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Quantum simulators have made a remarkable progress towards exploring the dynamics of many-body systems, many of which offer a formidable challenge to both theoretical and numerical methods. While state-of-the-art quantum simulators are in…

We present a method for approximating the many-body density of states of a system of quantum identical particles, with a reduction of the computational cost by a combinatorial factor compared to the full calculation. This is carried out by…

Quantum Physics · Physics 2026-05-05 Hovan Lee , Rémi Lefèvre , Grégoire Ithier

Here we present a many-body theory based on a solution of the $N$-representability problem in which the ground-state two-particle reduced density matrix (2-RDM) is determined directly without the many-particle wave function. We derive an…

Quantum Physics · Physics 2023-04-19 David A. Mazziotti

The goal of this presentation is to highlight various computational techniques used to study dynamics of quantum many-body systems. We examine the projection and variable phase methods being applied to multi-channel problems of scattering…

Nuclear Theory · Physics 2014-12-22 Alexander Volya

In this paper, we introduce a new scheme for the efficient numerical treatment of the electronic Schr\"odinger equation for molecules. It is based on the combination of a many-body expansion, which corresponds to the so-called bond order…

Numerical Analysis · Mathematics 2017-07-20 Sambasiva Rao Chinnamsetty , Michael Griebel , Jan Hamaekers

The length and time scales of atomistic simulations are limited by the computational cost of the methods used to predict material properties. In recent years there has been great progress in the use of machine learning algorithms to develop…

Computational Physics · Physics 2022-11-03 Alberto Hernandez , Adarsh Balasubramanian , Fenglin Yuan , Simon Mason , Tim Mueller

This paper is concerned with the Taylor-reduced basis method (Taylor-RBM) for the efficient approximation of eigenspaces of large scale parametric Hermitian matrices. The Taylor-RBM is a local model order reduction method, which constructs…

Numerical Analysis · Mathematics 2026-03-31 Benjamin Stamm , Zhuoyao Zeng

We present a method for efficient differentiable simulation of articulated bodies. This enables integration of articulated body dynamics into deep learning frameworks, and gradient-based optimization of neural networks that operate on…

Machine Learning · Computer Science 2021-09-17 Yi-Ling Qiao , Junbang Liang , Vladlen Koltun , Ming C. Lin

The use of model-based numerical simulation of wave propagation in rooms for engineering applications requires that acoustic conditions for multiple parameters are evaluated iteratively and this is computationally expensive. We present a…

The first practical method to evolve many-body nuclear forces to softened form using the Similarity Renormalization Group (SRG) in a harmonic oscillator basis is demonstrated. When applied to He4 calculations, the two- and three-body…

Nuclear Theory · Physics 2009-09-02 E. D. Jurgenson , P. Navratil , R. J. Furnstahl

Fitting parametric models of human bodies, hands or faces to sparse input signals in an accurate, robust, and fast manner has the promise of significantly improving immersion in AR and VR scenarios. A common first step in systems that…

Computer Vision and Pattern Recognition · Computer Science 2022-07-22 Vasileios Choutas , Federica Bogo , Jingjing Shen , Julien Valentin

In this contribution, we are concerned with model order reduction in the context of iterative regularization methods for the solution of inverse problems arising from parameter identification in elliptic partial differential equations. Such…

Numerical Analysis · Mathematics 2024-10-14 Michael Kartmann , Tim Keil , Mario Ohlberger , Stefan Volkwein , Barbara Kaltenbacher

We investigate a projection-based reduced-order model of the steady incompressible Navier-Stokes equations for moderate Reynolds numbers. In particular, we construct an "embedded" reduced basis space, by applying proper orthogonal…

Numerical Analysis · Mathematics 2020-08-26 Efthymios N. Karatzas , Giovanni Stabile , Leo Nouveau , Guglielmo Scovazzi , Gianluigi Rozza

This programmatic paper lays down the possibility to reconcile the necessity to resum many-body correlations into the energy kernel with the fact that safe multi-reference energy density functional (EDF) calculations cannot be achieved…

Nuclear Theory · Physics 2016-01-27 T. Duguet , M. Bender , J. -P. Ebran , T. Lesinski , V. Somà

We present a method based on hyperspherical harmonics to solve the nuclear many-body problem. It is an extension of accurate methods used for studying few-body systems to many bodies and is based on the assumption that nucleons in nuclei…

Nuclear Theory · Physics 2009-11-10 M. Fabre de la Ripelle , S. A. Sofianos , R. M. Adam

The ground state energy of a many-electron system can be approximated by an variational approach in which the total energy of the system is minimized with respect to one and two-body reduced density matrices (RDM) instead of many-electron…

Optimization and Control · Mathematics 2017-09-01 Yongfeng Li , Zaiwen Wen , Chao Yang , Yaxiang Yuan

We use the recently introduced single-particle states obtained from localized Deuteron wave-functions as a basis for nuclear many-body calculations. We show that energies can be substantially lowered if the natural orbits obtained from this…

Nuclear Theory · Physics 2018-05-23 Giovanni Puddu

Broad resonances are a unique phenomenon in nuclear many-body systems. Theoretical studies usually involve the continuum degree of freedom, which drastically increases the model space of calculations, and may lead to non-convergence or…

Nuclear Theory · Physics 2025-12-23 Rongzhe Hu , Nicolas Michel , Zhicheng Xu , Jianguo Li , Furong Xu

In this work we propose an efficient and accurate multi-scale optical simulation algorithm by applying a numerical version of slowly varying envelope approximation in FEM. Specifically, we employ the fast iterative method to quickly compute…

Optics · Physics 2024-12-03 Fan Xiao , Jingwei Wang , Zhongfei Xiong , Yuntian Chen

We present a variational Monte Carlo method that solves the nuclear many-body problem in the occupation number formalism exploiting an artificial neural network representation of the ground-state wave function. A memory-efficient version of…