Integrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research,where the primary challenge lies in the computational intensity of calculating the electron-p...Integrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research,where the primary challenge lies in the computational intensity of calculating the electron-phonon spectral function,α2F(ω),the essential ingredient of Midgal-Eliashberg theory of superconductivity.To overcome this challenge,we adopt a two-step approach.First,we computeα2F(ω)for 818 dynamically stable materials.We then train a deep-learning model to predictα2F(ω),using a training strategy tailored for limited data to temper the model’s overfitting,enhancing predictions.Specifically,we train a Bootstrapped Ensemble of Tempered Equivariant graph neural NETworks(BETE-NET),obtaining an MAE of 0.21,45 K,and 43 K for the moments derived fromα2F(ω):λ,\({\omega}_{\log}\),andω2,respectively,yielding an MAE of 2.5 K for the critical temperature,Tc.Further,we incorporate domain knowledge of the site-projected phonon density of states to impose inductive bias into the model’s node attributes and enhance predictions.This methodological innovation decreases the MAE to 0.18,29 K,and 28 K,respectively,yielding an MAE of 2.1 K for Tc.We illustrate the practical application of our model in high-throughput screening for high-Tc materials.The model demonstrates an average precision nearly five times higher than random screening,highlighting the potential of ML in accelerating superconductor discovery.BETE-NET accelerates the search for high-Tc superconductors while setting a precedent for applying ML in materials discovery,particularly when data is limited.展开更多
In this paper,we define the spectral Einstein functional associated with the Dirac operator for manifolds with boundary.And we give the proof of Kastler-Kalau-Walze type theorem for the spectral Einstein functional as...In this paper,we define the spectral Einstein functional associated with the Dirac operator for manifolds with boundary.And we give the proof of Kastler-Kalau-Walze type theorem for the spectral Einstein functional associated with the Dirac operator on 4-dimensional manifolds with boundary.展开更多
In this paper,we give the definitions of the non-self-adjoint spectral triple and its spectral Einstein functional.We compute the spectral Einstein functional associated with the nonminimal de Rham-Hodge operator on e...In this paper,we give the definitions of the non-self-adjoint spectral triple and its spectral Einstein functional.We compute the spectral Einstein functional associated with the nonminimal de Rham-Hodge operator on evendimensional compact manifolds without boundary.Finally,several examples of the non-self-adjoint spectral triple are listed.展开更多
We characterize the surjective additive maps compressing the spectral function Δ（·） between standard operator algebras acting on complex Banach spaces, where Δ（·） stands for any one of nine spectral fu...We characterize the surjective additive maps compressing the spectral function Δ（·） between standard operator algebras acting on complex Banach spaces, where Δ（·） stands for any one of nine spectral functions σ（·）, σl（·）, σr（·）,σl（·） ∩ σr（·）, δσ（·）, ησ（·）, σap（·）, σs（·）, and σap（·） ∩ σs（·）.展开更多
Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalize...Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.展开更多
Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few wo...Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.展开更多
In this paper, we make use of the functional spectral analysis to infer the periodicity of paleoclimate in the Hongzuisi section since about 15 ka. Through combined analysis of organic carbon isotope and CaCO\-3 conte...In this paper, we make use of the functional spectral analysis to infer the periodicity of paleoclimate in the Hongzuisi section since about 15 ka. Through combined analysis of organic carbon isotope and CaCO\-3 content, the law of paleoclimatic evolution of the Hongzuisi section is obtained. There were climatic changes from 10 ka to about 0.1 ka over the last 15 ka. Among these cycles, the cycle of several ka is most remarkable. The result indicates that functional spectral analysis is helpful for paleoclimatic study, which can provide useful information about paleoclimatic reconstruction and future forecast.展开更多
We study the quark-antiquark scattering phase shift and meson spectral function in the pion superfluid described by the Nambu-Jona-Lasinio model. Meson mixing in the pion superfluid dramatically changes the full scatt...We study the quark-antiquark scattering phase shift and meson spectral function in the pion superfluid described by the Nambu-Jona-Lasinio model. Meson mixing in the pion superfluid dramatically changes the full scattering phase shift and significantly broadens the spectral function of some collective modes.展开更多
We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation...We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation. It is found that the bunching phenomenon is independent of the biexciton binding energy when it varies from 0.59 meV to nearly zero. The photon bunching takes place when the exeiton photon is not spectrally distinguishable from the biexciton photon, and either of them can trigger the %tart＇ in a Hanbury-Brown and Twiss setup. However, if the exciton energy is spectrally distinguishable from the biexciton, the photon statistics will become asymmetric and a cross-bunching lineshape can be obtained. The theoretical calculations based on a model of three-level rate-equation analysis are consistent with the result of g（2）（τ） correlation function measurements.展开更多
The main purpose of this paper is to show that the Poincaré q-polynomials admit a representation in terms of the symmetric functions and the Patterson-Selberg (or Ruelle-type) spectral functions. We have shown th...The main purpose of this paper is to show that the Poincaré q-polynomials admit a representation in terms of the symmetric functions and the Patterson-Selberg (or Ruelle-type) spectral functions. We have shown that the q-series elliptic genera can be expressed in terms of q-analogs of the classical special functions, specially the equivalence between the spectral Patterson-Selberg and the Ruelle functions. The main result of this manuscript is to show that this representation can be used in theoretical physics and we analyze them in terms of the Patterson-Selberg spectral function R (s).展开更多
By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of t...By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,respectively.From this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,andΓ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network models.Detailed analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and BiLSTM.The MAE peak of BiGRU+GRU reaches 0.00037.We have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent datasets.The ResNet has the worst performance among all the seven network models.The datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://doi.org/10.57760/sciencedb.j00113.00192.展开更多
In this paper, the spectral element method(SEM)is improved to solve the moving load problem. In this method, a structure with uniform geometry and material properties is considered as a spectral element, which means t...In this paper, the spectral element method(SEM)is improved to solve the moving load problem. In this method, a structure with uniform geometry and material properties is considered as a spectral element, which means that the element number and the degree of freedom can be reduced significantly. Based on the variational method and the Laplace transform theory, the spectral stiffness matrix and the equivalent nodal force of the beam-column element are established. The static Green function is employed to deduce the improved function. The proposed method is applied to two typical engineering practices—the one-span bridge and the horizontal jib of the tower crane. The results have revealed the following. First, the new method can yield extremely high-precision results of the dynamic deflection, the bending moment and the shear force in the moving load problem.In most cases, the relative errors are smaller than 1%. Second, by comparing with the finite element method, one can obtain the highly accurate results using the improved SEM with smaller element numbers. Moreover, the method can be widely used for statically determinate as well as statically indeterminate structures. Third, the dynamic deflection of the twin-lift jib decreases with the increase in the moving load speed, whereas the curvature of the deflection increases.Finally, the dynamic deflection, the bending moment and the shear force of the jib will all increase as the magnitude of the moving load increases.展开更多
A generalized finite spectral method is proposed. The method is of highorder accuracy. To attain high accuracy in time discretization, the fourth-order AdamsBashforth-Moulton predictor and corrector scheme was used. T...A generalized finite spectral method is proposed. The method is of highorder accuracy. To attain high accuracy in time discretization, the fourth-order AdamsBashforth-Moulton predictor and corrector scheme was used. To avoid numerical oscillations caused by the dispersion term in the KdV equation, two numerical techniques were introduced to improve the numerical stability. The Legendre, Chebyshev and Hermite polynomials were used as the basis functions. The proposed numerical scheme is validated by applications to the Burgers equation （nonlinear convection- diffusion problem） and KdV equation（single solitary and 2-solitary wave problems）, where analytical solutions are available for comparison. Numerical results agree very well with the corresponding analytical solutions in all cases.展开更多
The drag-free satellites are widely used in the field of fundamental science as they enable the high-precision measurement in pure gravity fields. This paper investigates the estimation of local orbital reference fram...The drag-free satellites are widely used in the field of fundamental science as they enable the high-precision measurement in pure gravity fields. This paper investigates the estimation of local orbital reference frame(LORF) for drag-free satellites. An approach, taking account of the combination of the minimum estimation error and power spectral density(PSD) constraint in frequency domain, is proposed. Firstly, the relationship between eigenvalues of estimator and transfer function is built to analyze the suppression and amplification effect on input signals and obtain the eigenvalue range. Secondly, an optimization model for state estimator design with minimum estimation error in time domain and PSD constraint in frequency domain is established. It is solved by the sequential quadratic programming(SQP) algorithm. Finally, the orbital reference frame estimation of low-earth-orbit satellite is taken as an example, and the estimator of minimum variance with PSD constraint is designed and analyzed using the method proposed in this paper.展开更多
We analyze the spectral distribution of localisation in a 1D diagonally disordered chain of fragments each of which consist of m coupled two-level systems. The calculations performed by means of developed perturbation...We analyze the spectral distribution of localisation in a 1D diagonally disordered chain of fragments each of which consist of m coupled two-level systems. The calculations performed by means of developed perturbation theory for joint statistics of advanced and retarded Green’s functions. We show that this distribution is rather inhomogeneous and reveals spectral regions of weakly localized states with sharp peaks of the localization degree in the centers of these regions.展开更多
基金funded by the U.S.National Science Foundation,Division of Materials Research,under Contract No.NSF-DMR-2118718.A.C.H.and R.G.H.acknowledge additional support from the National Science Foundation under award PHY-1549132(Center for Bright Beams)Part of this research was performed while J.B.G.,A.C.H.,and R.G.H.were visiting the Institute for Pure and Applied Mathematics(IPAM),which is supported by the National Science Foundation(Grant No.DMS-1925919)P.M.D was supported by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,under Award Number DE-SC0022311,during the writing and analysis stages of the project.Computational resources were provided by the University of Florida Research Computing Center.
文摘Integrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research,where the primary challenge lies in the computational intensity of calculating the electron-phonon spectral function,α2F(ω),the essential ingredient of Midgal-Eliashberg theory of superconductivity.To overcome this challenge,we adopt a two-step approach.First,we computeα2F(ω)for 818 dynamically stable materials.We then train a deep-learning model to predictα2F(ω),using a training strategy tailored for limited data to temper the model’s overfitting,enhancing predictions.Specifically,we train a Bootstrapped Ensemble of Tempered Equivariant graph neural NETworks(BETE-NET),obtaining an MAE of 0.21,45 K,and 43 K for the moments derived fromα2F(ω):λ,\({\omega}_{\log}\),andω2,respectively,yielding an MAE of 2.5 K for the critical temperature,Tc.Further,we incorporate domain knowledge of the site-projected phonon density of states to impose inductive bias into the model’s node attributes and enhance predictions.This methodological innovation decreases the MAE to 0.18,29 K,and 28 K,respectively,yielding an MAE of 2.1 K for Tc.We illustrate the practical application of our model in high-throughput screening for high-Tc materials.The model demonstrates an average precision nearly five times higher than random screening,highlighting the potential of ML in accelerating superconductor discovery.BETE-NET accelerates the search for high-Tc superconductors while setting a precedent for applying ML in materials discovery,particularly when data is limited.
文摘In this paper,we define the spectral Einstein functional associated with the Dirac operator for manifolds with boundary.And we give the proof of Kastler-Kalau-Walze type theorem for the spectral Einstein functional associated with the Dirac operator on 4-dimensional manifolds with boundary.
基金supported by the National Natural Science Foundation of China(Grant No.11771070).
文摘In this paper,we give the definitions of the non-self-adjoint spectral triple and its spectral Einstein functional.We compute the spectral Einstein functional associated with the nonminimal de Rham-Hodge operator on evendimensional compact manifolds without boundary.Finally,several examples of the non-self-adjoint spectral triple are listed.
基金Natural Science Foundation of ChinaGrant for Returned Scholars of Shanxi
文摘We characterize the surjective additive maps compressing the spectral function Δ（·） between standard operator algebras acting on complex Banach spaces, where Δ（·） stands for any one of nine spectral functions σ（·）, σl（·）, σr（·）,σl（·） ∩ σr（·）, δσ（·）, ησ（·）, σap（·）, σs（·）, and σap（·） ∩ σs（·）.
基金Supported by State Key Laboratory of InformationSecurity Opening Foundation(01-02) .
文摘Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.
基金the Postdoctoral ScienceFoundation of China(No.2023M730156)the NationalNatural Foundation of China(No.62301012).
文摘Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.
基金GrantedbytheNationalNaturalScienceFoundationofChina (No .4 9972 0 5 7)
文摘In this paper, we make use of the functional spectral analysis to infer the periodicity of paleoclimate in the Hongzuisi section since about 15 ka. Through combined analysis of organic carbon isotope and CaCO\-3 content, the law of paleoclimatic evolution of the Hongzuisi section is obtained. There were climatic changes from 10 ka to about 0.1 ka over the last 15 ka. Among these cycles, the cycle of several ka is most remarkable. The result indicates that functional spectral analysis is helpful for paleoclimatic study, which can provide useful information about paleoclimatic reconstruction and future forecast.
基金Supported by the NSFC(11775165)Fundamental Research Funds for the Central Universities
文摘We study the quark-antiquark scattering phase shift and meson spectral function in the pion superfluid described by the Nambu-Jona-Lasinio model. Meson mixing in the pion superfluid dramatically changes the full scattering phase shift and significantly broadens the spectral function of some collective modes.
基金Supported by the National Key Basic Research Program of China under Grant No 2013CB922304the National Natural Science Foundation of China under Grant Nos 11474275 and 11464034
文摘We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation. It is found that the bunching phenomenon is independent of the biexciton binding energy when it varies from 0.59 meV to nearly zero. The photon bunching takes place when the exeiton photon is not spectrally distinguishable from the biexciton photon, and either of them can trigger the %tart＇ in a Hanbury-Brown and Twiss setup. However, if the exciton energy is spectrally distinguishable from the biexciton, the photon statistics will become asymmetric and a cross-bunching lineshape can be obtained. The theoretical calculations based on a model of three-level rate-equation analysis are consistent with the result of g（2）（τ） correlation function measurements.
文摘The main purpose of this paper is to show that the Poincaré q-polynomials admit a representation in terms of the symmetric functions and the Patterson-Selberg (or Ruelle-type) spectral functions. We have shown that the q-series elliptic genera can be expressed in terms of q-analogs of the classical special functions, specially the equivalence between the spectral Patterson-Selberg and the Ruelle functions. The main result of this manuscript is to show that this representation can be used in theoretical physics and we analyze them in terms of the Patterson-Selberg spectral function R (s).
基金Project supported by the National Natural Science Foundation of China(Grant No.12174101)the Fundamental Research Funds for the Central Universities(Grant No.2022MS051)。
文摘By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,respectively.From this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,andΓ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network models.Detailed analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and BiLSTM.The MAE peak of BiGRU+GRU reaches 0.00037.We have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent datasets.The ResNet has the worst performance among all the seven network models.The datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://doi.org/10.57760/sciencedb.j00113.00192.
基金supported by the National Key Technology R&D Program (Grant 2011BAJ02B01-02)the National Natural Science Foundation of China (Grant 11602065)
文摘In this paper, the spectral element method(SEM)is improved to solve the moving load problem. In this method, a structure with uniform geometry and material properties is considered as a spectral element, which means that the element number and the degree of freedom can be reduced significantly. Based on the variational method and the Laplace transform theory, the spectral stiffness matrix and the equivalent nodal force of the beam-column element are established. The static Green function is employed to deduce the improved function. The proposed method is applied to two typical engineering practices—the one-span bridge and the horizontal jib of the tower crane. The results have revealed the following. First, the new method can yield extremely high-precision results of the dynamic deflection, the bending moment and the shear force in the moving load problem.In most cases, the relative errors are smaller than 1%. Second, by comparing with the finite element method, one can obtain the highly accurate results using the improved SEM with smaller element numbers. Moreover, the method can be widely used for statically determinate as well as statically indeterminate structures. Third, the dynamic deflection of the twin-lift jib decreases with the increase in the moving load speed, whereas the curvature of the deflection increases.Finally, the dynamic deflection, the bending moment and the shear force of the jib will all increase as the magnitude of the moving load increases.
基金Project supported by the National Natural Science Foundation of China (No.10272118) the Hong Kong Polytechnic University Research Grant (No.A-PE28) the Research Fund for the Doctoral Program of Ministry of Education of China (No.20020558013)
文摘A generalized finite spectral method is proposed. The method is of highorder accuracy. To attain high accuracy in time discretization, the fourth-order AdamsBashforth-Moulton predictor and corrector scheme was used. To avoid numerical oscillations caused by the dispersion term in the KdV equation, two numerical techniques were introduced to improve the numerical stability. The Legendre, Chebyshev and Hermite polynomials were used as the basis functions. The proposed numerical scheme is validated by applications to the Burgers equation （nonlinear convection- diffusion problem） and KdV equation（single solitary and 2-solitary wave problems）, where analytical solutions are available for comparison. Numerical results agree very well with the corresponding analytical solutions in all cases.
基金co-supported by the Open Fund of Joint Key Laboratory of Microsatellite of CAS (No. KFKT15SYS1)the Innovation Foundation of CAS (No. CXJJ-14-Q52)
文摘The drag-free satellites are widely used in the field of fundamental science as they enable the high-precision measurement in pure gravity fields. This paper investigates the estimation of local orbital reference frame(LORF) for drag-free satellites. An approach, taking account of the combination of the minimum estimation error and power spectral density(PSD) constraint in frequency domain, is proposed. Firstly, the relationship between eigenvalues of estimator and transfer function is built to analyze the suppression and amplification effect on input signals and obtain the eigenvalue range. Secondly, an optimization model for state estimator design with minimum estimation error in time domain and PSD constraint in frequency domain is established. It is solved by the sequential quadratic programming(SQP) algorithm. Finally, the orbital reference frame estimation of low-earth-orbit satellite is taken as an example, and the estimator of minimum variance with PSD constraint is designed and analyzed using the method proposed in this paper.
文摘We analyze the spectral distribution of localisation in a 1D diagonally disordered chain of fragments each of which consist of m coupled two-level systems. The calculations performed by means of developed perturbation theory for joint statistics of advanced and retarded Green’s functions. We show that this distribution is rather inhomogeneous and reveals spectral regions of weakly localized states with sharp peaks of the localization degree in the centers of these regions.
