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Related papers: Advanced switching schemes in a Stark decelerator

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Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each…

Statistical Mechanics · Physics 2017-04-07 Emilio Flores-Sola , Martin Weigel , Ralph Kenna , Bertrand Berche

To promote the global search ability of the original state transition algorithm, a new operator called axesion is suggested, which aims to search along the axes and strengthen single dimensional search. Several benchmark minimization…

Optimization and Control · Mathematics 2012-10-15 Xiaojun Zhou , Chunhua Yang , Weihua Gui

A conceptual model for microscopic-macroscopic slow-fast stochastic systems is considered. A dynamical reduction procedure is presented in order to extract effective dynamics for this kind of systems. Under appropriate assumptions, the…

Probability · Mathematics 2010-11-15 Jian Ren , Hongbo Fu , Daomin Cao , Jinqiao Duan

Controlling complex dynamical systems has been a topic of considerable interest in academic circles in recent decades. While existing works have primarily focused on closed-loop control schemes with infinite-time durations, this paper…

Optimization and Control · Mathematics 2025-01-08 Xiaoxiao Peng , Shijie Zhou

This paper addresses the question of whether it can be beneficial for an optimization algorithm to follow directions of negative curvature. Although prior work has established convergence results for algorithms that integrate both descent…

Optimization and Control · Mathematics 2018-04-05 Frank E. Curtis , Daniel P. Robinson

Stochastic variance reduced optimization methods are known to be globally convergent while they suffer from slow local convergence, especially when moderate or high accuracy is needed. To alleviate this problem, we propose an optimization…

Optimization and Control · Mathematics 2021-11-15 Hamed Sadeghi , Pontus Giselsson

Today's massively-sized datasets have made it necessary to often perform computations on them in a distributed manner. In principle, a computational task is divided into subtasks which are distributed over a cluster operated by a…

Information Theory · Computer Science 2017-06-20 Wael Halbawi , Navid Azizan-Ruhi , Fariborz Salehi , Babak Hassibi

A system of trapped ions under the action of off--resonant standing--waves can be used to simulate a variety of quantum spin models. In this work, we describe theoretically quantum phases that can be observed in the simplest realization of…

Quantum Physics · Physics 2009-11-11 X. -L. Deng , D. Porras , J. I. Cirac

We develop new more efficient A-WENO schemes for both hyperbolic systems of conservation laws and nonconservative hyperbolic systems. The new schemes are a very simple modification of the existing A-WENO schemes: They are obtained by a more…

Numerical Analysis · Mathematics 2025-05-26 Shaoshuai Chu , Alexander Kurganov , Ruixiao Xin

The ``fast iterative shrinkage-thresholding algorithm'', a.k.a. FISTA, is one of the most widely used algorithms in the literature. However, despite its optimal theoretical $O(1/k^2)$ convergence rate guarantee, oftentimes in practice its…

Optimization and Control · Mathematics 2018-07-12 Jingwei Liang , Carola-Bibiane Schönlieb

In this paper, it is shown completely analytically that a spintessence model can very well serve the purpose of providing an early deceleration and the present day acceleration.

General Relativity and Quantum Cosmology · Physics 2009-09-01 Narayan Banerjee , Sudipta Das

The recently introduced energy-saving extension of the sub-optimal sliding mode control allows for control-off phases during the convergence to second-order equilibrium. This way, it enables for a lower energy consumption compared to the…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Michael Ruderman

A method is presented which allows for a tremendous speed-up of computer simulations of statistical systems by orders of magnitude. This speed-up is achieved by means of a new observable, while the algorithm of the simulation remains…

Statistical Mechanics · Physics 2013-05-29 M. Kastner , J. D. Munoz , M. Promberger

A Stark decelerator is an effective tool for controlling motional degrees of freedom of polar molecules. Due to technical limitations, many of the current Stark decelerators focus on molecules in low-field-seeking quantum states and are…

Atomic Physics · Physics 2017-05-25 Demitri Y. Balabanov , Liam M. Duffy

We use optimal control theory to show that for a closed $\Lambda$-system where the excited intermediate level decays to the lower levels with a common large rate, the optimal scheme for population transfer between the lower levels is…

Quantum Physics · Physics 2022-12-27 Dionisis Stefanatos , Emmanuel Paspalakis

Novel multi-step predictor-corrector numerical schemes have been derived for approximating decoupled forward-backward stochastic differential equations (FBSDEs). The stability and high order rate of convergence of the schemes are rigorously…

Numerical Analysis · Mathematics 2021-02-12 Qiang Han , Shaolin Ji

Two new stochastic variance-reduced algorithms named SARAH and SPIDER have been recently proposed, and SPIDER has been shown to achieve a near-optimal gradient oracle complexity for nonconvex optimization. However, the theoretical advantage…

Optimization and Control · Mathematics 2019-05-17 Yi Zhou , Zhe Wang , Kaiyi Ji , Yingbin Liang , Vahid Tarokh

We present an analysis of the deceleration and trapping of heavy diatomic molecules in low-field seeking states by a moving electric potential. This moving potential is created by a 'ring-decelerator', which consists of a series of…

The bidirectional steering between two accelerated partners sharing initially different classes of entangled states is discussed. Due to the decoherence, the steerability and its degree decrease either as the acceleration increases or the…

Quantum Physics · Physics 2025-07-25 M. Y. Abd-Rabbou , N. Metwally , M. M. A. Ahmed , A. -S. F. Obada

Fine-tuning pretrained models has become a standard approach to adapting pretrained knowledge to improve the accuracy on new sparse, imbalance datasets. However, issues arise when optimization falls into a collapsed state, where the model…

Machine Learning · Computer Science 2026-05-01 Nghia Bui , Lijing Wang