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The one body density matrix, momentum distribution, natural orbits and quasi hole states of 16O and 40Ca are analyzed in the framework of the correlated basis function theory using state dependent correlations with central and tensor…

Nuclear Theory · Physics 2009-11-06 A. Fabrocini , G. Co'

Violent astrophysical events, including core-collapse supernovae and binary neutron star mergers, can result in rotating neutron stars with diverse degrees of differential rotation. Oscillation modes of these neutron stars could be excited…

High Energy Astrophysical Phenomena · Physics 2025-10-02 Anson Ka Long Yip , Patrick Chi-Kit Cheong , Tjonnie Guang Feng Li

Optically-active solid-state systems such as self-assembled quantum dots, rare-earth ions, and color centers in diamond and SiC are promising candidates for quantum network, computing, and sensing applications. Although the nuclei in these…

Quantum Physics · Physics 2026-04-07 Isabela Gnasso , Khadija Sarguroh , Dorian Gangloff , Sophia E. Economou , Edwin Barnes

We analyse a nonadiabatic self-consistent field method by means of an exactly-solvable model. The method is based on nuclear and electronic orbitals that are functions of the cartesian coordinates in the laboratory-fixed frame. The kinetic…

Quantum Physics · Physics 2012-12-27 Paolo Amore , Francisco M. Fernández

Energy Density Functionals are of major interest for the study of the atomic nucleus as, coupled with mean-field and beyond N-body approaches, they are applicable to the whole nuclear chart, including superheavy elements. On the one hand,…

Nuclear Theory · Physics 2026-01-01 G. Zietek , N. Pillet , M. Anguiano , P. Carpentier , N. Dubray , R. N. Bernard , G. Blanchon , D. Regnier

Machine learning (ML) outperforms traditional approaches in many molecular design tasks. ML models usually predict molecular properties from a 2D chemical graph or a single 3D structure, but neither of these representations accounts for the…

Computational Physics · Physics 2022-02-11 Simon Axelrod , Rafael Gomez-Bombarelli

We propose a novel quantum sensing protocol that leverages the dynamical response of physical observables to quenches in quantum systems. Specifically, we use the nitrogen-vacancy (NV) color center in diamond to realize both scalar and…

Quantum Physics · Physics 2023-07-12 Wenkui Ding , Xingyu Zhang , Jing Liu , Xiaoguang Wang

Modern machine learning (ML) models of chemical and materials systems with billions of parameters require vast training datasets and considerable computational efforts. Lightweight kernel or decision tree based methods, however, can be…

Chemical Physics · Physics 2024-10-18 Danish Khan , O. Anatole von Lilienfeld

The determination of the most stable structures of metal clusters supported at solid surfaces by computer simulations represents a formidable challenge due to the complexity of the potential-energy surface. Here we combine a…

Chemical Physics · Physics 2020-07-14 Martín Leandro Paleico , Jörg Behler

Global entanglement in quantum many-body systems is inherently nonlocal, raising the question of whether it can be inferred from local observations. We investigate this problem in monitored quantum circuits, where projective measurements…

Disordered Systems and Neural Networks · Physics 2026-03-24 Javad Vahedi , Stefan Kettemann

Orbital entropies, pair entropies, and mutual information have become popular tools for analysis of strongly correlated wave functions. They can quantitatively measure how strongly an orbital (e.g. from the DMRG active space) participates…

Chemical Physics · Physics 2025-05-19 Jiri Pittner

At the limit of an infinite confinement strength $\omega$, the ground state of a system that comprises two fermions or bosons in a harmonic confinement interacting through the Fermi--Huang pseudopotential remains strongly correlated. A…

Chemical Physics · Physics 2023-05-24 Jerzy Cioslowski , Berthold-Georg Englert , Martin-Isbjörn Trappe , Jun Hao Hue

We present a new application of the Generator Coordinate Method (GCM) as an electronic structure method for strong electron correlation in molecular systems. We identify spin fluctuations as an important generator coordinate responsible for…

Chemical Physics · Physics 2025-03-18 Amir Ayati , Hugh G. A. Burton , Patrick Bultinck , Stijn De Baerdemacker

Learning the structure--dynamics correlation in disordered systems is a long-standing problem. Here, we use unsupervised machine learning employing graph neural networks (GNN) to investigate the local structures in disordered systems. We…

Disordered Systems and Neural Networks · Physics 2022-06-28 Vaibhav Bihani , Sahil Manchanda , Sayan Ranu , N. M. Anoop Krishnan

A molecule's geometry, also known as conformation, is one of a molecule's most important properties, determining the reactions it participates in, the bonds it forms, and the interactions it has with other molecules. Conventional…

Machine Learning · Computer Science 2020-01-01 Elman Mansimov , Omar Mahmood , Seokho Kang , Kyunghyun Cho

We recently derived a spin-mapping approach for treating the nonadiabatic dynamics of a two-level system in a classical environment [J. Chem. Phys. 151, 044119 (2019)] based on the well-known quantum equivalence between a two-level system…

Chemical Physics · Physics 2020-03-03 Johan E. Runeson , Jeremy O. Richardson

Multi-configurational approaches yield universal wave function parameterizations that can qualitatively well describe electronic structures along reaction pathways. For quantitative results, multi-reference perturbation theory is required…

Chemical Physics · Physics 2016-09-08 Christopher J. Stein , Vera von Burg , Markus Reiher

The natural orbitals and natural occupation numbers of various N = Z, sp and sd shell nuclei are calculated by applying a correlated one-body density matrix. The correlated density matrix has been evaluated by considering central…

Nuclear Theory · Physics 2013-08-21 V. P. Psonis , Ch. C. Moustakidis , S. E. Massen

Surface-adsorbed rare-earth nanostructures are ideal platforms to investigate the interplay between intra-atomic interactions and multi-orbital spin configurations. However, addressing these properties has posed severe experimental and…

The magnetic fields generated by spins and currents provide a unique window into the physics of correlated-electron materials and devices. Proposed only a decade ago, magnetometry based on the electron spin of nitrogen-vacancy (NV) defects…

Strongly Correlated Electrons · Physics 2018-04-25 Francesco Casola , Toeno van der Sar , Amir Yacoby
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