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The goal of this study is to introduce a unified computational framework for simulating random iteration equations (RIE), understood as iteration equations containing random variables. The novelty of this work is that full probability…

Dynamical Systems · Mathematics 2026-04-08 Wolfgang Hoegele

Hydrodynamic models fail to describe the near-equal $v_2/v_3$ ratio observed in ultra-central heavy-ion collisions, despite their success in other centrality classes. This discrepancy stems from shear viscosity suppressing higher-order…

Nuclear Theory · Physics 2025-04-29 Qi Wang , Long-Gang Pang , Xin-Nian Wang

The double folding (DF) approach is one of the widely used methods for finding nucleus-nucleus interaction potential. In the present work, the influence of the nuclear matter density on the DF potential and on the Coulomb barrier parameters…

To explore the structure of the QCD phase diagram in high baryon density domain, several high-energy nuclear collision experiments in a wide range of beam energies are currently performed or planned using many accelerator facilities. In…

This study presents a correlation femtoscopy analysis of relativistic heavy-ion collisions at RHIC Beam Energy Scan (BES) energies using the extended integrated HydroKinetic Model (iHKMe). The model combines initial conditions from UrQMD…

High Energy Physics - Phenomenology · Physics 2025-06-25 Vladislav Naboka , Yuri Sinyukov , Musfer Adzhymambetov , Hanna Zbroszczyk

A unified description of full reaction channels in low-energy heavy-ion collisions is a great challenge. Although the theoretical models based on the dinuclear system (DNS) concept have been successfully employed in multinucleon transfer…

Nuclear Theory · Physics 2025-09-05 Zehong Liao , Yu Yang , Zepeng Gao , Jun Su , Long Zhu

In the framework of the KIDS generalized energy density functional (EDF), the nuclear equation of state (EoS) is expressed as an expansion in powers of the Fermi momentum or the cubic root of the density ($\rho^{1/3}$). Although an optimal…

Nuclear Theory · Physics 2019-07-24 Hana Gil , Young-Min Kim , Chang Ho Hyun , Panagiota Papakonstantinou , Yongseok Oh

The density functional renormalization group (density-fRG) is proposed to investigate the density fluctuations within the functional renormalization group approach, which allows us to quantify the medium effect and study physics of high…

Nuclear Theory · Physics 2025-08-05 Yong-rui Chen , Wei-jie Fu , Yang-yang Tan

Cluster formation is a fundamental aspect of the equation of state (EOS) of warm and dense nuclear matter such as can be found in supernovae (SNe). Similar matter can be studied in heavy-ion collisions (HIC). We use the experimental data of…

Nuclear Theory · Physics 2015-05-05 Matthias Hempel , Kris Hagel , Joseph Natowitz , Gerd Röpke , Stefan Typel

We have constructed a nuclear equation of state (EOS) that includes a full nuclear ensemble for use in core-collapse supernova simulations. It is based on the EOS for uniform nuclear matter that two of the authors derived recently, applying…

High Energy Astrophysical Phenomena · Physics 2017-08-01 S. Furusawa , H. Togashi , H. Nagakura , K. Sumiyoshi , S. Yamada , H. Suzuki , M. Takano

The development of safety validation methods is essential for the safe deployment and operation of Automated Driving Systems (ADSs). One of the goals of safety validation is to prospectively evaluate the risk of an ADS dealing with…

Robotics · Computer Science 2025-07-31 Erwin de Gelder , Maren Buermann , Olaf Op den Camp

The Ultrarelativistic Quantum Molecular Dynamics (UrQMD) model, a microscopic transport model, is used to study the directed and elliptic collective flows and the nuclear stopping in Au+Au collisions at incident energies covered by INDRA…

Nuclear Theory · Physics 2011-02-01 Qingfeng Li , Caiwan Shen , Chenchen Guo , Yongjia Wang , Zhuxia Li , J. Lukasik , W. Trautmann

We suggest that the ultrarelativistic collisions of heavy ions provide the simplest situation for the study of strong interactions which can be understood from first principles and without any model assumptions about the microscopic…

High Energy Physics - Phenomenology · Physics 2009-10-31 A. Makhlin

Molecular dynamics simulations have become essential in many areas of atomistic modelling from drug discovery to materials science. They provide critical atomic-level insights into key dynamical events experiments cannot easily capture.…

Biological Physics · Physics 2024-06-14 Tiejun Wei , Balint Dudas , Edina Rosta

This paper introduces a novel mathematical model for Molecular Communication (MC) systems, utilizing First Arrival Position (FAP) as a fundamental mode of information transmission. We address two critical challenges: the characterization of…

Information Theory · Computer Science 2024-02-20 Yen-Chi Lee , Yun-Feng Lo , Jen-Ming Wu , Min-Hsiu Hsieh

The dynamics and processes involved in particle-molecule scattering, including nuclear dynamics, are described and analyzed using various quantum information quantities throughout the different stages of the scattering. The main process…

Quantum Physics · Physics 2025-05-22 Martin Mendez , Federico M. Pont

Fermi operator expansion (FOE) methods are powerful alternatives to diagonalization type methods for solving Kohn-Sham density functional theory (KSDFT). One example is the pole expansion and selected inversion (PEXSI) method, which…

Computational Physics · Physics 2017-10-25 Weile Jia , Lin Lin

Sparse autoencoders (SAEs) have been applied to large language models and protein language models, but not systematically to electronic health record (EHR) foundation models. We train TopK SAEs on FlatASCEND, a 14.5-million-parameter…

Machine Learning · Computer Science 2026-05-07 Chris Sainsbury , Feng Dong , Andreas Karwath

A precise security analysis of practical quantum key distribution (QKD) systems is an important step for improving their performance. Here we consider a class of quantum soft filtering operations, which generalizes the unambiguous state…

Quantum Physics · Physics 2020-03-25 D. A. Kronberg , A. S. Nikolaeva , Y. V. Kurochkin , A. K. Fedorov

The rapid development of computational materials science powered by machine learning (ML) is gradually leading to solutions to several previously intractable scientific problems. One of the most prominent is machine learning interatomic…

Materials Science · Physics 2025-05-27 Xiao Fu , Jing Xu , Qifan Yang , Xuhe Gong , Jingchen Lian , Liqi Wang , Zibin Wang , Ruijuan Xiao , Hong Li