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A modification of the Adaptive Biasing Force method is introduced, in which the free energy is approximated by a sum of tensor products of one-dimensional functions. This enables to handle a larger number of reaction coordinates than the…

Probability · Mathematics 2020-07-21 Virginie Ehrlacher , Tony Lelièvre , Pierre Monmarché

We propose to use the energy absorption spectroscopy to measure the kinetic coefficients of unitary Fermi gases in a uniform potential. We show that in our scheme, the energy absorption spectrum is proportional to the dynamic structure…

Quantum Gases · Physics 2018-04-18 Pengfei Zhang , Zhenhua Yu

Bilevel optimisation is used in inverse imaging problems for hyperparameter learning/identification and experimental design, for instance, to find optimal regularisation parameters and forward operators. However, computationally, the…

Optimization and Control · Mathematics 2025-08-06 Ensio Suonperä , Tuomo Valkonen

Calculating one-body density profiles in equilibrium via particle-based simulation methods involves counting of events of particle occurrences at (histogram-resolved) space points. Here we investigate an alternative method based on a…

Soft Condensed Matter · Physics 2018-11-07 Daniel de las Heras , Matthias Schmidt

We present a method for determining the free energy of coexisting states from irreversible work measurements. Our approach is based on a fluctuation relation that is valid for dissipative transformations in partially equilibrated systems.…

Soft Condensed Matter · Physics 2009-02-21 Ivan Junier , Alessandro Mossa , Maria Manosas , Felix Ritort

We propose an iterative method of energy flow shaping in the focal region with the amplitude, phase and polarization modulation of incident light. By using an iterative optimization based on the diffraction calculation with help of the fast…

Optics · Physics 2015-11-10 Hao Chen , Guoqiang Li

Parameterizing mathematical models of biological systems often requires fitting to stable periodic data. In cardiac electrophysiology this typically requires converging to a stable action potential through long simulations. We explore this…

Quantitative Methods · Quantitative Biology 2025-01-16 Matt J Owen , Gary R Mirams

Phase recovery from the bispectrum is a central problem in speckle interferometry which can be posed as an optimization problem minimizing a weighted nonlinear least-squares objective function. We look at two different formulations of the…

Numerical Analysis · Mathematics 2019-06-26 James L. Herring , James Nagy , Lars Ruthotto

On the basis of the data given in the works of different authors a criterion of phase-photometric method of measurement of energy angle of divergence has been formulated. Validity of application of the obtained relations for a ray beam with…

Optics · Physics 2007-05-23 Rahul Malik

In biomolecular systems (especially all-atom models) with many degrees of freedom such as proteins and nucleic acids, there exist an astronomically large number of local-minimum-energy states. Conventional simulations in the canonical…

Statistical Mechanics · Physics 2010-12-30 Ayori Mitsutake , Yoshiharu Mori , Yuko Okamoto

We address the problem of motion estimation in images operating in the frequency domain. A method is presented which extends phase correlation to handle multiple motions present in an area. Our scheme is based on a novel Bilateral-Phase…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Vasileios Argyriou

We try to retrieve the power spectra with certainty to the highest spatial frequencies allowed by current instrumentation. For this, we use 2D inversion code that were able to recover information up to the instrumental diffraction limit.…

Solar and Stellar Astrophysics · Physics 2016-10-26 S. Danilovic , M. Rempel , M. van Noort , R. Cameron

Energy-based models (EBMs) estimate unnormalized densities in an elegant framework, but they are generally difficult to train. Recent work has linked EBMs to generative adversarial networks, by noting that they can be trained through a…

Machine Learning · Computer Science 2025-06-06 Cong Geng , Jia Wang , Li Chen , Zhiyong Gao , Jes Frellsen , Søren Hauberg

Bayesian inference is a widely used statistical method. The free energy and generalization loss, which are used to estimate the accuracy of Bayesian inference, are known to be small in singular models that do not have a unique optimal…

Statistics Theory · Mathematics 2020-12-16 Shuya Nagayasu , Sumio Watanabe

Exact numerical methods and stochastic simulation methods are developed to study the force stretching single RNA issue on the secondary structure level in equilibrium. By computing the force-extension curves on the constant force and the…

Biomolecules · Quantitative Biology 2016-09-08 Fei Liu , Bi-hui Zhu , Zhong-can Ou-Yang

We show how spectral submanifold (SSM) theory can be used to extract forced-response curves, including isolas, without any numerical simulation in high-degree-of-freedom, periodically forced mechanical systems. We use multivariate…

Dynamical Systems · Mathematics 2019-12-25 Sten Ponsioen , George Haller

Statistical power estimation for studies with multiple model parameters is inherently a multivariate problem. Power for individual parameters of interest cannot be reliably estimated univariately since correlation and variance explained…

Methodology · Statistics 2022-05-25 Ajinkya K Mulay , Sean Lane , Erin Hennes

The absolute free energy -- or partition function, equivalently -- of a molecule can be estimated computationally using a suitable reference system. Here, we demonstrate a practical method for staging such calculations by growing a molecule…

Biological Physics · Physics 2009-01-31 Xin Zhang , Artem B. Mamonov , Daniel M. Zuckerman

We present an efficient method to mix well converged ab initio forces with simpler and faster ones in molecular dynamics. While the cheap forces are evaluated every time step, the converged ones correct the trajectory only every n time…

Materials Science · Physics 2009-11-10 E. Anglada , J. Junquera , J. M. Soler

We consider the problem of sampling a high dimensional multimodal target probability measure. We assume that a good proposal kernel to move only a subset of the degrees of freedoms (also known as collective variables) is known a priori.…

Statistical Mechanics · Physics 2025-02-07 Christoph Schönle , Marylou Gabrié , Tony Lelièvre , Gabriel Stoltz