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Two roads are presently being followed in order to establish the existence of a liquid-gas phase transition in finite nuclear systems from nuclear reactions at high energy. The clean experiment of observing the thermodynamic properties of a…

Nuclear Experiment · Physics 2009-11-10 W. Trautmann

With increasing demand for accurate calculation of isotope shifts of atomic systems for fundamental and nuclear structure research, an analytic energy derivative approach is presented in the relativistic coupled-cluster theory framework to…

A coupling model of biomass fluidized bed gasification based on machine learning and computational fluid dynamics is proposed to improve the prediction accuracy and computational efficiency of complex thermochemical reaction process. By…

Machine Learning · Computer Science 2025-09-09 Chun Wang

We derive the rapidity evolution equation for the gluon four-point function in the dilute regime and at small x from the JIMWLK functional equation. We show that beyond leading order in Nc the mean field (Gaussian) approximation where the…

High Energy Physics - Phenomenology · Physics 2010-05-25 Adrian Dumitru , Jamal Jalilian Marian

A three-center phenomenological model able to explain, at least from a qualitative point of view, the difference in the observed yield of a particle-accompanied fission and that of binary fission was developed. It is derived from the liquid…

Nuclear Theory · Physics 2007-05-23 D. N. Poenaru , B. Dobrescu , W. Greiner

This is the first paper of a series of two devoted to develop a practical method to describe the growth history of bound virialized objects in the gravitational instability scenario without resorting to $N$-body simulations. Here we present…

Astrophysics · Physics 2009-10-28 Alberto Manrique , Eduard Salvador-Sole

A common approach to study nucleation rates is the estimation of free-energy barriers. This usually requires knowledge about the shape of the forming droplet, a task that becomes notoriously difficult in macromolecular setups starting with…

Statistical Mechanics · Physics 2017-03-28 Johannes Zierenberg , Philipp Schierz , Wolfhard Janke

We demonstrate a method of creating photonic two-dimensional cluster states that is considerably more efficient than previously proposed approaches. Our method uses only local unitaries and type-I fusion operations. The increased efficiency…

Quantum Physics · Physics 2009-11-11 Gerald Gilbert , Michael Hamrick , Yaakov S. Weinstein

The large-scale properties of chemical reaction systems, such as the metabolism, can be studied with graph-based methods. To do this, one needs to reduce the information -- lists of chemical reactions -- available in databases. Even for the…

Molecular Networks · Quantitative Biology 2009-09-25 Petter Holme

Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or online analysis is not adequate to capture dynamic behaviors of the power system,…

This article is concerned with a new filtered two-step variational integrator for solving the charged-particle dynamics in a mildly non-uniform moderate or strong magnetic field with a dimensionless parameter $\varepsilon$ inversely…

Numerical Analysis · Mathematics 2026-03-05 Ting Li , Bin Wang

We show that the unsteadiness of turbulence has a drastic effect on turbulence parameters and in particle cluster formation. To this end we use direct numerical simulations of particle laden flows with a steady forcing that generates an…

Cluster production plays an important role in heavy-ion collisions at intermediate beam energies, where light nuclei contribute substantially to final-state yields and to other observables that are used to infer the nuclear equation of…

Nuclear Theory · Physics 2026-05-13 Oleh Savchuk , Pawel Danielewicz , William Lynch , Jérôme Margueron

Granular materials are characterized by large collections of discrete particles of sizes larger than one micron, where the particle-particle interactions are significantly more important than the particle-fluid interactions. These flows can…

Soft Condensed Matter · Physics 2019-01-04 Yifei Duan , Zhi-Gang Feng

By approximating posterior distributions with weighted samples, particle filters (PFs) provide an efficient mechanism for solving non-linear sequential state estimation problems. While the effectiveness of particle filters has been…

Machine Learning · Computer Science 2023-12-15 Xiongjie Chen , Yunpeng Li

In this paper, a new formalism for the filtered density function (FDF) approach is developed for the treatment of turbulent polydispersed two-phase flows in LES simulations. Contrary to the FDF used for turbulent reactive single-phase…

Fluid Dynamics · Physics 2012-02-07 Sergio Chibbaro , jean-Pierre Minier

The use of machine learning algorithms is an attractive way to produce very fast detector simulations for scattering reactions that can otherwise be computationally expensive. Here we develop a factorised approach where we deal with each…

Data Analysis, Statistics and Probability · Physics 2022-07-26 D. Darulis , R. Tyson , D. G. Ireland , D. I. Glazier , B. McKinnon , P. Pauli

Rules for in-medium complex particle production in nuclear reactions are proposed. These rules have been implemented in two models to simulate nucleon-nucleus and nucleus-nucleus reactions around the Fermi energy. Our work emphasizes the…

Nuclear Theory · Physics 2007-05-23 D. Lacroix , D. Durand

The impulse response of a generalized fractional second order filter of the form ${{({{s}^{2\alpha}}+a{{s}^{\alpha}}+b)}^{-\gamma}}$ is derived, where $0<\alpha \le 1$, $0<\gamma <2$. The asymptotic properties of the impulse responses are…

Systems and Control · Computer Science 2012-12-18 Zhuang Jiao , YangQuan Chen

Recently, there has been a surge of interest in incorporating neural networks into particle filters, e.g. differentiable particle filters, to perform joint sequential state estimation and model learning for non-linear non-Gaussian…

Machine Learning · Computer Science 2025-01-07 Xiongjie Chen , Yunpeng Li