Among the charged leptons,theτelectric dipole moment dτis the least constrained.We show that the Im[d_(τ)]imposes strong constraints on new physics that have yet to be discussed.Motivated in particular by the Super...Among the charged leptons,theτelectric dipole moment dτis the least constrained.We show that the Im[d_(τ)]imposes strong constraints on new physics that have yet to be discussed.Motivated in particular by the Super Tau-Charm Facility(STCF),which will provide a uniquely clean environment for precisionτ-physics,we study the momentum-transfer dependence of d_(τ)(q^(2))and compare the projected sensitivities of STCF and BelleⅡ.Our analysis shows that an axion-like coupling of the τ lepton can induce sizable real and imaginary components of the EDM.The predicted EDM values may approach the present experimental sensitivities,making them accessible to future measurements at Belle II and the STCF.展开更多
Ultrafast optical spectroscopy was successfully introduced decades ago.Its deep relationship with condensed matter physics profoundly enriched the scientific frontier of light–matter interactions.Previously,materials...Ultrafast optical spectroscopy was successfully introduced decades ago.Its deep relationship with condensed matter physics profoundly enriched the scientific frontier of light–matter interactions.Previously,materials such as metals,insulators,semiconductors,and superconductors were investigated,followed by magnetic materials,strongly correlated materials,complex oxides,nano-materials,topological materials,and metamaterials.展开更多
In response to the capabilities presented by the High-Intensity Heavy Ion Accelerator Facility(HIAF) and the Accelerator-Driven Subcritical System(Ci ADS), as well as the proposed Chinese Advanced Nuclear Physics Rese...In response to the capabilities presented by the High-Intensity Heavy Ion Accelerator Facility(HIAF) and the Accelerator-Driven Subcritical System(Ci ADS), as well as the proposed Chinese Advanced Nuclear Physics Research Facility(CNUF), we are assembling a consortium of experts in relevant disciplines, both domestically and internationally,to delineate high-precision physics experiments that leverage the state-of-the-art research environment afforded by CNUF.Our focus encompasses six primary domains of inquiry: hadron physics—including endeavors such as the super eta factory and investigations into light hadron structures;muon physics;neutrino physics;neutron physics;the testing of fundamental symmetries;and the exploration of quantum effects within nuclear physics, along with the utilization of vortex accelerators.We aim to foster a well-rounded portfolio of large, medium, and small-scale projects, thus unlocking new scientific avenues and optimizing the potential of the Huizhou large scientific facility. The aspiration for international leadership in scientific research will be a guiding principle in our strategic planning. This initiative will serve as a foundational reference for the Institute of Modern Physics in its strategic planning and goal-setting, ensuring alignment with its developmental objectives while striving to secure a competitive edge in technological advancement. Our ambition is to engage in substantive research within these realms of high-precision physics, to pursue groundbreaking discoveries, and to stimulate progress in China's nuclear physics landscape, positioning Huizhou as a preeminent global hub for advanced nuclear physics research.展开更多
This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the pred...This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.展开更多
To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produce...To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produced by the tandem-accelerator in the China Institute of Atomic Energy was utilized.The proton beam was first transmitted through a 60.5μm aluminum foil and then impinged on a natural LiF target to produce neutron beam via^(7)Li(p,n)7Be reaction.The quasi-Gaussian energy distribution of protons in the LiF target resulted in neutron energy spectra that agreed with a Maxwellian energy distribution at kT=(22±2)keV,which was achieved by integrating neutrons detected within an emission angle of 65.0°±2.6°using a ^(6)Li glass detector positioned at 65°relative to the proton beam direction.The narrow angular spread of the Maxwelliandistributed neutron beam enables direct measurement of neutron capture cross-sections for most s-process nuclides,overcoming previous experimental limitations associated with broad angular distributions.展开更多
Low-dimensional physics provides profound insights into strongly correlated interactions,leading to enhancedquantum effects and the emergence of exotic quantum states.The Ln_(3)ScBi_(5)family stands out as a chemicall...Low-dimensional physics provides profound insights into strongly correlated interactions,leading to enhancedquantum effects and the emergence of exotic quantum states.The Ln_(3)ScBi_(5)family stands out as a chemicallyversatile kagome platform with mixed low-dimensional structural framework and tunable physical properties.Ourresearch initiates with a comprehensive evaluation of the currently known Ln_(3)ScBi_(5)(Ln=La-Nd,Sm)materials,providing a robust methodology for assessing their stability frontiers within this system.Focusing on Pr_(3)ScBi_(5),we investigate the influence of the zigzag chains of quasi-one-dimensional(Q1D)motifs and the distorted kagomelayers of quasi-two-dimensional(Q2D)networks in the mixed-dimensional structure on the intricate magneticground states and unique spin fluctuations.Our study reveals that the noncollinear antiferromagnetic(AFM)moments of Pr^(3+)ions are confined within the Q2D kagome planes,displaying minimal in-plane anisotropy.Incontrast,a strong AFM coupling is observed within the Q1D zigzag chains,significantly constraining spin motion.Notably,magnetic frustration is partially a consequence of coupling to conduction electrons via Ruderman-Kittel-Kasuya-Yosida interaction,highlighting a promising framework for future investigations into mixed-dimensional frustration in Ln_(3)ScBi_(5) systems.展开更多
The challenge in searching for fundamental symmetry violation.Neutrinoless double-beta(0νββ)decay represents one of the most profound tests of fundamental symmetries in nature.This hypothetical nuclear process,in w...The challenge in searching for fundamental symmetry violation.Neutrinoless double-beta(0νββ)decay represents one of the most profound tests of fundamental symmetries in nature.This hypothetical nuclear process,in which two neutrons simultaneously decay into two protons with the emission of two electrons but no neutrinos,would demonstrate that lepton number is not conserved and confirm that neutrinos are their own antiparticles(Majorana particles).The observation of 0νββdecay would provide crucial insights into the absolute neutrino mass scale and could illuminate the origin of matter-antimatter asymmetry in the universe.展开更多
Magnets exhibiting the Kitaev interaction,a bond-dependent magnetic interaction in honeycomb lattices,are generally regarded as promising candidates for hosting novel phenomena like quantum spin liquid states.However,...Magnets exhibiting the Kitaev interaction,a bond-dependent magnetic interaction in honeycomb lattices,are generally regarded as promising candidates for hosting novel phenomena like quantum spin liquid states.However,realizing such magnets remains a significant challenge.Recently,some studies have suggested honeycomb magnets A_(3)Ni_(2)XO_(6)(A=Li,Na;X=Bi,Sb)with a high spin S=1 could serve as potential candidates for realizing strong Kitaev interactions.In this work,we systematically investigate their magnetic properties,with a particular emphasis on their Kitaev interactions,using first-principles calculations and Monte Carlo simulations.Our results indicate that all A_(3)Ni_(2)XO_(6)compounds are zigzag antiferromagnets,and their magnetic moments almost tend to be out of plane.We find that their dominant magnetic interactions are the nearest-neighbor ferromagnetic and third-nearest-neighbor antiferromagnetic Heisenberg interactions,while their Kitaev interactions are extremely weak.By analyzing their electronic structures and the mechanism of generating their magnetic interactions,we reveal that either artificially tuning spin-orbit coupling or applying strain cannot produce sufficient spin-orbit entangled states to realize the intriguing Kitaev interactions.Our work advances the understanding of the magnetism in A_(3)Ni_(2)XO_(6)compounds and provides insights for further exploration of Kitaev physics in honeycomb magnets.展开更多
Traditional educational paradigms prioritize age-based progression and early specialization as key indicators of academic potential,especially in STEM.This study challenges this norm by analyzing university entrance a...Traditional educational paradigms prioritize age-based progression and early specialization as key indicators of academic potential,especially in STEM.This study challenges this norm by analyzing university entrance ages of 226 Nobel Physics Laureates(1901-2024).Results reveal a right-skewed distribution(Median=18;Mean=18.8;SD=2.4)with substantial variance(14-25 years),including outliers like Lev Landau(14)and Arthur Ashkin(24).Notably,figures such as Guglielmo Marconi achieved breakthroughs without formal university entry,relying on self-directed learning.Using survival analysis and multinomial regression,we find“non-traditional”timelines,accelerated,delayed,or non-formal pathways,correlate with distinct creative advantages.This suggests current“timeliness”metrics poorly predict transformative scientific achievement.We propose an“Optimal Chrono-Diversity”framework advocating flexible entry systems,enhanced adult learner support,and recognition of autodidactic potential to inform educational policy and cultivate innovative STEM talent.展开更多
The Beijing 325 m meteorological tower stands as a pivotal research platform for exploring atmospheric boundary layer physics and atmospheric chemistry.With a legacy spanning 45 years,the tower has played a crucial ro...The Beijing 325 m meteorological tower stands as a pivotal research platform for exploring atmospheric boundary layer physics and atmospheric chemistry.With a legacy spanning 45 years,the tower has played a crucial role in unraveling the complexities of urban air pollution,atmospheric processes,and climate change in Beijing,China.This review paper provides a comprehensive overview of the measurements on the tower over the past two decades.Through long-term comprehensive observations,researchers have elucidated the intricate relationships between anthropogenic emissions,meteorological dynamics,and atmospheric composition,shedding light on the drivers of air pollution and its impacts on public health.The vertical measurements on the tower also enable detailed investigations into boundary layer dynamics,turbulent mixing,and pollutant dispersion,providing invaluable data for validating chemical transport models.Key findings from the tower’s research include the identification of positive feedback mechanisms between aerosols and the boundary layer,the characterization of pollutant sources and transport pathways,the determination of fluxes of gaseous and particulate species,and the assessment of the effectiveness of pollution control measures.Additionally,isotopic measurements have provided new insights into the sources and formation processes of particulate matter and reactive nitrogen species.Finally,the paper outlines future directions for tower-based research,emphasizing the need for long-term comprehensive measurements,the development of innovative tower platforms,and integration of emerging technologies.展开更多
Deep learning combining the physics information is employed to solve the Boussinesq equation with second-order time derivative.High prediction accuracies are achieved by adding a new initial loss term in the physics-i...Deep learning combining the physics information is employed to solve the Boussinesq equation with second-order time derivative.High prediction accuracies are achieved by adding a new initial loss term in the physics-informed neural networks along with the adaptive activation function and loss-balanced coefficients.The numerical simulations are carried out with different initial and boundary conditions,in which the relative L2-norm errors are all around 10^(−4).The prediction accuracies have been improved by two orders of magnitude compared to the former results in certain simulations.The dynamic behavior of solitons and their interaction are studied in the colliding and chasing processes for the Boussinesq equation.More training time is needed for the solver of the Boussinesq equation when the width of the two-soliton solutions becomes narrower with other parameters fixed.展开更多
Active matter encompasses all systems in which each individual constituent independently dissipates energy in its environment.This definition brings together biological systems such as cellular tissues,bacterial colon...Active matter encompasses all systems in which each individual constituent independently dissipates energy in its environment.This definition brings together biological systems such as cellular tissues,bacterial colonies,cytoskeletal filaments driven by molecular motors and animal groups,as well as collections of inert self-propelled particles such as Janus particles,[1]colloidal rollers[2]or vibrated grains.[3]Because of the local persistent drive,these systems are far from thermal equilibrium and cannot be described in terms of thermodynamic potentials.This leads to surprising physics that defies some of the basic intuitions that we have from passive systems,including longrange order in two dimensions[4]and phase-separation in absence of attractive interactions.展开更多
The 2024 MRE HP Special Volume selects papers on new theoretical and experimental developments in the use of static largevolume presses(LVPs)1–3 and dynamic compression4,5 for studies under extreme high-pressure and ...The 2024 MRE HP Special Volume selects papers on new theoretical and experimental developments in the use of static largevolume presses(LVPs)1–3 and dynamic compression4,5 for studies under extreme high-pressure and high-temperature(HPHT)conditions.It also continues the previous year’s6 contemporary focus on superhydrides7–11 with extremely high superconducting temperatures Tc and addresses some controversial issues.12–14 In addition,it explores unconventional pressure-induced chemistry,particularly novel chemical stoichiometry and its impact on geochemistry and cosmochemistry in the deep interiors of Earth and other planets.18–21.展开更多
With the development of educational digitalization,how to effectively apply digital animation technology to traditional classroom teaching has become an urgent problem to be solved.This study explores the application ...With the development of educational digitalization,how to effectively apply digital animation technology to traditional classroom teaching has become an urgent problem to be solved.This study explores the application of Manim in the course of Mathematical Methods for Physics.Taking the visualization of Fourier series,complex numbers,and other content as examples,it improves students’understanding of complex and abstract mathematical physics concepts through dynamic and visual teaching methods.The teaching effect shows that Manim helps to enhance students’learning experience,improve teaching efficiency and effectiveness,and has a positive impact on students’active learning ability.The research in this paper can provide references and inspiration for the educational digitalization of higher education.展开更多
We investigate electron mesoscopic transport in a three-terminal setup with coupled quantum dots and a magnetic flux.By mapping the original transport problem into a non-Hermitian Hamiltonian form,we study the interpl...We investigate electron mesoscopic transport in a three-terminal setup with coupled quantum dots and a magnetic flux.By mapping the original transport problem into a non-Hermitian Hamiltonian form,we study the interplay between the coherent couplings between quantum dots,the magnetic flux,and the dissipation due to the tunnel coupling with the reservoirs.展开更多
In this paper,we design a new error estimator and give a posteriori error analysis for a poroelasticity model.To better overcome“locking phenomenon”on pressure and displacement,we proposed a new error estimators bas...In this paper,we design a new error estimator and give a posteriori error analysis for a poroelasticity model.To better overcome“locking phenomenon”on pressure and displacement,we proposed a new error estimators based on multiphysics discontinuous Galerkin method for the poroelasticity model.And we prove the upper and lower bound of the proposed error estimators,which are numerically demonstrated to be computationally very efficient.Finally,we present numerical examples to verify and validate the efficiency of the proposed error estimators,which show that the adaptive scheme can overcome“locking phenomenon”and greatly reduce the computation cost.展开更多
Milling force is key to the understanding of cutting mechanism and the control of machining process.Traditional milling force models have limited prediction accuracy due to their simplified conditions and incomplete k...Milling force is key to the understanding of cutting mechanism and the control of machining process.Traditional milling force models have limited prediction accuracy due to their simplified conditions and incomplete knowledge contained for model construction.On the other hand,due to the lack of guidance from physics,the data-driven models lack interpretability,making them challenging to generalize to practical applications.To meet these difficulties,a deep network model guided by milling dynamics is proposed in this study to predict the instantaneous milling force and spindle vibration under varying cutting conditions.The model uses a milling dynamics model to generate data sets to pre-train the deep network and then integrates the experimental data for fine-tuning to improve the model’s generalization and accuracy.Additionally,the vibration equation is incorporated into the loss function as the physical constraint,enhancing the model’s interpretability.A milling experiment is conducted to validate the effectiveness of the proposed model,and the results indicate that the physics incorporated could improve the network learning capability and interpretability.The predicted results are in good agreement with the measured values,with an average error as low as 2.6705%.The prediction accuracy is increased by 24.4367%compared to the pure data-driven model.展开更多
The integration of physics-based modelling and data-driven artificial intelligence(AI)has emerged as a transformative paradigm in computational mechanics.This perspective reviews the development and current status of ...The integration of physics-based modelling and data-driven artificial intelligence(AI)has emerged as a transformative paradigm in computational mechanics.This perspective reviews the development and current status of AI-empowered frameworks,including data-driven methods,physics-informed neural networks,and neural operators.While these approaches have demonstrated significant promise,challenges remain in terms of robustness,generalisation,and computational efficiency.We delineate four promising research directions:(1)Modular neural architectures inspired by traditional computational mechanics,(2)physics informed neural operators for resolution-invariant operator learning,(3)intelligent frameworks for multiphysics and multiscale biomechanics problems,and(4)structural optimisation strategies based on physics constraints and reinforcement learning.These directions represent a shift toward foundational frameworks that combine the strengths of physics and data,opening new avenues for the modelling,simulation,and optimisation of complex physical systems.展开更多
Single-pixel imaging(SPI)enables efficient sensing in challenging conditions.However,the requirement for numerous samplings constrains its practicality.We address the challenge of high-quality SPI reconstruction at ul...Single-pixel imaging(SPI)enables efficient sensing in challenging conditions.However,the requirement for numerous samplings constrains its practicality.We address the challenge of high-quality SPI reconstruction at ultra-low sampling rates.We develop an alternative optimization with physics and a data-driven diffusion network(APD-Net).It features alternative optimization driven by the learned task-agnostic natural image prior and the task-specific physics prior.During the training stage,APD-Net harnesses the power of diffusion models to capture data-driven statistics of natural signals.In the inference stage,the physics prior is introduced as corrective guidance to ensure consistency between the physics imaging model and the natural image probability distribution.Through alternative optimization,APD-Net reconstructs data-efficient,high-fidelity images that are statistically and physically compliant.To accelerate reconstruction,initializing images with the inverse SPI physical model reduces the need for reconstruction inference from 100 to 30 steps.Through both numerical simulations and real prototype experiments,APD-Net achieves high-quality,full-color reconstructions of complex natural images at a low sampling rate of 1%.In addition,APD-Net’s tuning-free nature ensures robustness across various imaging setups and sampling rates.Our research offers a broadly applicable approach for various applications,including but not limited to medical imaging and industrial inspection.展开更多
Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resoluti...Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resolution limited-area models such as cloud-resolving models(CRMs)and large-eddy simulation(LES)models.Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years,this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations:multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions;discrete vs“continuous”representation of hydrometeor types;turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation;theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology;and approaches for developing bulk microphysics parameterizations.Also presented are the spectral bin scheme and particle-based scheme(especially,super-droplet method)for representing explicit microphysics.Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations.Particle-resolved direct numerical simulation(DNS)models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds.Outstanding challenges and future research directions are explored as well.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos.12090064,12205063,12375088,and W2441004)the Fundamental Research Funds for the Central Universitiesin part by the National Key Research and Development Program of China (Grant No.2020YFC2201501)。
文摘Among the charged leptons,theτelectric dipole moment dτis the least constrained.We show that the Im[d_(τ)]imposes strong constraints on new physics that have yet to be discussed.Motivated in particular by the Super Tau-Charm Facility(STCF),which will provide a uniquely clean environment for precisionτ-physics,we study the momentum-transfer dependence of d_(τ)(q^(2))and compare the projected sensitivities of STCF and BelleⅡ.Our analysis shows that an axion-like coupling of the τ lepton can induce sizable real and imaginary components of the EDM.The predicted EDM values may approach the present experimental sensitivities,making them accessible to future measurements at Belle II and the STCF.
文摘Ultrafast optical spectroscopy was successfully introduced decades ago.Its deep relationship with condensed matter physics profoundly enriched the scientific frontier of light–matter interactions.Previously,materials such as metals,insulators,semiconductors,and superconductors were investigated,followed by magnetic materials,strongly correlated materials,complex oxides,nano-materials,topological materials,and metamaterials.
基金supported by the National Natural Science Foundation of China (Grant No.12075326)the Guangdong Basic and Applied Basic Research Foundation (Grant No.2025A1515010669)+2 种基金the Natural Science Foundation of Guangzhou (Grant No.2024A04J6243)the Fundamental Research Funds for the Central Universities in Sun Yat-sen University (No.23xkjc017)the Innovation Training Program for bachelor students in Sun Yat-sen University。
文摘In response to the capabilities presented by the High-Intensity Heavy Ion Accelerator Facility(HIAF) and the Accelerator-Driven Subcritical System(Ci ADS), as well as the proposed Chinese Advanced Nuclear Physics Research Facility(CNUF), we are assembling a consortium of experts in relevant disciplines, both domestically and internationally,to delineate high-precision physics experiments that leverage the state-of-the-art research environment afforded by CNUF.Our focus encompasses six primary domains of inquiry: hadron physics—including endeavors such as the super eta factory and investigations into light hadron structures;muon physics;neutrino physics;neutron physics;the testing of fundamental symmetries;and the exploration of quantum effects within nuclear physics, along with the utilization of vortex accelerators.We aim to foster a well-rounded portfolio of large, medium, and small-scale projects, thus unlocking new scientific avenues and optimizing the potential of the Huizhou large scientific facility. The aspiration for international leadership in scientific research will be a guiding principle in our strategic planning. This initiative will serve as a foundational reference for the Institute of Modern Physics in its strategic planning and goal-setting, ensuring alignment with its developmental objectives while striving to secure a competitive edge in technological advancement. Our ambition is to engage in substantive research within these realms of high-precision physics, to pursue groundbreaking discoveries, and to stimulate progress in China's nuclear physics landscape, positioning Huizhou as a preeminent global hub for advanced nuclear physics research.
基金supported by the National Key R&D Program of China[grant number 2023YFC3008004]。
文摘This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.
基金National Natural Science Foundation of China(12125509,11961141003,12275361,U2267205,12175152,12175121)National Key Research and Development Project(2022YFA1602301)Continuous-support Basic Scientific Research Project。
文摘To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produced by the tandem-accelerator in the China Institute of Atomic Energy was utilized.The proton beam was first transmitted through a 60.5μm aluminum foil and then impinged on a natural LiF target to produce neutron beam via^(7)Li(p,n)7Be reaction.The quasi-Gaussian energy distribution of protons in the LiF target resulted in neutron energy spectra that agreed with a Maxwellian energy distribution at kT=(22±2)keV,which was achieved by integrating neutrons detected within an emission angle of 65.0°±2.6°using a ^(6)Li glass detector positioned at 65°relative to the proton beam direction.The narrow angular spread of the Maxwelliandistributed neutron beam enables direct measurement of neutron capture cross-sections for most s-process nuclides,overcoming previous experimental limitations associated with broad angular distributions.
基金supported by the National Key R&D Program of China(Grant Nos.2024YFA1408400 and 2021YFA1400401)the National Natural Science Foundation of China(Grant Nos.U22A6005 and 52271238)+2 种基金the China Postdoctoral Science Foundation(Grant No.2025M770186)the Center for Materials Genome,and the Synergetic Extreme Condition User Facility(SECUF)supported by the AI-driven experiments,simulations and model training on the robotic AI-Scientist platform from Chinese Academy of Sciences and the Research Funds for the Central Universities(Grant No.N25ZLE007).
文摘Low-dimensional physics provides profound insights into strongly correlated interactions,leading to enhancedquantum effects and the emergence of exotic quantum states.The Ln_(3)ScBi_(5)family stands out as a chemicallyversatile kagome platform with mixed low-dimensional structural framework and tunable physical properties.Ourresearch initiates with a comprehensive evaluation of the currently known Ln_(3)ScBi_(5)(Ln=La-Nd,Sm)materials,providing a robust methodology for assessing their stability frontiers within this system.Focusing on Pr_(3)ScBi_(5),we investigate the influence of the zigzag chains of quasi-one-dimensional(Q1D)motifs and the distorted kagomelayers of quasi-two-dimensional(Q2D)networks in the mixed-dimensional structure on the intricate magneticground states and unique spin fluctuations.Our study reveals that the noncollinear antiferromagnetic(AFM)moments of Pr^(3+)ions are confined within the Q2D kagome planes,displaying minimal in-plane anisotropy.Incontrast,a strong AFM coupling is observed within the Q1D zigzag chains,significantly constraining spin motion.Notably,magnetic frustration is partially a consequence of coupling to conduction electrons via Ruderman-Kittel-Kasuya-Yosida interaction,highlighting a promising framework for future investigations into mixed-dimensional frustration in Ln_(3)ScBi_(5) systems.
文摘The challenge in searching for fundamental symmetry violation.Neutrinoless double-beta(0νββ)decay represents one of the most profound tests of fundamental symmetries in nature.This hypothetical nuclear process,in which two neutrons simultaneously decay into two protons with the emission of two electrons but no neutrinos,would demonstrate that lepton number is not conserved and confirm that neutrinos are their own antiparticles(Majorana particles).The observation of 0νββdecay would provide crucial insights into the absolute neutrino mass scale and could illuminate the origin of matter-antimatter asymmetry in the universe.
基金supported by the National Key R&D Program of China(Grant Nos.2024-YFA1408303 and 2022YFA1403301)the National Natural Sciences Foundation of China(Grant Nos.12474247 and 92165204)+1 种基金support from Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices(Grant No.2022B1212010008)Research Center for Magnetoelectric Physicsof Guangdong Province(Grant No.2024B0303390001).
文摘Magnets exhibiting the Kitaev interaction,a bond-dependent magnetic interaction in honeycomb lattices,are generally regarded as promising candidates for hosting novel phenomena like quantum spin liquid states.However,realizing such magnets remains a significant challenge.Recently,some studies have suggested honeycomb magnets A_(3)Ni_(2)XO_(6)(A=Li,Na;X=Bi,Sb)with a high spin S=1 could serve as potential candidates for realizing strong Kitaev interactions.In this work,we systematically investigate their magnetic properties,with a particular emphasis on their Kitaev interactions,using first-principles calculations and Monte Carlo simulations.Our results indicate that all A_(3)Ni_(2)XO_(6)compounds are zigzag antiferromagnets,and their magnetic moments almost tend to be out of plane.We find that their dominant magnetic interactions are the nearest-neighbor ferromagnetic and third-nearest-neighbor antiferromagnetic Heisenberg interactions,while their Kitaev interactions are extremely weak.By analyzing their electronic structures and the mechanism of generating their magnetic interactions,we reveal that either artificially tuning spin-orbit coupling or applying strain cannot produce sufficient spin-orbit entangled states to realize the intriguing Kitaev interactions.Our work advances the understanding of the magnetism in A_(3)Ni_(2)XO_(6)compounds and provides insights for further exploration of Kitaev physics in honeycomb magnets.
基金Inner Mongolia Natural Science Foundation of China(Project No.:2023QN01015).
文摘Traditional educational paradigms prioritize age-based progression and early specialization as key indicators of academic potential,especially in STEM.This study challenges this norm by analyzing university entrance ages of 226 Nobel Physics Laureates(1901-2024).Results reveal a right-skewed distribution(Median=18;Mean=18.8;SD=2.4)with substantial variance(14-25 years),including outliers like Lev Landau(14)and Arthur Ashkin(24).Notably,figures such as Guglielmo Marconi achieved breakthroughs without formal university entry,relying on self-directed learning.Using survival analysis and multinomial regression,we find“non-traditional”timelines,accelerated,delayed,or non-formal pathways,correlate with distinct creative advantages.This suggests current“timeliness”metrics poorly predict transformative scientific achievement.We propose an“Optimal Chrono-Diversity”framework advocating flexible entry systems,enhanced adult learner support,and recognition of autodidactic potential to inform educational policy and cultivate innovative STEM talent.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0760200)the National Natural Science Foundation of China(Grant Nos.42330605 and 42377101).
文摘The Beijing 325 m meteorological tower stands as a pivotal research platform for exploring atmospheric boundary layer physics and atmospheric chemistry.With a legacy spanning 45 years,the tower has played a crucial role in unraveling the complexities of urban air pollution,atmospheric processes,and climate change in Beijing,China.This review paper provides a comprehensive overview of the measurements on the tower over the past two decades.Through long-term comprehensive observations,researchers have elucidated the intricate relationships between anthropogenic emissions,meteorological dynamics,and atmospheric composition,shedding light on the drivers of air pollution and its impacts on public health.The vertical measurements on the tower also enable detailed investigations into boundary layer dynamics,turbulent mixing,and pollutant dispersion,providing invaluable data for validating chemical transport models.Key findings from the tower’s research include the identification of positive feedback mechanisms between aerosols and the boundary layer,the characterization of pollutant sources and transport pathways,the determination of fluxes of gaseous and particulate species,and the assessment of the effectiveness of pollution control measures.Additionally,isotopic measurements have provided new insights into the sources and formation processes of particulate matter and reactive nitrogen species.Finally,the paper outlines future directions for tower-based research,emphasizing the need for long-term comprehensive measurements,the development of innovative tower platforms,and integration of emerging technologies.
基金supported by the National Natural Science Foundation of China under Grant No.12475204.
文摘Deep learning combining the physics information is employed to solve the Boussinesq equation with second-order time derivative.High prediction accuracies are achieved by adding a new initial loss term in the physics-informed neural networks along with the adaptive activation function and loss-balanced coefficients.The numerical simulations are carried out with different initial and boundary conditions,in which the relative L2-norm errors are all around 10^(−4).The prediction accuracies have been improved by two orders of magnitude compared to the former results in certain simulations.The dynamic behavior of solitons and their interaction are studied in the colliding and chasing processes for the Boussinesq equation.More training time is needed for the solver of the Boussinesq equation when the width of the two-soliton solutions becomes narrower with other parameters fixed.
文摘Active matter encompasses all systems in which each individual constituent independently dissipates energy in its environment.This definition brings together biological systems such as cellular tissues,bacterial colonies,cytoskeletal filaments driven by molecular motors and animal groups,as well as collections of inert self-propelled particles such as Janus particles,[1]colloidal rollers[2]or vibrated grains.[3]Because of the local persistent drive,these systems are far from thermal equilibrium and cannot be described in terms of thermodynamic potentials.This leads to surprising physics that defies some of the basic intuitions that we have from passive systems,including longrange order in two dimensions[4]and phase-separation in absence of attractive interactions.
基金financial support from the Shanghai Key Laboratory of MFree,China(Grant No.22dz2260800)the Shanghai Science and Technology Committee,China(Grant No.22JC1410300).
文摘The 2024 MRE HP Special Volume selects papers on new theoretical and experimental developments in the use of static largevolume presses(LVPs)1–3 and dynamic compression4,5 for studies under extreme high-pressure and high-temperature(HPHT)conditions.It also continues the previous year’s6 contemporary focus on superhydrides7–11 with extremely high superconducting temperatures Tc and addresses some controversial issues.12–14 In addition,it explores unconventional pressure-induced chemistry,particularly novel chemical stoichiometry and its impact on geochemistry and cosmochemistry in the deep interiors of Earth and other planets.18–21.
基金supported by the Teaching Reform Research Project of Shaanxi University of Science&Technology(23Y083)the Project of National University Association for Mathematical Methods in Physics(JZW-23-SL-02)+3 种基金the Graduate Course Construction Project of Shaanxi University of Science&Technology(KC2024Y03)the 2024 National Higher Education University Physics Reform Research Project(2024PR064)the Teaching Reform Research Project of the International Office of Shaanxi University of Science&Technology(YB202410)Graduate Education and Teaching Reform Research Project of Shaanxi University of Science&Technology(JG2025Y18).
文摘With the development of educational digitalization,how to effectively apply digital animation technology to traditional classroom teaching has become an urgent problem to be solved.This study explores the application of Manim in the course of Mathematical Methods for Physics.Taking the visualization of Fourier series,complex numbers,and other content as examples,it improves students’understanding of complex and abstract mathematical physics concepts through dynamic and visual teaching methods.The teaching effect shows that Manim helps to enhance students’learning experience,improve teaching efficiency and effectiveness,and has a positive impact on students’active learning ability.The research in this paper can provide references and inspiration for the educational digitalization of higher education.
基金supported by the National Key R&D Program of China(Grant No.2022YFA1404400)the National Natural Science Foundation of China(Grant No.12125504 and 12305050)+2 种基金Zhejiang Provincial Natural Science Foundation of China(Grant No.LZ25A050001)the Hundred Talents Program of the Chinese Academy of Sciencesthe Natural Science Foundation of Jiangsu Higher Education Institutions of China(Grant No.23KJB140017)。
文摘We investigate electron mesoscopic transport in a three-terminal setup with coupled quantum dots and a magnetic flux.By mapping the original transport problem into a non-Hermitian Hamiltonian form,we study the interplay between the coherent couplings between quantum dots,the magnetic flux,and the dissipation due to the tunnel coupling with the reservoirs.
基金supported by the National Natural Science Foundation of China(Grant Nos.12371393 and 11971150)Natural Science Foundation of Henan(Grant No.242300421047).
文摘In this paper,we design a new error estimator and give a posteriori error analysis for a poroelasticity model.To better overcome“locking phenomenon”on pressure and displacement,we proposed a new error estimators based on multiphysics discontinuous Galerkin method for the poroelasticity model.And we prove the upper and lower bound of the proposed error estimators,which are numerically demonstrated to be computationally very efficient.Finally,we present numerical examples to verify and validate the efficiency of the proposed error estimators,which show that the adaptive scheme can overcome“locking phenomenon”and greatly reduce the computation cost.
基金supported in part by the National Natural Science Foundation of China(52175528)in part by the National Key Research and Development Program of China,the Chinese Ministry of Science and Technology(2018YFB1703200).
文摘Milling force is key to the understanding of cutting mechanism and the control of machining process.Traditional milling force models have limited prediction accuracy due to their simplified conditions and incomplete knowledge contained for model construction.On the other hand,due to the lack of guidance from physics,the data-driven models lack interpretability,making them challenging to generalize to practical applications.To meet these difficulties,a deep network model guided by milling dynamics is proposed in this study to predict the instantaneous milling force and spindle vibration under varying cutting conditions.The model uses a milling dynamics model to generate data sets to pre-train the deep network and then integrates the experimental data for fine-tuning to improve the model’s generalization and accuracy.Additionally,the vibration equation is incorporated into the loss function as the physical constraint,enhancing the model’s interpretability.A milling experiment is conducted to validate the effectiveness of the proposed model,and the results indicate that the physics incorporated could improve the network learning capability and interpretability.The predicted results are in good agreement with the measured values,with an average error as low as 2.6705%.The prediction accuracy is increased by 24.4367%compared to the pure data-driven model.
基金supported by the Australian Research Council(Grant No.IC190100020)the Australian Research Council Indus〓〓try Fellowship(Grant No.IE230100435)the National Natural Science Foundation of China(Grant Nos.12032014 and T2488101)。
文摘The integration of physics-based modelling and data-driven artificial intelligence(AI)has emerged as a transformative paradigm in computational mechanics.This perspective reviews the development and current status of AI-empowered frameworks,including data-driven methods,physics-informed neural networks,and neural operators.While these approaches have demonstrated significant promise,challenges remain in terms of robustness,generalisation,and computational efficiency.We delineate four promising research directions:(1)Modular neural architectures inspired by traditional computational mechanics,(2)physics informed neural operators for resolution-invariant operator learning,(3)intelligent frameworks for multiphysics and multiscale biomechanics problems,and(4)structural optimisation strategies based on physics constraints and reinforcement learning.These directions represent a shift toward foundational frameworks that combine the strengths of physics and data,opening new avenues for the modelling,simulation,and optimisation of complex physical systems.
基金upported by the National Natural Science Foundation of China(Grant No.62305184)the Major Key Project of Pengcheng Laboratory(Grant No.PCL2024A1)+1 种基金the Basic and Applied Basic Research Foundation of Guangdong Province(Grant No.2023A1515012932)the Science,Technology and Innovation Commission of Shenzhen Municipality(Grant No.WDZC20220818100259004).
文摘Single-pixel imaging(SPI)enables efficient sensing in challenging conditions.However,the requirement for numerous samplings constrains its practicality.We address the challenge of high-quality SPI reconstruction at ultra-low sampling rates.We develop an alternative optimization with physics and a data-driven diffusion network(APD-Net).It features alternative optimization driven by the learned task-agnostic natural image prior and the task-specific physics prior.During the training stage,APD-Net harnesses the power of diffusion models to capture data-driven statistics of natural signals.In the inference stage,the physics prior is introduced as corrective guidance to ensure consistency between the physics imaging model and the natural image probability distribution.Through alternative optimization,APD-Net reconstructs data-efficient,high-fidelity images that are statistically and physically compliant.To accelerate reconstruction,initializing images with the inverse SPI physical model reduces the need for reconstruction inference from 100 to 30 steps.Through both numerical simulations and real prototype experiments,APD-Net achieves high-quality,full-color reconstructions of complex natural images at a low sampling rate of 1%.In addition,APD-Net’s tuning-free nature ensures robustness across various imaging setups and sampling rates.Our research offers a broadly applicable approach for various applications,including but not limited to medical imaging and industrial inspection.
基金supported by the US Department of Energy(DOE)’s Office of Science Atmospheric Systems Research(ASR)Programthe Office of Energy Efficiency and Renewable Energy(EERE)Solar Energy Technologies Office(SETO)award(33504)+3 种基金the Brookhaven National Laboratory(BNL)’s Laboratory Directed Research&Development Program(LDRD)(22-065)The Brookhaven National Laboratory is operated by the Brookhaven Science Associates,LLC(BSA),for the US Department of Energy under Contract No.DESC0012704supported by JSPS KAKENHI Grant No.26286089MEXT KAKENHI Grant No.18H04448。
文摘Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resolution limited-area models such as cloud-resolving models(CRMs)and large-eddy simulation(LES)models.Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years,this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations:multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions;discrete vs“continuous”representation of hydrometeor types;turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation;theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology;and approaches for developing bulk microphysics parameterizations.Also presented are the spectral bin scheme and particle-based scheme(especially,super-droplet method)for representing explicit microphysics.Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations.Particle-resolved direct numerical simulation(DNS)models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds.Outstanding challenges and future research directions are explored as well.
