The increasing complexity of intelligent sensing environments,driven by the growth of Internet of Things technologies,has created a strong demand for neuromorphic systems capable of real-time,low-power multisensory pe...The increasing complexity of intelligent sensing environments,driven by the growth of Internet of Things technologies,has created a strong demand for neuromorphic systems capable of real-time,low-power multisensory perception.Traditional sensory architectures,constrained by single-modal processing and centralized computing,struggle to meet the requirements of diverse and dynamic input conditions.Multisensory neuromorphic devices offer a promising solution by mimicking the distributed,event-driven processing of biological systems.Recent efforts have explored synaptic devices and material systems that respond to various input modalities,including visual,tactile,thermal,and chemical stimuli.However,challenges remain in signal conversion,encoding compatibility,and the fusion of heterogeneous inputs without loss of unisensory information.This review provides a comprehensive overview of the physical mechanisms,device behaviors,and integration strategies that underpin signal processing in neuromorphic hardware.We highlight synaptic mechanisms conducive to cross-modal interaction,analyze representative signal fusion approaches at the device level,and discuss future directions for constructing efficient,scalable,and biologically inspired multisensory neuromorphic systems.展开更多
Delineating sweet spots is critical for the exploration and production of oil and gas in deep and tight sand reservoirs.The lack of advanced and reliable methods makes this a challenge for geologists and geophysicists...Delineating sweet spots is critical for the exploration and production of oil and gas in deep and tight sand reservoirs.The lack of advanced and reliable methods makes this a challenge for geologists and geophysicists.This study introduces,for the first time,an integrated workflow that combines pre-stack seismic inversion with rock physics modeling to predict reservoir porosity and shale volume(V-shale)for sweet spot identification in tight sand reservoirs.A new elastic parameter,the density calculation index(DCI),is introduced which links acoustic and shear impedance for seismic density inversion,thereby addressing the long-standing problem of poor density inversion accuracy.A novel combined Sun–Walsh rock physics model,developed as part of this study,significantly improves V-shale evaluation from seismic data.The proposed three-step seismic inversion approach includes:(1)deriving acoustic and shear impedance from angle-stack seismic data using model-based inversion;(2)calculating density using shear impedance constrained by DCI,followed by porosity estimation from the density–porosity relation;and(3)evaluating V-shale using theα-parameter derived from the Sun–Walsh model and pre-stack inversion results.This integrated workflow provides an effective tool for building accurate 3D reservoir models,and is especially applicable to deep,low-porosity,tight sand reservoirs worldwide.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
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
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
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
Accurate estimation of mineralogy from geophysical well logs is crucial for characterizing geological formations,particularly in hydrocarbon exploration,CO_(2) sequestration,and geothermal energy development.Current t...Accurate estimation of mineralogy from geophysical well logs is crucial for characterizing geological formations,particularly in hydrocarbon exploration,CO_(2) sequestration,and geothermal energy development.Current techniques,such as multimineral petrophysical analysis,offer details into mineralogical distribution.However,it is inherently time-intensive and demands substantial geological expertise for accurate model evaluation.Furthermore,traditional machine learning techniques often struggle to predict mineralogy accurately and sometimes produce estimations that violate fundamental physical principles.To address this,we present a new approach using Physics-Integrated Neural Networks(PINNs),that combines data-driven learning with domain-specific physical constraints,embedding petrophysical relationships directly into the neural network architecture.This approach enforces that predictions adhere to physical laws.The methodology is applied to the Broom Creek Deep Saline aquifer,a CO_(2) sequestration site in the Williston Basin,to predict the volumes of key mineral constituents—quartz,dolomite,feldspar,anhydrite,illite—along with porosity.Compared to traditional artificial neural networks (ANN),the PINN approach demonstrates higher accuracy and better generalizability,significantly enhancing predictive performance on unseen well datasets.The average mean error across the three blind wells is 0.123 for ANN and 0.042 for PINN,highlighting the superior accuracy of the PINN approach.This method reduces uncertainties in reservoir characterization by improving the reliability of mineralogy and porosity predictions,providing a more robust tool for decision-making in various subsurface geoscience applications.展开更多
ABOUT THIS JOURNAL Launched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoret ical research on interdisciplinary areas,with chemistry and physics gr...ABOUT THIS JOURNAL Launched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoret ical research on interdisciplinary areas,with chemistry and physics groundwork of interest to researchers,faculty and students domestic and abroad in the fields of chemistry,physics,material and biologi cal sciences and their interdisciplinary areas.As one of the 24 peer reviewed journals under the Chinese Physical Society(CPS),CJCP has been covered in ISI products(SCIE)as well as other major indexes CJCP is currently a bimonthly journal,and it publishes in English with Chinese abstract as of 2006.展开更多
ABOUT THIS JOURNAL Launched in 1988,the Chinese Journal of Chemical Physics (CJCP)is devoted to reporting new and original experimental and theoretical research on interdisciplinary areas,with chemistry and physics gr...ABOUT THIS JOURNAL Launched in 1988,the Chinese Journal of Chemical Physics (CJCP)is devoted to reporting new and original experimental and theoretical research on interdisciplinary areas,with chemistry and physics groundwork of interest to researchers,faculty and students domestic and abroad in the fields of chemistry,physics,material and biological sciences and their interdisciplinary areas.As one of the 24 peer-reviewed journals under the Chinese Physical Society (CPS),CJCP has been covered in ISI products (SCIE) as well as other major indexes.CJCP is currently a bimonthly journal,and it publishes in English with Chinese abstract as of 2006.展开更多
ABOUT THIS JOURNALLaunched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoretical research on interdisciplinary areas,with chemistry and physicsgroun...ABOUT THIS JOURNALLaunched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoretical research on interdisciplinary areas,with chemistry and physicsgroundwork of interest to researchers,faculty and students domesticand abroad in the fields of chemistry,physics,material and biological sciences and their interdisciplinary areas.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
We study the trimer state in a three-body system,where two of the atoms are subject to Rashba-type spin-orbit coupling and spin-dependent loss while interacting spin-selectively with the third atom.The short-time cond...We study the trimer state in a three-body system,where two of the atoms are subject to Rashba-type spin-orbit coupling and spin-dependent loss while interacting spin-selectively with the third atom.The short-time conditional dynamics of the three-body system is effectively governed by a non-Hermitian Hamiltonian with an imaginary Zeeman field.Remarkably,the interplay of non-Hermitian single particle dispersion and the spin-selective interaction results in a Borromean state and an enlarged trimer phase.The stability of trimer state can be reflected by the imaginary part of trimer energy and the momentum distribution of trimer wave function.We also show the phase diagram of the three-body system under both real and imaginary Zeeman fields.Our results illustrate the interesting consequence of non-Hermitian spectral symmetry on the few-body level,which may be readily observable in current cold-atom experiments.展开更多
ABOUT THIS JOURNAL.Launched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoret-ical research on interdisciplinary areas,with chemistry and physics gr...ABOUT THIS JOURNAL.Launched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoret-ical research on interdisciplinary areas,with chemistry and physics groundwork of interest to r resear chers,faculty and students domestic and abroad in the fields of chemistry,physics,material and biological sciences and their interdisciplinary areas.展开更多
This article presents a further development of the hypotheses concerning the possibility of predicting (“tectonic”) earthquakes [1]. Those hypotheses are based on the conversion of all types of released energy into ...This article presents a further development of the hypotheses concerning the possibility of predicting (“tectonic”) earthquakes [1]. Those hypotheses are based on the conversion of all types of released energy into heat and active chemical substances. One of the important sources of this phenomenon is the release of the latent energy trapped and stored during the Earth’s accretion. The latent energy of primordial hydrogen and helium escaping from the Earth’s core and lower mantle causes degassing processes [2] [3]. This latent energy converts into totally different types of chemical, electromagnetic and thermal energies of active compounds that are responsible for the major endogenic terrestrial processes. The dominating theories in seismology and volcanology are that an earthquake results from a sudden slip of a tectonic fault and that only magma and the gases contained in magma supply the volcanic energy resulting in the conclusions that earthquakes and eruptions are unpredictable. Volcanic eruption is considered herein to be a special case of the earthquake-process in which earthquake hypocenters rise to the Earth’s surface. A possible solution is proposed ([1] and herein) based on the analyses of the physicochemical processes as participants in earthquake and eruption preparations (foreshocks - major shock - aftershocks - volcanic eruptions) and on the characteristic rates of reflection of these processes on the Earth’s surface. Influences of Sun-Moon-tides and volcanic (“harmonic”) tremors are analyzed from physical-chemical point of view. The case of the 1980 eruption of Mount St. Helens and the proposed monitoring of the recommended additional data provides a way of selecting a complex of reliable earthquake and volcanic eruption precursors.展开更多
The Laboratory of Rare Earth Chemistry and Physics,Changchun Institute of Ap-plied Chemistry,Academia Sinica,has been opened to foreign scientists since October,1987.The first plenary session of the Academic Committee...The Laboratory of Rare Earth Chemistry and Physics,Changchun Institute of Ap-plied Chemistry,Academia Sinica,has been opened to foreign scientists since October,1987.The first plenary session of the Academic Committee was held in March,1988,andthe first batch of research projects granted by the Scientific Funds of the Laboratory wereapproved at this meeting.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
Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal disease.However,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging process...Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal disease.However,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging process.An inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping phenomenon.Deep learning methods have been applied in musculoskeletal imaging,but need a large amount of data for training.Inspired by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and density.In the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue models.The results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best performance.The specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.展开更多
Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL...Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL models,however,do not necessarily obey the fundamental governing laws of PAM physical systems,nor do they generalize well to scenarios on which they have not been trained.In this work,a physics-embedded degeneration learning(PEDL)approach is proposed to enhance the image quality of PAM with a self-attention enhanced U-Net network,which obtains greater physical consistency,improves data efficiency,and higher adaptability.The proposed method is demonstrated on both synthetic and real datasets,including animal experiments in vivo(blood vessels of mouse's ear and brain).And the results show that compared with previous DL methods,the PEDL algorithm exhibits good performance in recovering PAM images qualitatively and quantitatively.It overcomes the challenges related to training data,accuracy,and robustness which a typical data-driven approach encounters,whose exemplary application envisions to provide a new perspective for existing DL tools of enhanced PAM.展开更多
基金the financial support from the National Key Research and Development Program of China(Grant No.2022YFB4400100)the NSFC under Grant Nos.92477102 and 62122084the open research fund of Songshan Lake Materials Laboratory 2023SLABFK09。
文摘The increasing complexity of intelligent sensing environments,driven by the growth of Internet of Things technologies,has created a strong demand for neuromorphic systems capable of real-time,low-power multisensory perception.Traditional sensory architectures,constrained by single-modal processing and centralized computing,struggle to meet the requirements of diverse and dynamic input conditions.Multisensory neuromorphic devices offer a promising solution by mimicking the distributed,event-driven processing of biological systems.Recent efforts have explored synaptic devices and material systems that respond to various input modalities,including visual,tactile,thermal,and chemical stimuli.However,challenges remain in signal conversion,encoding compatibility,and the fusion of heterogeneous inputs without loss of unisensory information.This review provides a comprehensive overview of the physical mechanisms,device behaviors,and integration strategies that underpin signal processing in neuromorphic hardware.We highlight synaptic mechanisms conducive to cross-modal interaction,analyze representative signal fusion approaches at the device level,and discuss future directions for constructing efficient,scalable,and biologically inspired multisensory neuromorphic systems.
文摘Delineating sweet spots is critical for the exploration and production of oil and gas in deep and tight sand reservoirs.The lack of advanced and reliable methods makes this a challenge for geologists and geophysicists.This study introduces,for the first time,an integrated workflow that combines pre-stack seismic inversion with rock physics modeling to predict reservoir porosity and shale volume(V-shale)for sweet spot identification in tight sand reservoirs.A new elastic parameter,the density calculation index(DCI),is introduced which links acoustic and shear impedance for seismic density inversion,thereby addressing the long-standing problem of poor density inversion accuracy.A novel combined Sun–Walsh rock physics model,developed as part of this study,significantly improves V-shale evaluation from seismic data.The proposed three-step seismic inversion approach includes:(1)deriving acoustic and shear impedance from angle-stack seismic data using model-based inversion;(2)calculating density using shear impedance constrained by DCI,followed by porosity estimation from the density–porosity relation;and(3)evaluating V-shale using theα-parameter derived from the Sun–Walsh model and pre-stack inversion results.This integrated workflow provides an effective tool for building accurate 3D reservoir models,and is especially applicable to deep,low-porosity,tight sand reservoirs worldwide.
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 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 (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the North Dakota Industrial Commission (NDIC) for their financial supportprovided by the University of North Dakota Computational Research Center。
文摘Accurate estimation of mineralogy from geophysical well logs is crucial for characterizing geological formations,particularly in hydrocarbon exploration,CO_(2) sequestration,and geothermal energy development.Current techniques,such as multimineral petrophysical analysis,offer details into mineralogical distribution.However,it is inherently time-intensive and demands substantial geological expertise for accurate model evaluation.Furthermore,traditional machine learning techniques often struggle to predict mineralogy accurately and sometimes produce estimations that violate fundamental physical principles.To address this,we present a new approach using Physics-Integrated Neural Networks(PINNs),that combines data-driven learning with domain-specific physical constraints,embedding petrophysical relationships directly into the neural network architecture.This approach enforces that predictions adhere to physical laws.The methodology is applied to the Broom Creek Deep Saline aquifer,a CO_(2) sequestration site in the Williston Basin,to predict the volumes of key mineral constituents—quartz,dolomite,feldspar,anhydrite,illite—along with porosity.Compared to traditional artificial neural networks (ANN),the PINN approach demonstrates higher accuracy and better generalizability,significantly enhancing predictive performance on unseen well datasets.The average mean error across the three blind wells is 0.123 for ANN and 0.042 for PINN,highlighting the superior accuracy of the PINN approach.This method reduces uncertainties in reservoir characterization by improving the reliability of mineralogy and porosity predictions,providing a more robust tool for decision-making in various subsurface geoscience applications.
文摘ABOUT THIS JOURNAL Launched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoret ical research on interdisciplinary areas,with chemistry and physics groundwork of interest to researchers,faculty and students domestic and abroad in the fields of chemistry,physics,material and biologi cal sciences and their interdisciplinary areas.As one of the 24 peer reviewed journals under the Chinese Physical Society(CPS),CJCP has been covered in ISI products(SCIE)as well as other major indexes CJCP is currently a bimonthly journal,and it publishes in English with Chinese abstract as of 2006.
文摘ABOUT THIS JOURNAL Launched in 1988,the Chinese Journal of Chemical Physics (CJCP)is devoted to reporting new and original experimental and theoretical research on interdisciplinary areas,with chemistry and physics groundwork of interest to researchers,faculty and students domestic and abroad in the fields of chemistry,physics,material and biological sciences and their interdisciplinary areas.As one of the 24 peer-reviewed journals under the Chinese Physical Society (CPS),CJCP has been covered in ISI products (SCIE) as well as other major indexes.CJCP is currently a bimonthly journal,and it publishes in English with Chinese abstract as of 2006.
文摘ABOUT THIS JOURNALLaunched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoretical research on interdisciplinary areas,with chemistry and physicsgroundwork of interest to researchers,faculty and students domesticand abroad in the fields of chemistry,physics,material and biological sciences and their interdisciplinary areas.
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 Natural Science Foundation of China(Grant No.11974331)。
文摘We study the trimer state in a three-body system,where two of the atoms are subject to Rashba-type spin-orbit coupling and spin-dependent loss while interacting spin-selectively with the third atom.The short-time conditional dynamics of the three-body system is effectively governed by a non-Hermitian Hamiltonian with an imaginary Zeeman field.Remarkably,the interplay of non-Hermitian single particle dispersion and the spin-selective interaction results in a Borromean state and an enlarged trimer phase.The stability of trimer state can be reflected by the imaginary part of trimer energy and the momentum distribution of trimer wave function.We also show the phase diagram of the three-body system under both real and imaginary Zeeman fields.Our results illustrate the interesting consequence of non-Hermitian spectral symmetry on the few-body level,which may be readily observable in current cold-atom experiments.
文摘ABOUT THIS JOURNAL.Launched in 1988,the Chinese Journal of Chemical Physics(CJCP)is devoted to reporting new and original experimental and theoret-ical research on interdisciplinary areas,with chemistry and physics groundwork of interest to r resear chers,faculty and students domestic and abroad in the fields of chemistry,physics,material and biological sciences and their interdisciplinary areas.
文摘This article presents a further development of the hypotheses concerning the possibility of predicting (“tectonic”) earthquakes [1]. Those hypotheses are based on the conversion of all types of released energy into heat and active chemical substances. One of the important sources of this phenomenon is the release of the latent energy trapped and stored during the Earth’s accretion. The latent energy of primordial hydrogen and helium escaping from the Earth’s core and lower mantle causes degassing processes [2] [3]. This latent energy converts into totally different types of chemical, electromagnetic and thermal energies of active compounds that are responsible for the major endogenic terrestrial processes. The dominating theories in seismology and volcanology are that an earthquake results from a sudden slip of a tectonic fault and that only magma and the gases contained in magma supply the volcanic energy resulting in the conclusions that earthquakes and eruptions are unpredictable. Volcanic eruption is considered herein to be a special case of the earthquake-process in which earthquake hypocenters rise to the Earth’s surface. A possible solution is proposed ([1] and herein) based on the analyses of the physicochemical processes as participants in earthquake and eruption preparations (foreshocks - major shock - aftershocks - volcanic eruptions) and on the characteristic rates of reflection of these processes on the Earth’s surface. Influences of Sun-Moon-tides and volcanic (“harmonic”) tremors are analyzed from physical-chemical point of view. The case of the 1980 eruption of Mount St. Helens and the proposed monitoring of the recommended additional data provides a way of selecting a complex of reliable earthquake and volcanic eruption precursors.
文摘The Laboratory of Rare Earth Chemistry and Physics,Changchun Institute of Ap-plied Chemistry,Academia Sinica,has been opened to foreign scientists since October,1987.The first plenary session of the Academic Committee was held in March,1988,andthe first batch of research projects granted by the Scientific Funds of the Laboratory wereapproved at this meeting.
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.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12122403 and 12327807).
文摘Full waveform inversion(FWI)has showed great potential in the detection of musculoskeletal disease.However,FWI is an ill-posed inverse problem and has a high requirement on the initial model during the imaging process.An inaccurate initial model may lead to local minima in the inversion and unexpected imaging results caused by cycle-skipping phenomenon.Deep learning methods have been applied in musculoskeletal imaging,but need a large amount of data for training.Inspired by work related to generative adversarial networks with physical informed constrain,we proposed a method named as bone ultrasound imaging with physics informed generative adversarial network(BUIPIGAN)to achieve unsupervised multi-parameter imaging for musculoskeletal tissues,focusing on speed of sound(SOS)and density.In the in-silico experiments using a ring array transducer,conventional FWI methods and BUIPIGAN were employed for multiparameter imaging of two musculoskeletal tissue models.The results were evaluated based on visual appearance,structural similarity index measure(SSIM),signal-to-noise ratio(SNR),and relative error(RE).For SOS imaging of the tibia–fibula model,the proposed BUIPIGAN achieved accurate SOS imaging with best performance.The specific quantitative metrics for SOS imaging were SSIM 0.9573,SNR 28.70 dB,and RE 5.78%.For the multi-parameter imaging of the tibia–fibula and human forearm,the BUIPIGAN successfully reconstructed SOS and density distributions with SSIM above 94%,SNR above 21 dB,and RE below 10%.The BUIPIGAN also showed robustness across various noise levels(i.e.,30 dB,10 dB).The results demonstrated that the proposed BUIPIGAN can achieve high-accuracy SOS and density imaging,proving its potential for applications in musculoskeletal ultrasound imaging.
基金supported by National Natural Science Foundation of China(62227818,12204239,62275121)Youth Foundation of Jiangsu Province(BK20220946)+1 种基金Fundamental Research Funds for the Central Universities(30923011024)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202201).
文摘Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL models,however,do not necessarily obey the fundamental governing laws of PAM physical systems,nor do they generalize well to scenarios on which they have not been trained.In this work,a physics-embedded degeneration learning(PEDL)approach is proposed to enhance the image quality of PAM with a self-attention enhanced U-Net network,which obtains greater physical consistency,improves data efficiency,and higher adaptability.The proposed method is demonstrated on both synthetic and real datasets,including animal experiments in vivo(blood vessels of mouse's ear and brain).And the results show that compared with previous DL methods,the PEDL algorithm exhibits good performance in recovering PAM images qualitatively and quantitatively.It overcomes the challenges related to training data,accuracy,and robustness which a typical data-driven approach encounters,whose exemplary application envisions to provide a new perspective for existing DL tools of enhanced PAM.
