics 2015-12-01 P. D. Stevenson , P. M. Goddard , A. Rios

This dissertation explores the topics of parameter estimation and model reduction in the context of quantum filtering. Chapters 2 and 3 provide a review of classical and quantum probability theory, stochastic calculus and filtering. Chapter…

Quantum Physics · Physics 2009-08-11 Bradley A. Chase
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