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In this paper, we extend a method recently reported [Phys. Rev. E 87, 042921 (2012)] for the calculation of the eigestates of classically highly chaotic systems to cases of mixed dynamics, i.e. those presenting regular and irregular motions…

Quantum Physics · Physics 2017-09-13 F. Revuelta , E. Vergini , R. M. Benito , F. Borondo

The quantum state preparation of probability distributions is an important subroutine for many quantum algorithms. When embedding $D$-dimensional multivariate probability distributions by discretizing each dimension into $2^n$ points, we…

Quantum Physics · Physics 2025-06-04 Hidetaka Manabe , Yuichi Sano

Precise needle alignment is essential for percutaneous needle insertion in robotic ultrasound-guided procedures. However, inherent challenges such as speckle noise, needle-like artifacts, and low image resolution make robust needle…

Calculations are reported on the rotation-vibration energy levels of the arsine molecule with associated transition intensities. A potential energy surface (PES) obtained from \textit{ab initio} electronic structure calculations is refined…

Earth and Planetary Astrophysics · Physics 2019-02-07 Phillip A. Coles , Sergei N. Yurchenko , Richard P. Kovacich , James Hobby , Jonathan Tennyson

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamical…

Condensed Matter · Physics 2007-05-23 Karen Hallberg

We introduce a general approach for the simulation of quantum vibrational states of (symmetric and asymmetric) double-well potentials in molecules and materials for thermodynamic and spectroscopic applications. The method involves solving…

A new semiclassical "divide-and-conquer" method is presented with the aim of demonstrating that quantum dynamics simulations of high dimensional molecular systems are doable. The method is first tested by calculating the quantum vibrational…

Chemical Physics · Physics 2017-07-11 Michele Ceotto , Giovanni Di Liberto , Riccardo Conte

Quantum computers have the potential to help solve a range of physics and chemistry problems, but noise in quantum hardware currently limits our ability to obtain accurate results from the execution of quantum-simulation algorithms. Various…

Quantum Physics · Physics 2022-01-13 Eliott Rosenberg , Paul Ginsparg , Peter L. McMahon

The Density Matrix Renormalization Group (DMRG) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamic and…

Strongly Correlated Electrons · Physics 2008-11-26 Karen Hallberg

We apply the Anharmonic Oscillator Symmetry Model to the description of vibrational excitations in ${\cal D}_{3h}$ and ${\cal T}_d$ molecules. A systematic procedure can be used to establish the relation between the algebraic and…

chem-ph · Physics 2008-02-03 A. Frank , R. Lemus , R. Bijker , F. Perez-Bernal , J. M. Arias

Hybrid Tensor Networks (hTN) offer a promising solution for encoding variational quantum states beyond the capabilities of efficient classical methods or noisy quantum computers alone. However, their practical usefulness and many…

Optimal set of 1050 rovibronic energy levels for 35 triplet electronic states of $D_2$ has been obtained by means of a statistical analysis of all available wavenumbers of triplet-triplet rovibronic transitions studied in emission,…

Optics · Physics 2009-11-13 B. P. Lavrov , I. S. Umrikhin

The numerical study of anyonic systems is known to be highly challenging due to their non-bosonic, non-fermionic particle exchange statistics, and with the exception of certain models for which analytical solutions exist, very little is…

Strongly Correlated Electrons · Physics 2015-12-25 Robert N. C. Pfeifer , Sukhwinder Singh

Molecular vibrations and their dynamics are of outstanding importance for electronic and thermal transport in nanoscale devices as well as for molecular catalysis. The vibrational dynamics of <100 molecules are studied through three-colour…

The random matrix ensembles (RME) of Hamiltonian matrices, e.g. Gaussian random matrix ensembles (GRME) and Ginibre random matrix ensembles (Ginibre RME), are applicable to following quantum statistical systems: nuclear systems, molecular…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

We solve the ground state of the deuteron using a variational neural network ansatz for the wave function in momentum space. This ansatz provides a flexible representation of both the $S$ and the $D$ states, with relative errors in the…

Nuclear Theory · Physics 2024-04-19 J Rozalén Sarmiento , J W T Keeble , A Rios

The Density Matrix Renormalization Group (DMRG) algorithm is a powerful tool for solving eigenvalue problems to model quantum systems. DMRG relies on tensor contractions and dense linear algebra to compute properties of condensed matter…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Ryan Levy , Edgar Solomonik , Bryan K. Clark

We propose a new estimator of high-dimensional spectral density matrices, called UNshrunk ALgebraic Spectral Estimator (UNALSE), under the assumption of an underlying low rank plus sparse structure, as typically assumed in dynamic factor…

Statistics Theory · Mathematics 2021-04-06 Matteo Barigozzi , Matteo Farnè

The term values of all rotational levels of the $^4$He${_2}^+\,X^+\,^2\Sigma_u^+\,(\nu^+=0)$ ground vibronic state with rotational quantum number $N^+\le 19$ have been determined with an accuracy of 8 x 10$^{-4}$ cm$^{-1}$ ($\sim{25}$ MHz)…

Chemical Physics · Physics 2017-05-03 Luca Semeria , Paul Jansen , Frédéric Merkt

Tree tensor network (TTN) provides an essential theoretical framework for the practical simulation of quantum many-body systems, where the network structure defined by the connectivity of the isometry tensors plays a crucial role in…

Statistical Mechanics · Physics 2023-01-24 Toshiya Hikihara , Hiroshi Ueda , Kouichi Okunishi , Kenji Harada , Tomotoshi Nishino