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Thermodynamical properties of nuclear matter undergoing multifragmentation are studied within a simplified version of the statistical model. An exact analytical solution has been found for the grand canonical ensemble. Excluded volume…

Nuclear Theory · Physics 2009-11-06 K. A. Bugaev , M. I. Gorenstein , I. N. Mishustin , W. Greiner

Reliable calculations of the structure of heavy elements are crucial to address fundamental science questions such as the origin of the elements in the universe. Applications relevant for energy production, medicine, or national security…

We develop a new formalism to treat nuclear many-body systems using bare nucleon-nucleon interaction. It has become evident that the tensor interaction plays important role in nuclear many-body systems due to the role of the pion in…

Nuclear Theory · Physics 2017-04-28 Takayuki Myo , Hiroshi Toki , Kiyomi Ikeda , Hisashi Horiuchi , Tadahiro Suhara

Nuclear energy density functionals (EDFs) have a long history of success in reproducing properties of nuclei across the table of the nuclides. They capture quantitatively the emergent features of bound nuclei, such as nuclear saturation and…

Nuclear Theory · Physics 2020-06-24 R. J. Furnstahl

The DMD (Dynamic Mode Decomposition) method has attracted widespread attention as a representative modal-decomposition method and can build a predictive model. However, the DMD may give predicted results that deviate from physical reality…

Computational Physics · Physics 2023-11-29 Yuhui Yin , Chenhui Kou , Shengkun Jia , Lu Lu , Xigang Yuan , Yiqing Luo

Recent developments, both in theoretical modeling and computational power, have allowed us to make progress on a goal not fully achieved yet in nuclear theory: a microscopic theory of nuclear fission. Even if the complete microscopic…

Nuclear Theory · Physics 2022-03-29 I. Stetcu , A. Bulgac , S. Jin , K. J. Roche , N. Schunck

Microscopic calculations of central collisions between heavy nuclei are used to study fragment production and the creation of collective flow. It is shown that the final phase space distributions are compatible with the expectations from a…

The Fast Multipole Method (FMM) offers an acceleration for pairwise interaction calculation, known as $N$-body problems, from $\mathcal{O}(N^2)$ to $\mathcal{O}(N)$ with $N$ particles. This has brought dramatic increase in the capability of…

Data Structures and Algorithms · Computer Science 2011-09-21 Felipe A. Cruz , L. A. Barba

Reaction-diffusion equations are one of the most common partial differential equations used to model physical phenomenon. They arise as the combination of two physical processes: a driving force $f(u)$ that depends on the state variable $u$…

Numerical Analysis · Mathematics 2020-01-08 Barbara Kaltenbacher , William Rundell

Depending on the energy regime, the dynamics of heavy-ion collisions reveals a variety of different mechanisms which are attributed to the combination of collective and dissipative effects. Semi-classical approaches have been successful in…

Nuclear Theory · Physics 2022-03-28 Hung Dinh Viet , Paolo Napolitani

The increasing complexity and scale of photonic and electromagnetic devices demand efficient and accurate numerical solvers. In this work, we develop a parallel overlapping domain decomposition method (DDM) based on the finite-difference…

Optics · Physics 2025-09-26 Zhanwen Wang , Chengnian Huang , Wangtao Lu , Yuntian Chen , Wei E. I. Sha

Digital twins (DTs) rely on continuous synchronization between physical systems and their virtual counterparts through online parameter estimation under uncertainty. In many practical settings, however, this task is challenged by low…

Computational Engineering, Finance, and Science · Computer Science 2026-05-19 Yasar Yanik , Himadri Basu , Ricardo G. Sanfelice , Daniele Venturi

Nuclear Astrophysics requires the knowledge of reaction rates over a wide range of nuclei and temperatures. In recent calculations the nuclear level density - as an important ingredient to the statistical model (Hauser-Feshbach) - has shown…

Astrophysics · Physics 2009-10-28 T. Rauscher , F. -K. Thielemann , K. -L. Kratz

We introduce the formalism to describe heavy-ion Double-Charge-Exchange (DCE) processes in the eikonal approximation. We focus on the low-momentum-transfer limit -- corresponding to the differential cross section at $\theta=0^\circ$ -- and,…

Nuclear Theory · Physics 2018-12-12 E. Santopinto , H. García-Tecocoatzi , R. I. Magaña-Vsevolodovna , J. Ferretti

We construct the equation of state (EOS) of nuclear matter at finite temperature and density with various proton fractions within the relativistic mean field (RMF) theory for the use in the supernova simulations. The Thomas-Fermi…

Nuclear Theory · Physics 2009-10-31 H. Shen , H. Toki , K. Oyamatsu , K. Sumiyoshi

The computation of dynamical response functions is central to many problems in condensed matter physics. Owing to the rapid growth of quantum correlations following a quench, classical methods face significant challenges even if an…

Quantum Physics · Physics 2025-05-09 Esther Cruz , Dominik S. Wild , Mari Carmen Bañuls , J. Ignacio Cirac

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible…

Density-functional theory (DFT) has revolutionized computer simulations in chemistry and material science. A faithful implementation of the theory requires self-consistent calculations. However, this effort involves repeatedly diagonalizing…

Quantum Physics · Physics 2023-07-17 Taehee Ko , Xiantao Li , Chunhao Wang

Time-dependent Hartree--Fock (TDHF) method has been applied to various low-energy nuclear reactions, such as fusion, fission, and multinucleon transfer reactions. In this Mini Review, we summarize recent attempts to bridge a microscopic…

Nuclear Theory · Physics 2020-03-16 Kouhei Washiyama , Kazuyuki Sekizawa

Deep Feedback Models (DFMs) are a new class of stateful neural networks that combine bottom up input with high level representations over time. This feedback mechanism introduces dynamics into otherwise static architectures, enabling DFMs…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 David Calhas , Arlindo L. Oliveira