Physics-Informed Neural Networks(PINNs)have emerged as a powerful tool for solving high-dimensional partial differential equations and have demonstrated promising results across various fields of physics and engineeri...Physics-Informed Neural Networks(PINNs)have emerged as a powerful tool for solving high-dimensional partial differential equations and have demonstrated promising results across various fields of physics and engineering.In this paper,we present the first application of PINNs to quantum tunneling in heavy-ion fusion reactions.By incorporating the physical laws directly into the neural network's loss function,PINNs enable the accurate solution of the multidimensional Schr?dinger equation,whose wavefunction has substantial oscillations.The calculated quantum tunneling probabilities exhibit good agreement with those obtained using the finite element method at the considered near barrier energy region.Furthermore,we demonstrate a significant advantage of the PINN approach to save and fine-tune pre-trained neural networks for related tunneling calculations,thereby enhancing computational efficiency and adaptability.展开更多
To study the coupling effect of the positive Q-value two-neutron stripping channel in the sub-barrier of^(18)O+^(50)Cr,the fusion excitation functions were measured for the^(16,18)O+^(50)Cr systems at energies near an...To study the coupling effect of the positive Q-value two-neutron stripping channel in the sub-barrier of^(18)O+^(50)Cr,the fusion excitation functions were measured for the^(16,18)O+^(50)Cr systems at energies near and below the Coulomb barriers by using the electrostatic deflector setup.16O+^(50)Cr was selected as a reference system.The coupling effect of the low-lying collective excitation states in sub-barrier fusion was considered based on coupledchannels calculations.For^(18)O+^(50)Cr,the calculated fusion cross-sections of coupled channels,including the lowest 2^(+)vibrational states of the target nucleus and projectile,give subtle under-estimation for the experimental ones at energies below the Coulomb barrier.This means that there is limited room for the transfer effect in^(18)O+^(50)Cr,compared to the widely accepted argument of positive Q-value 2n-transfer remarkably enhancing the sub-barrier fusion cross-sections.Analogous systems of neutron-rich^(18)O-induced fusion in existing literature show the same peculiarity that the positive Q-value two-neutron stripping channel has no remarkable influence on enhancing sub-barrier fusion cross-sections.展开更多
The establishment of a possible connection between neutrino emission and gravitational-wave(GW)bursts is important to our understanding of the physical processes that occur when black holes or neutron stars merge.In t...The establishment of a possible connection between neutrino emission and gravitational-wave(GW)bursts is important to our understanding of the physical processes that occur when black holes or neutron stars merge.In the Daya Bay experiment,using the data collected from December 2011 to August 2017,a search was per-formed for electron-antineutrino signals that coincided with detected GW events,including GW150914,GW151012,GW151226,GW170104,GW170608,GW 170814,and GW 170817.We used three time windows of±10,±500,and±1000 s relative to the occurrence of the GW events and a neutrino energy range of 1.8 to 100 MeV to search for correlated neutrino candidates.The detected electron-antineutrino candidates were consistent with the expected background rates for all the three time windows.Assuming monochromatic spectra,we found upper limits(90%confidence level)of the electron-antineutrino fluence of(1.13-2.44)×10^(11)cm^(-2)at 5 MeV to 8.0×10^(7)cm^(-2)at 100 MeV for the three time w indows.Under the assumption of a Fermi-Dirac spectrum,the upper limits were found to be(5.4-7.0)×10^(9)cm^(2)for the three time windows.展开更多
The prediction of reactor antineutrino spectra will play a crucial role as reactor experiments enter the precision era.The positron energy spectrum of 3.5 million antineutrino inverse beta decay reactions observed by ...The prediction of reactor antineutrino spectra will play a crucial role as reactor experiments enter the precision era.The positron energy spectrum of 3.5 million antineutrino inverse beta decay reactions observed by the Daya Bay experiment,in combination with the fission rates of fissile isotopes in the reactor,is used to extract the positron energy spectra resulting from the fission of specific isotopes.This information can be used to produce a precise,data-based prediction of the antineutrino energy spectrum in other reactor antineutrino experiments with different fission fractions than Daya Bay.The positron energy spectra are unfolded to obtain the antineutrino energy spectra by removing the contribution from detector response with the Wiener-SVD unfolding method.Consistent results are obtained with other unfolding methods.A technique to construct a data-based prediction of the reactor antineutrino energy spectrum is proposed and investigated.Given the reactor fission fractions,the technique can predict the energy spectrum to a 2%precision.In addition,we illustrate how to perform a rigorous comparison between the unfolded antineutrino spectrum and a theoretical model prediction that avoids the input model bias of the unfolding method.展开更多
基金Supported by the National Key R&D Program of China(2024YFE0109804,2023YFA1606402,2022YFA1602302)the National Natural Science Foundation of China(U2167204,12375130,12175313,12175314,12235020,12275360)+3 种基金the Director's Foundation of Department of Nuclear Physics(12SZJJ-202305)the Dean's Foundation of China Institute of Atomic Energy(12YZ010270624219)the Continuous Basic Scientific Research ProjectBasic Research Special Zone。
文摘Physics-Informed Neural Networks(PINNs)have emerged as a powerful tool for solving high-dimensional partial differential equations and have demonstrated promising results across various fields of physics and engineering.In this paper,we present the first application of PINNs to quantum tunneling in heavy-ion fusion reactions.By incorporating the physical laws directly into the neural network's loss function,PINNs enable the accurate solution of the multidimensional Schr?dinger equation,whose wavefunction has substantial oscillations.The calculated quantum tunneling probabilities exhibit good agreement with those obtained using the finite element method at the considered near barrier energy region.Furthermore,we demonstrate a significant advantage of the PINN approach to save and fine-tune pre-trained neural networks for related tunneling calculations,thereby enhancing computational efficiency and adaptability.
基金Supported by the National Key R&D Program of China(2023YFA1606402,2022YFA1602302)the National Natural Science Foundation of China(U2167204,12175314,12275360,12235020)the Continuous-Support Basic Scientific Research Project。
文摘To study the coupling effect of the positive Q-value two-neutron stripping channel in the sub-barrier of^(18)O+^(50)Cr,the fusion excitation functions were measured for the^(16,18)O+^(50)Cr systems at energies near and below the Coulomb barriers by using the electrostatic deflector setup.16O+^(50)Cr was selected as a reference system.The coupling effect of the low-lying collective excitation states in sub-barrier fusion was considered based on coupledchannels calculations.For^(18)O+^(50)Cr,the calculated fusion cross-sections of coupled channels,including the lowest 2^(+)vibrational states of the target nucleus and projectile,give subtle under-estimation for the experimental ones at energies below the Coulomb barrier.This means that there is limited room for the transfer effect in^(18)O+^(50)Cr,compared to the widely accepted argument of positive Q-value 2n-transfer remarkably enhancing the sub-barrier fusion cross-sections.Analogous systems of neutron-rich^(18)O-induced fusion in existing literature show the same peculiarity that the positive Q-value two-neutron stripping channel has no remarkable influence on enhancing sub-barrier fusion cross-sections.
基金Daya Bay is supported in part by the Ministry of Science and Technology o f China, the U.S. Department o f Energy, the Chinese Academy of Sciences, the CASCenter for Excellence in Particle Physics, the National Natural Science Foundation of China, the Guangdong provincial government, the Shenzhen municipal government,the China General Nuclear Power Group, Key Laboratory of Particle and Radiation Imaging (Tsinghua University), the Ministry of Education, Key Laboratory ofParticle Physics and Particle Irradiation (Shandong University), the Ministry o f Education, Shanghai Laboratory for Particle Physics and Cosmology, the ResearchGrants Council o f the Hong Kong Special Administrative Region of China, the University Development Fund of the University of Hong Kong, the MOE program forResearch of Excellence at National Taiwan University, National Chiao-Tung University, NSC fund support from Taiwan, the U.S. National Science Foundation, the AlfredP. Sloan Foundation, the Ministry o f Education, Youth, and Sports of the Czech Republic, the Charles University GAUK (284317), the Joint Institute o f NuclearResearch in Dubna, Russia, the National Commission of Scientific and Technological Research of Chile, and the Tsinghua University Initiative Scientific Research Program.
文摘The establishment of a possible connection between neutrino emission and gravitational-wave(GW)bursts is important to our understanding of the physical processes that occur when black holes or neutron stars merge.In the Daya Bay experiment,using the data collected from December 2011 to August 2017,a search was per-formed for electron-antineutrino signals that coincided with detected GW events,including GW150914,GW151012,GW151226,GW170104,GW170608,GW 170814,and GW 170817.We used three time windows of±10,±500,and±1000 s relative to the occurrence of the GW events and a neutrino energy range of 1.8 to 100 MeV to search for correlated neutrino candidates.The detected electron-antineutrino candidates were consistent with the expected background rates for all the three time windows.Assuming monochromatic spectra,we found upper limits(90%confidence level)of the electron-antineutrino fluence of(1.13-2.44)×10^(11)cm^(-2)at 5 MeV to 8.0×10^(7)cm^(-2)at 100 MeV for the three time w indows.Under the assumption of a Fermi-Dirac spectrum,the upper limits were found to be(5.4-7.0)×10^(9)cm^(2)for the three time windows.
基金Supported in part by the Ministry of Science and Technology of Chinathe U.S.Department of Energy,the Chinese Academy of Sciences,the CAS Center for Excellence in Particle Physics,the National Natural Science Foundation of China+3 种基金the Guangdong provincial governmentthe Shenzhen municipal government,the China General Nuclear Power Group,the Research Grants Council of the Hong Kong Special Administrative Region of China,the Ministry of Education in TWthe U.S.National Science Foundation,the Ministry of Education,Youth,and Sports of the Czech Republic,the Charles University Research Centre UNCE,the Joint Institute of Nuclear Research in Dubna,Russiathe National Commission of Scientific and Technological Research of Chile。
文摘The prediction of reactor antineutrino spectra will play a crucial role as reactor experiments enter the precision era.The positron energy spectrum of 3.5 million antineutrino inverse beta decay reactions observed by the Daya Bay experiment,in combination with the fission rates of fissile isotopes in the reactor,is used to extract the positron energy spectra resulting from the fission of specific isotopes.This information can be used to produce a precise,data-based prediction of the antineutrino energy spectrum in other reactor antineutrino experiments with different fission fractions than Daya Bay.The positron energy spectra are unfolded to obtain the antineutrino energy spectra by removing the contribution from detector response with the Wiener-SVD unfolding method.Consistent results are obtained with other unfolding methods.A technique to construct a data-based prediction of the reactor antineutrino energy spectrum is proposed and investigated.Given the reactor fission fractions,the technique can predict the energy spectrum to a 2%precision.In addition,we illustrate how to perform a rigorous comparison between the unfolded antineutrino spectrum and a theoretical model prediction that avoids the input model bias of the unfolding method.
