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In this paper, we propose new proximal Newton-type methods for convex optimization problems in composite form. The applications include model predictive control (MPC) and embedded MPC. Our new methods are computationally attractive since…

Optimization and Control · Mathematics 2020-07-21 Ilan Adler , Zhiyue Tom Hu , Tianyi Lin

In analog circuits, process variation can cause unpredictability in circuit performance. Common-centroid (CC) type layouts have been shown to mitigate process-induced variations and are widely used to match circuit elements. Nevertheless,…

Hardware Architecture · Computer Science 2025-04-18 Supriyo Maji , Hyungjoo Park , Gi moon Hong , Souradip Poddar , David Z. Pan

We deal with the presence of topological defects in models for two real scalar fields. We comment on defects hosting topological defects, and we search for explicit defect solutions using the trial orbit method. As we know, under certain…

High Energy Physics - Theory · Physics 2009-11-07 D. Bazeia , W. Freire , L. Losano , R. F. Ribeiro

This paper aims at developing novel shuffling gradient-based methods for tackling two classes of minimax problems: nonconvex-linear and nonconvex-strongly concave settings. The first algorithm addresses the nonconvex-linear minimax model…

Optimization and Control · Mathematics 2024-10-30 Quoc Tran-Dinh , Trang H. Tran , Lam M. Nguyen

We demonstrate the accuracy of ground-state energies of the transcorrelated Hamiltonian, employing sophisticated Jastrow factors obtained from variational Monte Carlo, together with the coupled cluster and distinguishable cluster methods at…

Entropy regularized optimal transport and its multi-marginal generalization have attracted increasing attention in various applications, in particular due to efficient Sinkhorn-like algorithms for computing optimal transport plans. However,…

Optimization and Control · Mathematics 2023-01-25 Florian Beier , Johannes von Lindheim , Sebastian Neumayer , Gabriele Steidl

We propose an efficient algorithm for solving orthogonal canonical correlation analysis (OCCA) in the form of trace-fractional structure and orthogonal linear projections. Even though orthogonality has been widely used and proved to be a…

Machine Learning · Computer Science 2019-09-26 Leihong Zhang , Li Wang , Zhaojun Bai , Ren-cang Li

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled- cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived…

Chemical Physics · Physics 2018-03-14 Takeshi Sato , Himadri Pathak , Yuki Orimo , Kenichi L. Ishikawa

In this paper, we introduce a generalized dynamical unbalanced optimal transport framework by incorporating limited control input and mass dissipation, addressing limitations in conventional optimal transport for control applications. We…

Optimization and Control · Mathematics 2025-04-07 Dongjun Wu , Anders Rantzer

This paper considers a new method for the binary asteroid orbit determination problem. The method is based on the Bayesian approach with a global optimisation algorithm. The orbital parameters to be determined are modelled through an a…

Instrumentation and Methods for Astrophysics · Physics 2017-08-31 Irina D. Kovalenko , Radu S. Stoica , Nikolay V. Emelyanov

In this paper, we focus on the solution of online optimization problems that arise often in signal processing and machine learning, in which we have access to streaming sources of data. We discuss algorithms for online optimization based on…

Optimization and Control · Mathematics 2023-05-05 Nicola Bastianello , Ruggero Carli , Andrea Simonetto

It has been well established that the Jastrow correlation factor can effectively capture the electron correlation effects, and thus, the efficient optimization of the many-body wave function including the Jastrow correlation factor is of…

Atomic Physics · Physics 2023-09-12 Masayuki Ochi

Tensor train (TT) decomposition provides a space-efficient representation for higher-order tensors. Despite its advantage, we face two crucial limitations when we apply the TT decomposition to machine learning problems: the lack of…

Machine Learning · Statistics 2017-08-03 Masaaki Imaizumi , Takanori Maehara , Kohei Hayashi

The time evolution of quantum many-body systems is one of the most promising applications for near-term quantum computers. However, the utility of current quantum devices is strongly hampered by the proliferation of hardware errors. The…

Quantum Physics · Physics 2024-05-21 Maurits S. J. Tepaske , David J. Luitz , Dominik Hahn

In this work, we develop a new orbital optimization approach, perturbative Super-CI (Super-CIPT), for the two-component complete active space self-consistent field (2C-CASSCF) method. By variationally optimizing spinor orbitals and…

Chemical Physics · Physics 2026-03-04 Yang Guo , Achintya Kumar Dutta

Trajectory optimization of low-thrust perturbed orbit rendezvous is a crucial technology for space missions in low Earth orbits, which is difficult to solve due to its initial value sensitivity, especially when the transfer trajectory has…

Instrumentation and Methods for Astrophysics · Physics 2023-05-03 An-yi Huang , Heng-nian Li

In this note we aim at putting more emphasis on the fact that trying to solve non-convex optimization problems with coordinate-descent iterative linear matrix inequality algorithms leads to suboptimal solutions, and put forward other…

Optimization and Control · Mathematics 2024-10-30 Emile Simon , Vincent Wertz

This paper presents a trajectory optimization and control approach for the guidance of an orbital four-arm robot in extravehicular activities. The robot operates near the target spacecraft, enabling its arm's end-effectors to reach the…

In this paper, we propose a trajectory optimization for computing smooth collision free trajectories for nonholonomic curvature bounded vehicles among static and dynamic obstacles. One of the key novelties of our formulation is a hierarchal…

In this paper, we consider the decentralized optimization problems with generalized orthogonality constraints, where both the objective function and the constraint exhibit a distributed structure. Such optimization problems, albeit…

Optimization and Control · Mathematics 2024-09-10 Lei Wang , Nachuan Xiao , Xin Liu