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In the present paper we perfomrm molecular dynamics simulation of liquid carbon with a machine-learning potential GAP-20. We show that within the framework of this model carbon demonstrates a relatively low critical temperature, which can…

Soft Condensed Matter · Physics 2026-03-02 Yu. D. Fomin

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

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab-initio calculations) and at speeds suitable for molecular dynam- ics simulation. Best…

Computational Physics · Physics 2017-05-03 G. Ferré , T. Haut , K. Barros

We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary…

We present the quantum mechanics of "partial-trace" non-linear sigma models, on the grounds of a fully symmetry-based procedure. After the general scheme is sketched, the particular example of a particle on the two-sphere is explicitly…

High Energy Physics - Theory · Physics 2010-10-28 V. Aldaya , M. Calixto , J. Guerrero , F. F. López-Ruiz

The structure of finite nuclei is investigated by employing an interaction model which is based on the low-momentum interaction $V_{lowk}$. It is supplemented by a density-dependent contact interaction fitted to reproduce the saturation…

Nuclear Theory · Physics 2015-06-19 E. N. E. van Dalen , H. Müther

Using a quantum processor to embed and process classical data enables the generation of correlations between variables that are inefficient to represent through classical computation. A fundamental question is whether these correlations…

Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has use cases in chemistry, biology, and medicine. In the past decade, the advent of machine learning…

Chemical Physics · Physics 2022-08-23 Sajjad Heydari , Stefano Raniolo , Lorenzo Livi , Vittorio Limongelli

A fully relativistic finite nucleus wave-function approach to the non-mesonic weak decay of the ${_\Lambda^{12} C}$ hypernucleus is presented. The model is based on the calculation of the amplitudes of the tree-level Feynman diagrams for…

Nuclear Theory · Physics 2015-03-13 Francesco Conti , Andrea Meucci , Carlotta Giusti. Franco Davide Pacati

Recent results from RIKEN/RIBF on the low-lying level structure of 29F are interpreted within the Particle-Rotor Model. We show that the experimental data can be understood in the Rotation-aligned Coupling Scheme, with the 5/2+ ground state…

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification…

Computer Vision and Pattern Recognition · Computer Science 2014-05-05 Joshua C. Chang , Tom Chou

The low-energy structure of 231Ac has been investigated by means of gamma ray spectroscopy following the beta-decay of 231Ra. Multipolarities of 28 transitions have been established by measuring conversion electrons with a mini-orange…

Nowadays, the coupling of electronic structure and machine learning techniques serves as a powerful tool to predict chemical and physical properties of a broad range of systems. With the aim of improving the accuracy of predictions, a large…

The potential-energy surfaces of an extended set of heavy and super-heavy even-even nuclei with $92 \le Z \le 126$ and isospins $40 \le N-Z \le 74$ are evaluated within the recently developed Fourier shape parametrization. Ground-state and…

Nuclear Theory · Physics 2018-03-28 K. Pomorski , B. Nerlo-Pomorska , J. Bartel , C. Schmitt

The nucleation of carbon caps on small nickel clusters is studied using a tight binding model coupled to grand canonical Monte Carlo simulations. It takes place in a well defined carbon chemical potential range, when a critical…

Materials Science · Physics 2009-11-13 Hakim Amara , Christophe Bichara , François Ducastelle

We investigate even-even nuclei in the $A\sim70$ mass region within the framework of the proton-neutron quasi-particle random phase approximation (\mbox{pn-QRPA}) and the interacting boson model-1 (\mbox{IBM-1}). Our work includes…

Nuclear Theory · Physics 2016-03-02 Jameel-Un Nabi , Mahmut Böyükata

The convergence of no-core shell model (NCSM) calculations using renormalization group evolved low-momentum two-nucleon interactions is studied for light nuclei up to Li-7. Because no additional transformation was used in applying the NCSM…

Nuclear Theory · Physics 2008-11-26 S. K. Bogner , R. J. Furnstahl , P. Maris , R. J. Perry , A. Schwenk , J. P. Vary

CAlcium fluoride for the study of Neutrinos and Dark matters by Low-energy Spectrometer (CANDLES) searches for neutrino-less double beta decay of $^{48}$Ca using a CaF$_2$ scintillator array. A high Q-value of $^{48}$Ca at 4,272 keV enabled…

Angular-momentum-projected energy surface calculations for A~110 nuclei indicate three distinct energy minima occurring at different angular-momenta. These correspond to normal, super-, and hyper-deformed shapes coexisting in one nucleus.…

Nuclear Theory · Physics 2008-02-01 Yang Sun , Jing-ye Zhang , Gui-Lu Long , Cheng-Li Wu

Macroscopic models of nucleation provide powerful tools for understanding activated phase transition processes. These models do not provide atomistic insights and can thus sometime lack material-specific descriptions. Here we provide a…

Statistical Mechanics · Physics 2020-02-19 Bingqing Cheng , Michele Ceriotti , Gareth A. Tribello