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Silk damping in scalar-induced gravitational waves: a novel probe for new physics

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Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 79-85页

作者： Yan-Heng Yu Sai Wang theoretical physics Division Institute of High Energy Physics Chinese Academy of Sciences School of physics University of Chinese Academy of Sciences

Silk damping is well known in the study of cosmic microwave background（CMB） and accounts for suppression of the angular power spectrum of CMB on large angular multipoles. In this article, we study the effect of Silk damping on the scalar-induced gravitational waves（SIGWs）. Resulting from the dissipation of cosmic fluid, the Silk damping notably suppresses the energydensity spectrum of SIGWs on scales comparable to a diffusion scale at the decoupling time of weakly-interacting particles. The effect offers a novel observable for probing the underlying particle interaction, especially for those mediated by heavy gauge bosons beyond the standard model of particles. We anticipate that pulsar timing arrays are sensitive to gauge bosons with mass ～10～3-10～4 GeV, while space-and ground-based interferometers to those with mass ～10～7-1012GeV, leading to essential complements to on-going and future experiments of high-energy physics.

关键词： scalar-induced gravitational waves Silk damping new physics

Decision making module based on stochastic magnetic tunnel junctions

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Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 202-209页

作者： Yifan Miao Li Zhao Yajun Zhang Zhe Yuan Center for Advanced Quantum Studies and department of physics Beijing Normal University Institute for Nanoelectric Devices and Quantum Computing Fudan University Interdisciplinary Center for theoretical physics and Information Sciences Fudan University

In biological neural systems, noise is ubiquitous but does not affect the correct decisions made in the complex cognitive ***-making in biological neural system is typically achieved by accumulating input information over a period of *** by recent developments in neurosciences, we design a decision-making module based on spintronic devices, utilizing superparamagnetic tunnel junctions as artificial neurons. The feasibility of this decision-making module is verified through circuit simulations. Taking a multi-layer perceptron as an example, the module significantly improves the accuracy of the perceptron in the handwritten digit recognition task. Furthermore, the spintronic decision-making module offers advantages over the conventional pooling methods, such as adaptive decision time, high performance and the absence of analog-to-digital conversion. The decision-making module is flexible to be integrated into artificial neural networks and provides a general yet effective solution to enhance performance against device noise.

关键词： neuromorphic computing spintronics magnetic tunnel junction neural networks

Rough singular integrals associated to surfaces of revolution on product spaces

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Acta Mathematica Sinica,English Series 2025年

作者： Hussain AL-QASSEM Leslie CHENG Yibiao PAN mathematics Program Department of Mathematics Statistics and Physics College of Arts and Sciences Qatar University department of mathematics Bryn Mawr College department of mathematics University of Pittsburgh

We study the Lpboundedness of singular integral operators along surfaces of revolution on product spaces. The Lpboundedness for these operators are obtained under very weak conditions on kernels. Our results are new and they improve several previously known results. Furthermore, they are natural extensions of many known results on singular integrals in the one-parameter setting and they subsume many other corresponding results on the product space setting.

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Establishing the vector-meson-exchange dominance for the short range interactions of light quarks

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Science China(physics,Mechanics & Astronomy) 2025年

作者： Bing-Song Zou department of physics Tsinghua University CAS Key Laboratory of theoretical physics Institute of Theoretical Physics Chinese Academy of Sciences School of physics University of Chinese Academy of Sciences Southern Center for Nuclear-Science Theory (SCNT) Institute of Modern Physics Chinese Academy of Sciences

Understanding the interactions between constituent quarks is one of the fundamental and challenging problems in hadron physics. At present, the constituent quark models have achieved great success in describing the properties of hadrons, whereas some long-standing disputes remain, especially for the short range interactions between constituent quarks. In exploring the dynamic mechanism between u/d quarks, it is found that the one gluon exchange and/or vector meson exchange induced interactions may dominate the short range interactions [1].

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Sky location of massive black hole binaries in the foreground of Galactic white dwarf binaries

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Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 97-108页

作者： Pan Guo Hong-Bo Jin Cong-Feng Qiao Yue-Liang Wu The International Centre for theoretical physics Asia-Pacific University of Chinese Academy of Sciences The School of Physical Sciences University of Chinese Academy of Sciences Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University National Astronomical Observatories Chinese Academy of Sciences Institute of theoretical physics Chinese Academy of Sciences

For space-based gravitational wave （GW） detection,the main noise source for massive black hole binaries （MBHBs） is attributed to approximately 10～7double white dwarf binaries in the *** a GW source,the amplitude of the detector response,recorded by a space-based gravitational wave detector,exhibits a modulation effect with a year period when observing the source from various orbital *** the adverse conditions mentioned above,where there is a strong foreground noise and annual modulation in the signals,we employed the wavelet transform and the strong-amplitude relevant orbital position search methods,which allows the weak MBHB sources to achieve higher locating *** detail,for two MBHB sources of lower intensity,the precision of luminosity distance,represented by the ratio ?DL/DLat the 95%confidence level,is enhanced by factors of ～*** angular resolutions,denoted by??s,are enhanced by a factor of ～*** improvements increase the number of detectable GW sources,facilitate multi-messenger follow-up observations and provide constraints on the cosmological constant.

关键词： space-based gravitational wave detection gravitational waves massive black hole binaries

The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

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Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao Han Yi-Yang Guo He Wang Minghui Du Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou Center for theoretical physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of theoretical physics & Research Center of Gravitation Lanzhou University International Centre for theoretical physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

Reducing the measurement errors in nonadiabatic holonomic quantum computers

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Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 64-70页

作者： Guo-Fu Xu department of physics Shandong University

Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum *** quantum computation has entered the noisy intermediate-scale era, building accurate intermediate-scale nonadiabatic holonomic quantum computers is clearly necessary. Given that measurements are the sole means of extracting information, they play an indispensable role in nonadiabatic holonomic quantum computers. Accordingly, developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance. However, while much attention has been given to the research on nonadiabatic holonomic gates, the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking. In this study, we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers. The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates. Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.

关键词： quantum holonomy quantum computation measurement errors

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 501-530页

作者： Khuram Ali Khan Saba Mubeen Ishfaq Atiqe Ur Rahman Salwa El-Morsy department of mathematics University of SargodhaSargodha40100Pakistan department of mathematics University of Management and TechnologyLahore54000Pakistan department of mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be *** concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such *** study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and *** results related to these operations are also modified for ***,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and ***,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested *** algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical ***,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

关键词： Hypersoft set Pythagorean fuzzy hypersoft set computational complexity multi-attribute decision-making optimization similarity measures uncertainty

Effect of order–disorder transition on thermodynamic and electronic properties of σ and χ phases in W–Re alloy: the first-principles calculation

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Tungsten 2025年第1期7卷 195-213页

作者： Zhi-Peng Zhu Dian Jia William Yi Wang Jun-Lei Yin Xing-Yu Gao Shu-Feng Yang Hai-Feng Song Jin-Shan Li State Key Laboratory of Solidification Processing Northwestern Polytechnical University Laboratory of Computational physics Institute of Applied Physics and Computational Mathematics School of Metallurgical and Ecological Engineering University of Science and Technology Beijing

The Tungsten-Rhenium(W-Re) alloys,celebrated for their high melting point,strength at elevated temperatures,electrical resistivity,and radiation resistance,have been widely utilized in high-temperature components,aerospace,electronics,and nuclear *** constituents of the topologically close-packed(TCP) phases,the sigma phase(σ) and chi phase(χ) formed within W-Re alloys wield considerable influence on the mechanical properties and the stability of the *** calculations were utilized in the present work to explore the structural,thermodynamic,and electronic properties of both ordered and disordered configurations within the σ and χ phases,culminating in a systematic elucidation of the higher phase stability exhibited by the ordered *** is found that the bulk modulus of these two phases is directly proportional to the concentration of Re in the alloy,while the equilibrium volume is inversely *** thermodynamic parameters of the σ and χ phases are calculated via the mean-field potential *** similar trends observed in the isobaric heat capacity,enthalpy increment,and entropy change curves for these two phases suggest they possess comparable thermodynamic *** is noteworthy that the contribution of ionic vibrations predominantly affects the isobaric heat capacity,while the contribution of thermal electronic excitations increases linearly with *** the structure and thermodynamic properties of TCP phases in W-Re alloys at low temperatures has profound significance for optimizing material performance,microstructures features,establishing theoretical foundations,and predicting material behavior.

关键词： First-principles calculations Phase stability TCP phases Thermodynamic properties W–Re alloy