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The description of strongly correlated quantum many-body systems far from equilibrium presents a fundamental challenge due to the vast amount of information it requires. We introduce a generalization of the Jastrow ansatz for time-dependent…

Quantum Physics · Physics 2025-03-17 Jing Yang , Adolfo del Campo

A correlated quantum many-body method is applied to describe resonance states of atomic Bose-Einstein condensates (BEC) in a realistic shallow trap (as opposed to infinite traps commonly used). The realistic van der Waals interaction is…

Quantum Gases · Physics 2011-11-30 Sudip Kumar Haldar , Barnali Chakrabarti , Tapan Kumar Das

We propose an excited-state molecular dynamics simulation method based on variational quantum algorithms at a computational cost comparable to that of ground-state simulations. We utilize the feature that excited states can be obtained as…

Chemical Physics · Physics 2023-03-02 Hirotoshi Hirai

Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Instead, given the difference in scales at which the two…

Machine Learning · Computer Science 2022-02-22 Amol Salunkhe , Dwyer Deighan , Paul DesJardin , Varun Chandola

Quantum nuclear dynamics with wavepacket time-evolution is classically intractable and viewed as a promising avenue for quantum information processing. Here, we use an IonQ 11-qubit trapped-ion quantum computer, Harmony, to study the…

Quantum Physics · Physics 2024-12-05 Anurag Dwivedi , A. J. Rasmusson , Philip Richerme , Srinivasan S. Iyengar

Topological phase of matter is now a mainstream of research in condensed matter physics, of which the classification, synthesis, and detection of topological states have brought excitements over the recent decade while remain incomplete…

Mesoscale and Nanoscale Physics · Physics 2018-10-26 Lin Zhang , Long Zhang , Sen Niu , Xiong-Jun Liu

Stochastic Closed-Loop Active Fault Diagnosis (CLAFD) aims to select the input sequentially in order to improve the discrimination of different models by minimizing the predicted error probability. As computation of these error…

Systems and Control · Electrical Eng. & Systems 2024-01-12 Jacques Noom , Oleg Soloviev , Carlas Smith , Michel Verhaegen

Molecular clouds show complex structures reflecting their non-linear dynamics. Many studies investigating the bridge between their morphology and physical properties have shown the value of non-Gaussian higher-order statistics in capturing…

Astrophysics of Galaxies · Physics 2025-04-30 Pablo Richard , Erwan Allys , François Levrier , Antoine Gusdorf , Constant Auclair

Dynamical systems across the sciences, from electrical circuits to ecological networks, undergo qualitative and often catastrophic changes in behavior, called bifurcations, when their underlying parameters cross a threshold. Existing…

Machine Learning · Computer Science 2024-03-22 Noa Moriel , Matthew Ricci , Mor Nitzan

This paper demonstrates the efficient extraction of unstable recurrent flows from two-dimensional turbulence by using nonlinear triads to diagnose recurrence in direct numerical simulations. Nearly recurrent episodes are identified from…

Fluid Dynamics · Physics 2024-08-12 Edward M. Redfern , Andrei L. Lazer , Dan Lucas

The interplay between matter particles and gauge fields in physical spaces with nontrivial geometries can lead to novel topological quantum matter. However, detailed microscopic mechanisms are often obscure, and unconventional spaces are…

Quantum computation (QC) and simulation rely on long-lived qubits with controllable interactions. Early work in quantum computing made use of molecules because of their readily available intramolecular nuclear spin coupling and chemical…

We develop a unified quantum geometric framework to understand reactive quantum dynamics. The critical roles of the quantum geometry of adiabatic electronic states in both adiabatic and non-adiabatic quantum dynamics are unveiled. A…

Chemical Physics · Physics 2025-05-19 Yujuan Xie , Ruoxi Liu , Bing Gu

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

Model selection in the presence of intractable likelihoods remains a central challenge in Bayesian inference. Approximate Bayesian computation (ABC) provides a flexible likelihood-free framework, but its use for model choice is known to be…

Methodology · Statistics 2026-03-03 Clara Grazian

We study the mean-field dynamics and the reduced-dimension character of two-mode Bose-Einstein condensates (BECs) in highly anisotropic traps. By means of perturbative techniques, we show that the tightly confined (transverse) degrees of…

Quantum Gases · Physics 2013-02-07 Alexandre B. Tacla , Carlton M. Caves

Nonadiabatic dynamical processes are one of the most important quantum mechanical phenomena in chemical, materials, biological, and environmental molecular systems, where the coupling between different electronic states is either inherent…

Chemical Physics · Physics 2022-05-24 Jian Liu , Xin He , Baihua Wu

Theoretical advances in the study of non-equilibrium phenomena are briefly reviewed with emphasis on steady state properties of one-dimensional driven lattice gases. The presentation is focused on the totally asymmetric simple-exclusion…

Statistical Mechanics · Physics 2008-03-19 J. G. Brankov , N. C. Pesheva , N. Zh. Bunzarova

The significance of topological phases has been widely recognized in the community of condensed matter physics. The well controllable quantum systems provide an artificial platform to probe and engineer various topological phases. The…

Quantum Physics · Physics 2018-01-01 Tenghui Wang , Zhenxing Zhang , Liang Xiang , Zhihao Gong , Jianlan Wu , Yi Yin

Approximate Bayesian Computation (ABC) is a popular method for approximate inference in generative models with intractable but easy-to-sample likelihood. It constructs an approximate posterior distribution by finding parameters for which…

Computation · Statistics 2020-03-09 Kimia Nadjahi , Valentin De Bortoli , Alain Durmus , Roland Badeau , Umut Şimşekli