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Iterative algorithms aimed at solving some problems are discussed. For certain problems, such as finding a common point in the intersection of a finite number of convex sets, there often exist iterative algorithms that impose very little…

Optimization and Control · Mathematics 2010-09-28 Y. Censor , R. Davidi , G. T. Herman

We describe a newly developed hydrodynamic code for studying accretion disk processes. The numerical method uses a finite volume, nonlinear, Total Variation Diminishing (TVD) scheme to capture shocks and control spurious oscillations. It is…

Astrophysics · Physics 2008-12-18 L. R. Mudryk , N. W. Murray

Given a family of rational curves depending on a real parameter, defined by its parametric equations, we provide an algorithm to compute a finite partition of the parameter space (${\Bbb R}$, in general) so that the shape of the family…

Symbolic Computation · Computer Science 2009-11-13 Juan Gerardo Alcazar

It is well known that conventional simulation algorithms are inefficient for the statistical description of macroscopic systems exactly at the critical point due to the divergence of the corresponding relaxation time (critical slowing…

Computational Physics · Physics 2008-11-26 N. G. Antoniou , F. K. Diakonos , E. N. Saridakis , G. A. Tsolias

We study the classical problem of prediction with expert advice in the adversarial setting with a geometric stopping time. In 1965, Cover gave the optimal algorithm for the case of 2 experts. In this paper, we design the optimal algorithm,…

Machine Learning · Computer Science 2016-07-12 Nick Gravin , Yuval Peres , Balasubramanian Sivan

Many signal processing problems can be solved by maximizing the fitness of a segmented model over all possible partitions of the data interval. This letter describes a simple but powerful algorithm that searches the exponentially large…

The central object of this PhD thesis is known under different names in the fields of computer science and statistical mechanics. In computer science, it is called the Maximum Cut problem, one of the famous twenty-one Karp's original…

Machine Learning · Computer Science 2022-08-31 Mikhail Krechetov

This paper presents a hierarchical planning algorithm for racing with multiple opponents. The two-stage approach consists of a high-level behavioral planning step and a low-level optimization step. By combining discrete and continuous…

Robotics · Computer Science 2026-04-29 Georg Jank , Matthias Rowold , Boris Lohmann

Generating intelligent robot behavior in contact-rich settings is a research problem where zeroth-order methods currently prevail. A major contributor to the success of such methods is their robustness in the face of non-smooth and…

Robotics · Computer Science 2025-04-15 Onur Beker , Nico Gürtler , Ji Shi , A. René Geist , Amirreza Razmjoo , Georg Martius , Sylvain Calinon

Generalizable manipulation requires that robots be able to interact with novel objects and environment. This requirement makes manipulation extremely challenging as a robot has to reason about complex frictional interaction with uncertainty…

Robotics · Computer Science 2023-01-18 Yuki Shirai , Devesh K. Jha , Arvind Raghunathan , Diego Romeres

Finite-precision floating point arithmetic unavoidably introduces rounding errors which are traditionally bounded using a worst-case analysis. However, worst-case analysis might be overly conservative because worst-case errors can be…

Numerical Analysis · Mathematics 2019-12-11 Fredrik Dahlqvist , Rocco Salvia , George A Constantinides

We turn the long time puzzle of the free volume, known for its highly irregular form, into exact analytical formulae and develop statistical mechanics of the hard disk model. The free volume is exactly expressed in terms of the intersection…

Statistical Mechanics · Physics 2026-03-24 Victor M. Pergamenshchik , Taras Bryk , Andrij Trokhymchuk

We consider optimization algorithms that are open systems, that is, with external inputs and outputs. Such algorithms arise for instance, when analyzing the effect of noise or disturbance on an algorithm, or when an algorithm is part of…

Optimization and Control · Mathematics 2026-04-02 Jaap Eising , Florian Dörfler

We present certain mathematical aspects of an information method which was formulated in an attempt to investigate diffusion phenomena. We imagine a regular dynamical hamiltonian systems under the random perturbation of thermal (molecular)…

Statistical Mechanics · Physics 2007-05-23 Qiuping A. Wang , Wei Li

We study theoretically the effects of dissipation on the performances of a variational quantum algorithm used to approximately solve a combinatorial optimization problem, the Maximum Independent Set, on a platform of neutral atoms. We take…

Quantum Physics · Physics 2020-01-29 Loïc Henriet

A modification of the standard Boris algorithm, called filtered Boris algorithm, is proposed for the numerical integration of the equations of motion of charged particles in a strong non-uniform magnetic field in the asymptotic scaling…

Numerical Analysis · Mathematics 2019-07-18 Ernst Hairer , Christian Lubich , Bin Wang

This paper proposes an improved quasi-Newton penalty decomposition algorithm for the minimization of continuously differentiable functions, possibly nonconvex, over sparse symmetric sets. The method solves a sequence of penalty subproblems…

Optimization and Control · Mathematics 2026-01-21 Ahmad Mousavi , Morteza Kimiaei , Saman Babaie-Kafaki , Vyacheslav Kungurtsev

In this article we describe a stable partitioned algorithm that overcomes the added mass instability arising in fluid-structure interactions of light rigid bodies and inviscid compressible flow. The new algorithm is stable even for bodies…

Numerical Analysis · Mathematics 2015-06-11 J. W. Banks , W. D. Henshaw , B. Sjogreen

We propose a planning and control approach to physics-based manipulation. The key feature of the algorithm is that it can adapt to the accuracy requirements of a task, by slowing down and generating `careful' motion when the task requires…

Robotics · Computer Science 2019-01-23 Wisdom C. Agboh , Mehmet R. Dogar

We develop methods to solve general optimal stopping problems with opportunities to stop that arrive randomly. Such problems occur naturally in applications with market frictions. Pivotal to our approach is that our methods operate on…