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An approximation method which combines the perturbation theory with the variational calculation is constructed for quantum mechanical problems. Using the anharmonic oscillator and the He atom as examples, we show that the present method…

Quantum Physics · Physics 2009-10-30 Sang Koo You , Kwang Joe Jeon , Chul Koo Kim , Kyun Nahm

We develop a quantum relative entropy method for the mean-field limit of quantum many-body systems. For closed systems governed by the von Neumann equation, we prove a quantitative stability estimate between the $N$-body density matrix and…

Mathematical Physics · Physics 2026-05-12 Gaoyue Guo , Hao Liang , Zhenfu Wang

Maximum entropy inference and learning of graphical models are pivotal tasks in learning theory and optimization. This work extends algorithms for these problems, including generalized iterative scaling (GIS) and gradient descent (GD), to…

Machine Learning · Computer Science 2024-07-17 Minbo Gao , Zhengfeng Ji , Fuchao Wei

The coupled cluster method is considered a gold standard in quantum chemistry, reliably giving energies that are exact within chemical accuracy (1.6 mHartree). However, even in the CCSD approximation, where the cluster operator is truncated…

Chemical Physics · Physics 2023-03-10 Simon Elias Schrader , Simen Kvaal

This work presents a general framework for deriving exact and approximate Newton self-consistent field (SCF) orbital optimization algorithms by leveraging concepts borrowed from differential geometry. Within this framework, we extend the…

Chemical Physics · Physics 2023-09-13 Robin Feldmann , Alberto Baiardi , Markus Reiher

An ab initio approach formulated under an entropy-inspired repartitioning of the electronic Hamiltonian is presented. This ansatz produces orbital eigenvalues each shifted by entropic contributions expressed as subsets of scaled pair…

Chemical Physics · Physics 2025-06-10 Abdulrahman Y. Zamani , Kevin Carter-Fenk

In high magnetic field calculations, anisotropic Gaussian type orbital (AGTO) basis functions are capable of reconciling the competing demands of the spherically symmetric Coulombic interaction and cylindrical magnetic ($B$ field)…

Computational Physics · Physics 2018-01-17 Wuming Zhu , S. B. Trickey

In this work, we firstly investigate how to reproduce and how well one can reproduce the Woods-Saxon density distribution of initial nuclei in the framework of the improved quantum molecular dynamics model. Then, we propose a new treatment…

Nuclear Theory · Physics 2021-08-13 Junping Yang , Yingxun Zhang , Ning Wang , Zhuxia Li

Uncertainty estimation is essential for robust decision-making in the presence of ambiguous or out-of-distribution inputs. Gaussian Processes (GPs) are classical kernel-based models that offer principled uncertainty quantification and…

Machine Learning · Statistics 2026-04-30 Albert Saiapin , Kim Batselier

The variational quantum eigensolver algorithm has gained attentions due to its capability of locating the ground state and ground energy of a Hamiltonian, which is a fundamental task in many physical and chemical problems. Although it has…

Quantum Physics · Physics 2024-10-07 Trung Huynh , Gwangil An , Minsu Kim , Yu-Seong Jeon , Jinhyoung Lee

This article provides a new theory for the analysis of forward and backward particle approximations of Feynman-Kac models. Such formulae are found in a wide variety of applications and their numerical (particle) approximation are required…

Statistics Theory · Mathematics 2014-11-17 Hock Peng Chan , Pierre Del Moral , Ajay Jasra

As quantum technologies advance, the ability to generate increasingly large quantum states has experienced rapid development. In this context, the verification and estimation of large entangled systems represents one of the main challenges…

Quantum Physics · Physics 2022-03-30 Joshua Morris , Valeria Saggio , Aleksandra Gočanin , Borivoje Dakić

The quantum guesswork quantifies the minimum number of queries needed to guess the state of a quantum ensemble if one is allowed to query only one state at a time. Previous approaches to the computation of the guesswork were based on…

Quantum Physics · Physics 2023-08-28 Michele Dall'Arno , Francesco Buscemi , Takeshi Koshiba

Particle Metropolis-Hastings enables Bayesian parameter inference in general nonlinear state space models (SSMs). However, in many implementations a random walk proposal is used and this can result in poor mixing if not tuned correctly…

Computation · Statistics 2016-03-11 Johan Dahlin , Fredrik Lindsten , Thomas B. Schön

We present a Monte Carlo method for direct incorporation of nuclear inputs in primordial nucleosynthesis calculations. This method is intended to remedy shortcomings of current error estimation, by eliminating intermediate data evaluations…

Astrophysics · Physics 2009-10-31 Kenneth M. Nollett , Scott Burles

Recent advances in both theoretical and computational methods have enabled large-scale, precision calculations of the properties of atomic nuclei. With the growing complexity of modern nuclear theory, however, also comes the need for novel…

Nuclear Theory · Physics 2024-11-26 R. Y. Cheng , K. Godbey , Y. B. Niu , Y. G. Ma , W. B. He , S. M. Wang

A new theoretical approach to spin-isospin excitations in open-shell nuclei is presented. The developed method is based on the relativistic meson-exchange nuclear Lagrangian of Quantum Hadrodynamics and extends the response theory for…

Nuclear Theory · Physics 2016-08-01 Caroline Robin , Elena Litvinova

The well established macroscopic-microscopic (mac-mic) description of nuclear fission enables the prediction of fission fragment yields for a broad range of fissioning systems. In this work, we present several key enhancements to this…

Nuclear Theory · Physics 2021-03-31 Marc Verriere , Matthew R. Mumpower

The method of increments and frozen natural orbital (MI-FNO) framework is introduced to help expedite the application of noisy, intermediate-scale quantum~(NISQ) devices for quantum chemistry simulations. The MI-FNO framework provides a…

The measured relative entropies of quantum states and channels find operational significance in quantum information theory as achievable error rates in hypothesis testing tasks. They are of interest in the near term, as they correspond to…

Quantum Physics · Physics 2025-10-21 Zixin Huang , Mark M. Wilde