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A computer code for quasiparticle random phase approximation-QRPA and projected quasiparticle random phase approximation-PQRPA models of nuclear structure is explained in details. An important application of the code consists in evaluating…

Nuclear Theory · Physics 2010-04-22 F. Krmpotic , A. R. Samana , C. A. Bertulani

Theoretical studies of low-lying dipole strength in even-even spherical nuclei within the relativistic quasiparticle time blocking approximation (RQTBA) are presented. The RQTBA developed recently as an extension of the self-consistent…

Nuclear Theory · Physics 2009-08-03 E. Litvinova , P. Ring , V. Tselyaev , K. Langanke

Relativistic Continuum Random Phase Approximation (CRPA) is used to investigate collective excitation phenomena in several spherical nuclei along the periodic table. We start from relativistic mean field calculations based on a covariant…

Nuclear Theory · Physics 2011-03-21 J. Daoutidis , P. Ring

We show that, within the Quasiparticle Random Phase Approximation (QRPA) and the renormalized QRPA (RQRPA) based on the Bonn CD nucleon-nucleon interaction, the competition between the pairing and the neutron-proton particle-particle and…

Nuclear Theory · Physics 2008-11-26 Fedor Simkovic , Amand Faessler , Vadim Rodin , Petr Vogel , Jonathan Engel

The explicit evaluation of linear response coefficients for interacting many-particle systems still poses a considerable challenge to theoreticians. In this work we use a novel many-particle renormalization technique, the so-called…

Strongly Correlated Electrons · Physics 2015-06-18 Van-Nham Phan , Klaus W. Becker , Holger Fehske

We develop a new framework of the deformed quasiparticle-random-phase approximation (QRPA) where the Skyrme density functional and the density-dependent pairing functional are consistently treated. Numerical applications are carried out for…

Nuclear Theory · Physics 2009-11-23 Kenichi Yoshida , Nguyen Van Giai

The nuclear matrix elements $M^{0\nu}$ of the neutrinoless double beta decay ($0\nu\beta\beta$) of most nuclei with known $2\nu\beta\beta$-decay rates are systematically evaluated using the Quasiparticle Random Phase Approximation (QRPA)…

Nuclear Theory · Physics 2007-05-23 V. A. Rodin , Amand Faessler , F. Šimkovic , Petr Vogel

A survey is presented of the theoretical status of quadratic response theories for the understanding of nonlinear aspects in the interaction of charged particles with matter. In the frame of the many-body perturbation theory we study the…

Materials Science · Physics 2007-05-23 J. M. Pitarke , I. Campillo

The random phase approximation (RPA) has received a considerable interest in the field of modeling systems where noncovalent interactions are important. Its advantages over widely used density functional theory (DFT) approximations are the…

Chemical Physics · Physics 2019-12-04 Marcin Modrzejewski , Sirous Yourdkhani , Jiri Klimes

Force-based multiphysics coupling methods have become popular since they provide a simple and efficient coupling mechanism, avoiding the difficulties in formulating and implementing a consistent coupling energy. They are also the only known…

Numerical Analysis · Mathematics 2011-04-12 Mitchell Luskin , Christoph Ortner

Exact results of pair transfer probabilities for the Richardson model with equidistant or random level spacing are presented. The results are then compared either to particle-particle random phase approximation (ppRPA) in the normal phase…

Nuclear Theory · Physics 2015-06-11 Danilo Gambacurta , Denis Lacroix

Linear response (LR) is an important tool in the computational chemist's toolbox. It is therefore no surprise that the emergence of quantum computers has led to a quantum version, quantum LR (qLR). However, the current quantum era of…

We study the reliability of the constrained random phase approximation (cRPA) method for the calculation of low-energy effective Hamiltonians by considering multi-orbital lattice models with one strongly correlated "target" band and two…

Strongly Correlated Electrons · Physics 2015-07-24 Hiroshi Shinaoka , Matthias Troyer , Philipp Werner

To study shape fluctuations of nuclei in transitional regions, the collective Hamiltonian method has often been employed. We intend to construct the quadrupole collective Hamiltonian with the collective inertial functions given by the local…

Nuclear Theory · Physics 2019-01-30 Kouhei Washiyama , Takashi Nakatsukasa

Radio-Frequency Quadrupoles (RFQs) are multi-purpose linear particle accelerators that simultaneously bunch and accelerate charged particle beams. They are ubiquitous in accelerator physics, especially as injectors to higher-energy…

Computational Physics · Physics 2024-03-18 Joshua Villarreal , Daniel Winklehner , Daniel Koser , Janet Marie Conrad

We start from the QED Lagrangian to describe a charged many-particle system coupled to the radiation field. A covariant density matrix approach to kinetic theory of QED plasmas, subjected to a strong external electro-magnetic field has…

Quantum Physics · Physics 2009-11-07 A. Hoell , V. G. Morozov , G. Roepke

The variances and covariances associated to the nuclear matrix elements (NME) of neutrinoless double beta decay are estimated within the quasiparticle random phase approximation (QRPA). It is shown that correlated NME uncertainties play an…

High Energy Physics - Phenomenology · Physics 2009-11-06 Amand Faessler , G. L. Fogli , E. Lisi , V. Rodin , A. M. Rotunno , F. Simkovic

A new Quasiparticle Random Phase Approximation approach is presented. The corresponding ground state is variationally determined and exhibits a minimum energy. New solutions for the ground state, some with spontaneously broken symmetry, of…

Nuclear Theory · Physics 2008-11-26 F. Simkovic , M. Smotlak , A. A. Raduta

The five-dimensional quadrupole collective model based on energy density functionals (EDF) has often been employed to treat long-range correlations associated with shape fluctuations in nuclei. Our goal is to derive the collective inertial…

Nuclear Theory · Physics 2017-11-08 Kouhei Washiyama , Takashi Nakatsukasa

We call matrix algorithms superfast if they use much fewer flops and memory cells than the input matrix has entries. Using such algorithms is indispensable for Big Data Mining and Analysis, where the input matrices are so immense that one…

Numerical Analysis · Mathematics 2025-01-17 Victor Y. Pan , John Svadlenka