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In this paper we combine two powerful computational techniques, well-tempered metadynamics and time lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy…

Statistical Mechanics · Physics 2017-12-08 James McCarty , Michele Parrinello

A recently proposed method for computer simulations in the isothermal-isobaric (NPT) ensemble, based on Langevin-type equations of motion for the particle coordinates and the ``piston'' degree of freedom, is re-derived by straightforward…

Soft Condensed Matter · Physics 2016-08-31 A. Kolb , B. Duenweg

The scheme of divided differences is widely used in many approximation and interpolation problems. Computing the Newton coefficients of the interpolating polynomial is the first step of the Bj\"{o}rck and Pereyra algorithm for solving…

Numerical Analysis · Mathematics 2007-05-23 Alicja Smoktunowicz , Przemyslaw Kosowski , Iwona Wrobel

We develop a method for offline parameter estimation of discrete multibody dynamics with regularized and frictional kinematic constraints. This setting leads to unobserved degrees of freedom, which we handle using joint state and parameter…

Optimization and Control · Mathematics 2025-02-11 Hannes Marklund , Martin Servin , Mats G Larson

In this paper we derive a Newton type method to solve the non-linear system formed by combining the Tikhonov normal equations and Morozov's discrepancy principle. We prove that by placing a bound on the step size of the Newton iterations…

Numerical Analysis · Mathematics 2018-09-06 Nick Schenkels , Wim Vanroose

We consider systems of recursively defined combinatorial structures. We give algorithms checking that these systems are well founded, computing generating series and providing numerical values. Our framework is an articulation of the…

Combinatorics · Mathematics 2012-12-18 Carine Pivoteau , Bruno Salvy , Michele Soria

In this paper, we enumerate Newton polygons asymptotically. The number of Newton polygons is computable by a simple recurrence equation, but unexpectedly the asymptotic formula of its logarithm contains growing oscillatory terms. As the…

Number Theory · Mathematics 2020-03-26 Shushi Harashita

We propose an efficient way of solving optimal control problems for rigid-body systems on the basis of inverse dynamics and the multiple-shooting method. We treat all variables, including the state, acceleration, and control input torques,…

Optimization and Control · Mathematics 2022-10-25 Sotaro Katayama , Toshiyuki Ohtsuka

We develop a new, group-theoretic approach to bounding the exponent of matrix multiplication. There are two components to this approach: (1) identifying groups G that admit a certain type of embedding of matrix multiplication into the group…

Group Theory · Mathematics 2012-03-15 Henry Cohn , Christopher Umans

This paper describes a method for solving smooth nonconvex minimization problems subject to bound constraints with good worst-case complexity guarantees and practical performance. The method contains elements of two existing methods: the…

Optimization and Control · Mathematics 2023-06-08 Yue Xie , Stephen J. Wright

For large-scale eigenvalue problems requiring many mutually orthogonal eigenvectors, traditional numerical methods suffer substantial computational and communication costs with limited parallel scalability, primarily due to explicit…

Numerical Analysis · Mathematics 2026-01-12 Shengyue Wang , Aihui Zhou

In this paper we develop a straightforward procedure to construct higher dimensional isochronous Hamiltonian systems. We first show that a class of singular Hamiltonian systems obtained through the $\Omega$-modified procedure is equivalent…

Exactly Solvable and Integrable Systems · Physics 2012-11-15 A. Durga Devi , R. Gladwin Pradeep , V. K. Chandrasekar , M. Lakshmanan

There have been several algorithms designed to optimise matrix multiplication. From schoolbook method with complexity $O(n^3)$ to advanced tensor-based tools with time complexity $O(n^{2.3728639})$ (lowest possible bound achieved), a lot of…

Data Structures and Algorithms · Computer Science 2019-01-30 Shrohan Mohapatra

We show that Newton methods for generalized equations are input-to-state stable with respect to disturbances such as due to inexact computations. We then use this result to obtain convergence and robustness of a multistep Newton-type method…

Optimization and Control · Mathematics 2025-03-18 Torbjørn Cunis , Ilya Kolmanovsky

Gradients have been exploited in proposal distributions to accelerate the convergence of Markov chain Monte Carlo algorithms on discrete distributions. However, these methods require a natural differentiable extension of the target discrete…

Machine Learning · Computer Science 2023-02-28 Yue Xiang , Dongyao Zhu , Bowen Lei , Dongkuan Xu , Ruqi Zhang

This paper is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints. Specifically, we study situations where parts of the constraints…

Optimization and Control · Mathematics 2022-04-20 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz , Gerd Wachsmuth

A new algorithm for numerical integration of the rigid-body equations of motion is proposed. The algorithm uses the leapfrog scheme and the quantities involved are angular velocities and orientational variables which can be expressed in…

Computational Physics · Physics 2016-09-08 Igor P. Omelyan

Novel classes of dynamical systems are introduced, including many-body problems characterized by nonlinear equations of motion of Newtonian type ("acceleration equals forces") which determine the motion of points in the complex plane. These…

Mathematical Physics · Physics 2016-01-20 Oksana Bihun , Francesco Calogero

We introduce an extension of a variationally optimized perturbation method, by combining it with renormalization group properties in a straightforward (perturbative) form. This leads to a very transparent and efficient procedure, with a…

High Energy Physics - Theory · Physics 2014-11-20 J. -L. Kneur , A. Neveu

The solution of a (stochastic) differential equation can be locally approximated by a (stochastic) expansion. If the vector field of the differential equation is a polynomial, the corresponding expansion is a linear combination of iterated…

Probability · Mathematics 2010-09-29 Christophe Ladroue , Anastasia Papavasiliou