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Related papers: Computing the QRPA Level Density with the Finite A…

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We propose an effectively nonperturbative approach to calculating scattering amplitudes in the perturbative regime. We do this in a discretized momentum space by using the QSE method to calculate all the contributions (to all orders in…

High Energy Physics - Phenomenology · Physics 2018-07-20 Neil Christensen , Joshua Henderson , Santiago Pinto , Cory Russ

The microscopic calculation of nuclear level densities in the presence of correlations is a difficult many-body problem. The shell model Monte Carlo method provides a powerful technique to carry out such calculations using the framework of…

Nuclear Theory · Physics 2013-05-27 Y. Alhassid , C. Özen , H. Nakada

We describe a new implementation of the quasiparticle random phase approximation (QRPA) in axially-symmetric deformed nuclei with Skyrme and volume-pairing energy-density functionals. After using a variety of tests to demonstrate the…

Nuclear Theory · Physics 2014-11-21 J. Terasaki , J. Engel

The modern form of the Moments Method applied to the calculation of the nuclear shell-model level density is explained and examples of the method at work are given. The calculated level density practically exactly coincides with the result…

Nuclear Theory · Physics 2016-01-27 V. Zelevinsky , M. Horoi , R. A. Sen'kov

Finite-volume pionless effective field theory provides an efficient framework for the extrapolation of nuclear spectra and matrix elements calculated at finite volume in lattice QCD to infinite volume, and to nuclei with larger atomic…

Nuclear Theory · Physics 2022-02-28 Xiangkai Sun , William Detmold , Di Luo , Phiala E. Shanahan

The iterative quasi-particle-random-phase approximation (QRPA) method we previously developed to accurately calculate properties of individual nuclear states is extended so that it can be applied for nuclei with odd numbers of neutrons and…

Nuclear Theory · Physics 2014-06-03 B. G. Carlsson , J. Toivanen

In finite mixture models, apart from underlying mixing measure, true kernel density function of each subpopulation in the data is, in many scenarios, unknown. Perhaps the most popular approach is to choose some kernel functions that we…

Statistics Theory · Mathematics 2017-09-26 Nhat Ho , XuanLong Nguyen , Ya'acov Ritov

The momentum and density dependence of mean fields in symmetric and asymmetric nuclear matter are analysed using the simple density dependent finite range effective interaction containing a single Gaussian term alongwith the zero-range…

Nuclear Theory · Physics 2015-06-11 T. R. Routray , X. Vinas , S. K. Tripathy , M. Bhuyan , S. K. Patra , B. Behera

We propose an accurate and efficient method to compute vibrational spectra of molecules, based on exact diagonalization of an algebraically calculated matrix based on powers of Morse coordinate. The present work focuses on the 1D potential…

Chemical Physics · Physics 2009-11-13 Andrea Bordoni , Nicola Manini

We measure molecular vibrations with femtometer precision using time-resolved x-ray absorption spectroscopy. For a demonstration, a Raman process excites the A$_{1g}$ mode in gas-phase SF$_6$ molecules with an amplitude of $\approx50$ fm,…

Estimation of quantum states is one of the most important steps in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not…

Quantum Physics · Physics 2016-08-24 Harpreet Singh , Arvind , Kavita Dorai

Accurately simulating molecular vibronic spectra remains computationally challenging due to the exponential scaling of required calculations. Here, we show that employing the linear coupling model within the gaussian boson sampling…

Quantum Physics · Physics 2025-08-07 I. Konyshev , R. Pradip , O. Page , C. Ünlüer , R. T. Nasibullin , V. V. Rybkin , W. Pernice , S. Ferrari

An infinitely wide model is a weighted integration $\int \varphi(x,v) d \mu(v)$ of feature maps. This model excels at handling an infinite number of features, and thus it has been adopted to the theoretical study of deep learning. Kernel…

Machine Learning · Statistics 2020-07-08 Sho Sonoda

Studying the response of quantum systems is essential for gaining deeper insights into the fundamental nature of matter and its behavior in diverse physical contexts. Computation of nuclear response is critical for many applications, but…

Nuclear Theory · Physics 2024-05-06 John Novak , Manqoba Q. Hlatshwayo , Elena Litvinova

It is possible to employ virtual decay paths, including two-particle transfer, to calculate the nuclear matrix element of neutrinoless double-beta decay under the closure approximation, in addition to the true double-beta path. In the…

Nuclear Theory · Physics 2016-03-02 Jun Terasaki

Kernel density estimation (KDE) is one of the most widely used nonparametric density estimation methods. The fact that it is a memory-based method, i.e., it uses the entire training data set for prediction, makes it unsuitable for most…

Machine Learning · Computer Science 2022-08-08 Joseph A. Gallego , Juan F. Osorio , Fabio A. González

We discuss properties of the quadrupole collective excitation of the deformed neutron-rich nucleus $^{38}$Mg within the framework of quasi-particle random phase approximation (QRPA). We first solve the coupled-channels equations to obtain…

Nuclear Theory · Physics 2015-06-26 K. Hagino , Nguyen Van Giai , H. Sagawa

We use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model to examine the likely performance of variational quantum eigensolvers in nuclear-structure theory. The LMG model exhibits both a phase transition and…

Nuclear Theory · Physics 2022-06-30 A. M. Romero , J. Engel , Ho Lun Tang , Sophia E. Economou

In bulk quantum computation one can manipulate a large number of indistinguishable quantum computers by parallel unitary operations and measure expectation values of certain observables with limited sensitivity. The initial state of each…

Quantum Physics · Physics 2009-10-30 Emanuel Knill , Isaac Chuang , Raymond Laflamme

We present a high order perturbation approach to quantitatively calculate spectral densities in three distinct steps starting from the model Hamiltonian and the observables of interest. The approach is based on the perturbative continuous…

Strongly Correlated Electrons · Physics 2009-11-10 Christian Knetter , Kai P. Schmidt , Götz S. Uhrig