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New experimental measurement of^(nat)Se(n,γ)cross section between 1 eV to 1 keV at the CSNS Back-n facility

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Chinese physics B 2022年第8期31卷 117-124页

作者： Xin-Rong Hu Long-Xiang Liu Wei Jiang Jie Ren Gong-Tao Fan Hong-Wei Wang Xi-Guang Cao Long-Long Song Ying-Du Liu Yue Zhang Xin-Xiang Li Zi-Rui Hao Pan Kuang Xiao-He Wang Ji-Feng Hu Bing Jiang De-Xin Wang Suyalatu Zhang Zhen-Dong An Yu-Ting Wang Chun-Wang Ma Jian-Jun He Jun Su Li-Yong Zhang Yu-Xuan Yang Sheng Jin Kai-Jie Chen Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China University of Chinese Academy of Sciences Beijing 100049China Shanghai Advanced Research Institute Chinese Academy of SciencesShanghai 201210China Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China Spallation Neutron Source Science Center Dongguan 523803China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China Xiangtan University Xiangtan 411105China Institute of Nuclear Physics Inner Mongolia University for the NationalitiesTongliao 028000China Sun Yat-sen University Zhuhai 510275China Henan Normal University Xinxiang 453007China Beijing Normal University Beijing 100875China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450052China ShanghaiTech University Shanghai 200120China

The^(74)Se is one of 35 p-nuclei,and^(82)Se is a r-process only nucleus,and their(n,γ)cross sections are vital input parameters for nuclear astrophysics reaction network *** neutron capture cross section in the resonance range of isotopes and even natural selenium samples has not been ***γ-rays originating from neutron-induced capture events were detected by four C_(6)D_(6) liquid scintillator detectors at the Back-n facility of China Spallation Neutron Source(CSNS).The pulse height weighting technique(PHWT)was used to analyze the data in the 1 e V to 100 ke V *** deduced neutron capture cross section was compared with ENDF/B-VIII.0,JEFF-3.2,and JENDL-4.0,and some differences were *** parameters were extracted by the R-matrix code SAMMY in the 1 e V-1 ke V *** the cross sections ofnatSe and resonance parameters are given in the *** datasets are openly available at http://***/10.11922/sciencedb.j00113.00019.

关键词： ^(nat)Se(n γ)cross section CSNS Back-n facility C_6D_6 detectors resolved resonance region Rmatrix

Reconstructing the Magnetic Field in an Arbitrary Domain via data-driven Bayesian Methods and Numerical Simulations

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arXiv 2024年

作者： Pavlou, Georgios E. Pavlidou, Vasiliki Harmandaris, Vagelis Institute of Applied and Computational Mathematics Foundation for Research and Technology- Hellas HeraklionGR-71110 Greece Institute of Astrophysics Foundation for Research and Technology- Hellas Vasilika Vouton HeraklionGR-71110 Greece Department of Physics University of Crete HeraklionGR-70013 Greece Department of Mathematics and Applied Mathematics University of Crete HeraklionGR-71409 Greece Computation-Based Science and Technology Research Center The Cyprus Institute Nicosia2121 Cyprus

Inverse problems are prevalent in numerous scientific and engineering disciplines, where the objective is to determine unknown parameters within a physical system using indirect measurements or observations. The inherent challenge lies in deducing the most probable parameter values that align with the collected data. This study introduces an algorithm for reconstructing parameters by addressing an inverse problem formulated through differential equations underpinned by uncertain boundary conditions or variant parameters. We adopt a Bayesian approach for parameter inference, delineating the establishment of prior, likelihood, and posterior distributions, and the subsequent resolution of the maximum a posteriori problem via numerical optimization techniques. The proposed algorithm is applied to the task of magnetic field reconstruction within a conical domain, demonstrating precise recovery of the true parameter values. © 2024, CC BY.

关键词： Differential equations

Cross sections for valence-shell excitations of H2O in the 9.85–12.15-eV energy-loss range studied by high-energy inelastic electron scattering

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Physical Review A 2022年第3期105卷 032801-032801页

作者： Wei-Qing Xu Yi-Geng Peng Jian-Hui Zhu Xiao-Jiao Du Yuan-Chen Xu Li-Han Wang Bo Li Hao-Ran Zhang Bei-Yuan Zhang Zi-Ru Ma Shu-Xing Wang Yong Wu Jian-Guo Wang Lin-Fan Zhu Center for Transformative Science ShanghaiTech University Shanghai 201210 China Department of Applied Physics Nanjing University of Science and Technology Nanjing 210094 China Institute of Applied Physics and Computational Mathematics Beijing 100088 China Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China Hefei Anhui 230026 China HEDPS Center for Applied Physics and Technology and College of Engineering Peking University Beijing 100871 China

The recent measurement of the generalized oscillator strengths (GOSs) for ÃB11 and B̃A11 of H2O exhibits the apparent deviations from the first Born approximation calculations in the large squared momentum transfer region [W. Q. Xu et al., Phys. Rev. A 103, 032808 (2021)]. Here a simplified theoretical model was proposed to calculate the GOSs of the two excitations at large momentum transfer within the second Born approximation. The accord of the experimental GOSs and the theoretical ones is improved, but the differences still exist. In addition, the GOSs and the integral cross sections for the higher excitations of H2O in 9.85–12.15 eV are presented, which could be used to complete the database of electron-impact excitation cross sections of H2O and be beneficial for modeling interaction processes between electrons and H2O in the earth's atmosphere, plasmas, radiation physics, biology, etc.

关键词： Electron & positron scattering Electronic excitation & ionization Electronic structure of atoms & molecules Molecular spectra Molecules Configuration interaction High-resolution electron energy loss spectroscopy

Investigation of astrophysical S-factor for 12C + 16O and 16O + 16O reactions within the relativistic mean-field approach 1

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Investigation of astrophysical S-factor for 12C + 16O and 16...

1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Rana, Shilpa Jain, N. Joshua, T.M. Bhuyan, M. Kumar, Raj School of Physics and Materials Science Thapar Institute of Engineering and Technology Punjab Patiala147004 India Institute of Engineering Mathematics Faculty of Applied and Human Sciences University Malaysia Perlis Perlis Arau02600 Malaysia Center for Theoretical and Computational Physics Department of Physics Faculty of Science University of Malaya Kuala Lumpur50603 Malaysia Institute of Research and Development Duy Tan University Da Nang 550000 Viet Nam

ISBN: (纸本)9781607685395

The fusion dynamics of 12C + 16O and 16O + 16O astrophysical reactions is investigated using the relativistic mean-field (RMF) formalism for the non-linear NL3* parameter set. The RMF densities, along with the widely adopted M3Y and relativistic R3Y nucleon-nucleon (NN) interaction potentials, are used to obtain the nuclear potential within the double folding approach. The -summed Wong model is used to obtain the fusion cross-section. The max values are extracted from the sharp cut-off model. The fusion cross-section is also represented in terms of the astrophysical S-factor, and the results are compared with the available experimental data. The microscopic R3Y NN potential is observed to give a reasonable fit to the experimental cross-section. © The Electrochemical Society

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Probing the state of hydrogen in δ−AlOOH at mantle conditions with machine learning potential

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Physical Review Research 2024年第1期6卷 013292-013292页

作者： Chenxing Luo Yang Sun Renata M. Wentzcovitch Department of Applied Physics and Applied Mathematics Columbia University New York New York 10027 USA Department of Physics and Astronomy Iowa State University Ames Iowa 50011 USA Department of Earth and Environmental Sciences Columbia University New York New York 10027 USA Lamont–Doherty Earth Observatory Columbia University Palisades New York 10964 USA Data Science Institute Columbia University New York New York 10027 USA Center for Computational Quantum Physics Flatiron Institute New York New York 10010 USA

Hydrous and nominally anhydrous minerals are a fundamental class of solids of enormous significance to geophysics. They are the water carriers in the deep geological water cycle and impact structural, elastic, plastic, and thermodynamic properties and phase relations in Earth's forming aggregates (rocks). They play a critical role in the geochemical and geophysical processes that shape the planet. Their complexity has prevented predictive calculations of their properties, but progress in materials simulations ushered by machine-learning potentials is transforming this state of affairs. Here, we adopt a hybrid approach that combines deep learning potentials (DPs) with the strongly constrained and appropriately normed meta-generalized gradient approximation functional to simulate a prototypical hydrous system. We illustrate the success of this approach to simulate δ−AlOOH (δ), a phase capable of transporting water down to near the core-mantle boundary of the Earth (∼2900km depth and ∼135GPa) in subducting slabs. A high-throughput sampling of phase space using molecular dynamics simulations with DPs sheds light on the hydrogen-bond behavior and proton diffusion at geophysical conditions. These simulations provide a pathway for a deeper understanding of these crucial components that shape Earth's internal state.

关键词： Diffusion Earth's interior Equations of state Hydrogen bonds Interatomic & molecular potentials Disordered systems Machine learning Molecular dynamics

PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming

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arXiv 2024年

作者： Li, Bingheng Yang, Linxin Chen, Yupeng Wang, Senmiao Mao, Haitao Chen, Qian Ma, Yao Wang, Akang Ding, Tian Tang, Jiliang Sun, Ruoyu Michigan State University United States School of Data Science The Chinese University of Hong Kong Shenzhen China Shenzhen International Center For Industrial and Applied Mathematics Shenzhen Research Institute of Big Data China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Rensselaer Polytechnic Institute United States

Solving large-scale linear programming (LP) problems is an important task in various areas such as communication networks, power systems, finance, and logistics. Recently, two distinct approaches have emerged to expedite LP solving: (i) First-order methods (FOMs);(ii) Learning to optimize (L2O). In this work, we propose a FOM-unrolled neural network (NN) called PDHG-Net, and propose a two-stage L2O method to solve large-scale LP problems. The new architecture PDHG-Net is designed by unrolling the recently emerged PDHG method into a neural network, combined with channel-expansion techniques borrowed from graph neural networks. We prove that the proposed PDHG-Net can recover PDHG algorithm, thus can approximate optimal solutions of LP instances with a polynomial number of neurons. We propose a two-stage inference approach: first use PDHG-Net to generate an approximate solution, and then apply the PDHG algorithm to further improve the solution. Experiments show that our approach can significantly accelerate LP solving, achieving up to a 3× speedup compared to FOMs for large-scale LP problems. © 2024, CC BY.

关键词： Linear programming

Effect of shapes degrees of freedom on the fusion cross-sections of 16O+154Sm and 18O+148Nd 1

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Effect of shapes degrees of freedom on the fusion cross-sect...

1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Jain, Nishu Rana, Shilpa Joshua, T.M. Kumar, Raj Bhuyan, M. School of Physics and Materials Science Thapar Institute of Engineering and Technology Patiala147004 India Institute of Engineering Mathematics Faculty of Applied and Human Sciences Universiti Malaysia Perlis Perlis Arau02600 Malaysia Center for Theoretical and Computational Physics Department of Physics Faculty of Science University of Malaya Kuala Lumpur50603 Malaysia Institute of Research and Development Duy Tan University Da Nang550000 Viet Nam

ISBN: (纸本)9781607685395

The fusion dynamics of 16O + 154Sm and 18O+148Nd reactions has been investigated to observe the effect of shape degree of freedom on the fusion cross-section using the coupled channel (CC) calculations. The one dimentional barrier penetration model (1-D BPM) is observed to underestimate the experimental data mainly at below barrier energies. The coupled channel calculations including target projectile excitations with 1 phonon of vibrational state and 2+ rotational state of target reproduce the experimental fusion cross-section for 16O + 154Sm reaction at below barrier energies while show some discrepancy for 18O+148Nd reaction. This discrepancy for 18O+148Nd reaction can be addressed with the inclusion of low-lying states with neutron transfer channels and the neck-formation. © The Electrochemical Society

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NONLINEAR ASYMPTOTIC STABILITY OF NON-SELF-SIMILAR RAREFACTION WAVE FOR TWO-DIMENSIONAL VISCOUS BURGERS EQUATION

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arXiv 2024年

作者： Huang, Feimin Qiu, Guiqin Wang, Yi Yang, Xiaozhou Institute of Applied Mathematics AMSS Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Wuhan Institute of Physics and Mathematics Innovation Academy for Precision Measurement Science and Technology Wuhan430071 China

We investigate the large time behavior of solutions to the two-dimensional viscous Burgers equation ut ` uux ` uuy "∆u, toward a non-self-similar rarefaction wave of inviscid Burgers equation with two initial constant states, seperated by a curve y "φpxq, and prove that the above 2D non-self-similar rarefaction wave is time-asymptotically stable. Furthermore, we can get the decay rate. Both the rarefaction wave strength and the initial perturbation can be large. The main difficulty comes from the fact that the initial discontinuity of 2D non-self-similar rarefaction is a curve y "φpxq, while the initial discontinuity of self-similar rarefaction is either a point in 1D or a straight line in 2D. Fortunately, we uncover a novel property that the non-self-similar inviscid rarefaction wave is also asymptotically stable with respect to the discontinuity curve y "φpxq. More precisely, let uRi px, y, tq, i "1, 2 be the corresponding non-self-similar rarefaction with the initial discontinuity curve y "φipxq, then }uR1 ´uR2 }L8 ď Ct if }φ1pxq ´ φ2pxq}L8 is bounded. Based on this property, any curve y "φpxq can be classified as a standard polyline Lpxq "# kk´`xx``c,c,xxăě00 where limxÑ8 φpxxq "k. Then we construct the approximate smooth rarefaction wave of the viscous Burgers equations based on the above polyline, and convert this wave to the self-similar planar rarefaction one through a new nonlinear coordinate transformation with the price that the 2D viscous Burgers equation is changed into a parabolic equation with variable and mixed derivative viscosities. Another advantage is that the main error terms generated by the new approximate smooth rarefaction in the new parabolic equation are integrable in R2. This approach enables us to overcome the main difficulty mentioned above. Finally, the time-asymptotic stability analysis is carried out to the viscous rarefaction wave and the transformed 2D viscous Burgers equation by using suitable time-weighted Lp-energy estimates, wh

关键词： Nonlinear equations

M-QR decomposition and hyperpower iterative methods for computing outer inverses of tensors

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arXiv 2024年

作者： Behera, Ratikanta Panigrahy, Krushnachandra Sahoo, Jajati Keshari Wei, Yimin Department of Computational and Data Sciences Indian Institute of Science Bangalore560012 India Department of Mathematics BITS Pilani K.K. Birla Goa Campus Goa India School of Mathematics Sciences Shanghai Key Laboratory of Contemporary Applied Mathematics Fudan University Shanghai200433 China

The outer inverse of tensors plays increasingly significant roles in computational mathematics, numerical analysis, and other generalized inverses of tensors. In this paper, we compute outer inverses with prescribed ranges and kernels of a given tensor through tensor QR decomposition and hyperpower iterative method under the M−product structure, which is a family of tensor–tensor products, generalization of the t-product and c-product, allows us to suit the physical interpretations across those different modes. We discuss a theoretical analysis of the nineteen-order convergence of the proposed tensor-based iterative method. Further, we design effective tensor-based algorithms for computing outer inverses using M−QR decomposition and hyperpower iterative method. The theoretical results are validated with numerical examples demonstrating the appropriateness of the proposed methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Tensors