Science China Physics, Mechanics & Astronomy最新文献_第5页

Confirming HSC strong lens candidates with DESI spectroscopy. I. Project overview and first results 用DESI光谱确认HSC强透镜候选者。一、项目概况及初步成果

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-09-08 DOI: 10.1007/s11433-025-2747-4

Yiping Shu, Shen Li

{"title":"Confirming HSC strong lens candidates with DESI spectroscopy. I. Project overview and first results","authors":"Yiping Shu, Shen Li","doi":"10.1007/s11433-025-2747-4","DOIUrl":"10.1007/s11433-025-2747-4","url":null,"abstract":"<div><p>Accurate redshift determinations of both lenses and sources are critical for confirming strong-lens systems and fully realizing their scientific value. However, the thousands of strong-lens candidates now routinely discovered in wide-field imaging surveys make one-by-one follow-up observations impractical. In this work, we investigate the capability and efficiency of large-scale spectroscopic surveys in confirming strong-lens systems. As a case study, we cross-match strong lens candidates identified from the Hyper Suprime-Cam Subaru Strategic Program with Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI). We find that DESI DR1 serendipitously observed putative lenses and/or lensed images in approximately 50% of these candidates. Analyzing the DESI spectra for ≈ 500 matched candidates that meet our selection criteria, we determine both lens and source red-shifts for 27 systems. Additionally, 76 candidate systems feature lensing galaxies at <i>z</i> > 0:8, and one candidate system contains a quasar within its lensing galaxy. Applying this approach to other strong-lens candidates will yield many more confirmations, with a further several-fold increase anticipated from the final DESI data release. Our results highlight the growing importance of large-scale spectroscopic surveys in advancing strong lensing discoveries and science.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"68 12","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Photon induced proton and anti-proton pair production with ultraperipheral heavy ion collisions at RHIC 超外围重离子碰撞中光子诱导质子和反质子对的产生

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-09-08 DOI: 10.1007/s11433-025-2720-6

Cheng Zhang, Limao Zhang, Dingyu Shao

引用次数: 0

Quantum criticality and emergent many-body excitations in quasi-one-dimensional quantum magnetic systems 准一维量子磁系统中的量子临界和涌现多体激发

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-09-08 DOI: 10.1007/s11433-025-2738-0

Yunjing Gao, Rong Yu, Jianda Wu

{"title":"Quantum criticality and emergent many-body excitations in quasi-one-dimensional quantum magnetic systems","authors":"Yunjing Gao, Rong Yu, Jianda Wu","doi":"10.1007/s11433-025-2738-0","DOIUrl":"10.1007/s11433-025-2738-0","url":null,"abstract":"<div><p>Investigation of quantum criticality in condensed matter systems not only reveals universal behaviors of quantum phase transitions but also deepens our understanding of emergent physics in quantum many-body systems. With accurate descriptions of the ground states and low-energy excitations of (quasi-)one-dimensional (1D) quantum spin models, significant progress has been made in studying quantum criticality and related emergent physics. In this review, we provide a short survey on some recent developments in this field. We start by discussing critical thermodynamics and dynamics of transverse-field Ising chain, highlighting novel quantum integrability and many-body excitations upon relevant perturbations. Dynamical properties of the excitations are further discussed, along with their experimental verification. Along the line of integrability, we further discuss the Heisenberg-Ising chain, introducing the string magnetic state. Among them, non-trivial string solutions which go beyond conventional field theory, have also been observed in experiments. Apart from the critical phenomena associated with the standard Ginzburg-Landau paradigm, we introduce the deconfined quantum criticality, which arises as a consequence of a continuous phase transition between two ordered states. Such a transition goes beyond the description of the Ginzburg-Landau paradigm and is characterized by the emergence of fractionalized spin excitations and enhanced continuous symmetry at the quantum critical point. Finally, we conclude by highlighting potential novel critical phenomena and emergent physics and their realizations in quasi-1D quantum magnetic systems.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"69 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fullerphene: A double covalently bonded two-dimensional fullerene semiconducting crystal with preserved Dirac states and emergent flat bands 富勒烯：一种双共价键的二维富勒烯半导体晶体，具有保留的狄拉克态和涌现的平带

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-09-08 DOI: 10.1007/s11433-025-2739-x

Yandi Zhu, Xiaoyan Ren, Xinlian Xue, Xigui Yang, Chongxin Shan, Xingju Zhao, Shunfang Li, Zhenyu Zhang

{"title":"Fullerphene: A double covalently bonded two-dimensional fullerene semiconducting crystal with preserved Dirac states and emergent flat bands","authors":"Yandi Zhu, Xiaoyan Ren, Xinlian Xue, Xigui Yang, Chongxin Shan, Xingju Zhao, Shunfang Li, Zhenyu Zhang","doi":"10.1007/s11433-025-2739-x","DOIUrl":"10.1007/s11433-025-2739-x","url":null,"abstract":"<div><p>The discovery of each new allotropic manifestation of carbon has substantially propelled contemporary scientific research and applications, as vividly exemplified by the explosive progressions within the realms of fullerene, carbon nanotube, graphene, and diamond sciences over recent decades. Here, using state-of-the-art first-principles calculations, we predict a new type of two- dimensional carbon network, dubbed fullerphene, by replacing each C atom in graphene with a fullerene (C[in60}). Its high energetic stability is tied to the symmetric cycloaddition of the double bonds between each C[in60} superatom with each of its three neighbors. A kinetic pathway is also proposed for the selective fabrication of fullerphene on Cu(111) or Rh(111), upon exploiting its en- hanced stability over other competing C[in60} assemblies and significantly lowered kinetic barrier in seed growing, as strategically supported by a recent experimental advance. Further investigations on fullerphene reveal an array of desirable characteristics, including a substantial band gap of ~2 eV, Dirac states for the conduction electrons, and flat bands for the valence electrons. These findings represent a distinctly new and significant advance in both fullerene and graphene sciences.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"68 12","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physics-informed neural networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and future prospects 基于物理信息的神经网络（pinn）作为求解偏微分方程的智能计算技术：局限性与未来展望

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-09-01 DOI: 10.1007/s11433-024-2665-5

Weiwei Zhang, Wei Suo, Jiahao Song, Wenbo Cao

{"title":"Physics-informed neural networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and future prospects","authors":"Weiwei Zhang, Wei Suo, Jiahao Song, Wenbo Cao","doi":"10.1007/s11433-024-2665-5","DOIUrl":"10.1007/s11433-024-2665-5","url":null,"abstract":"<div><p>In recent years, physics-informed neural networks (PINNs) have become a representative method for solving partial differential equations (PDEs) with neural networks. PINNs provide a novel approach to solving PDEs through optimization algorithms, offering a unified framework for solving both forward and inverse problems. However, some limitations in terms of solution accuracy and generality have also been revealed. This paper systematically summarizes the limitations of PINNs and identifies three root causes for their failure in solving PDEs: (1) poor multiscale approximation ability and ill-conditioning caused by PDE losses; (2) insufficient exploration of convergence and error analysis, resulting in weak mathematical rigor; (3) inadequate integration of physical information, causing mismatch between residuals and iteration errors. By focusing on addressing these limitations in PINNs, we outline the future directions and prospects for the intelligent computing of PDEs: (1) analysis of ill-conditioning in PINNs and mitigation strategies; (2) improvements to PINNs by enforcing temporal causality; (3) empowering PINNs with classical numerical methods.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"69 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implicit factorized transformer approach to fast prediction of turbulent channel flows 紊流通道流动的隐式分解变压器快速预测方法

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-09-01 DOI: 10.1007/s11433-024-2666-9

Huiyu Yang, Yunpeng Wang, Jianchun Wang

{"title":"Implicit factorized transformer approach to fast prediction of turbulent channel flows","authors":"Huiyu Yang, Yunpeng Wang, Jianchun Wang","doi":"10.1007/s11433-024-2666-9","DOIUrl":"10.1007/s11433-024-2666-9","url":null,"abstract":"<div><p>Transformer neural operators have recently become an effective approach for surrogate modeling of systems governed by partial differential equations (PDEs). In this paper, we introduce a modified implicit factorized transformer (IFactFormer-m) model, replacing the original chained factorized attention with parallel factorized attention. The IFactFormer-m model successfully performs long-term predictions for turbulent channel flow. In contrast, the original IFactFormer (IFactFormer-o), Fourier neural operator (FNO), and implicit Fourier neural operator (IFNO) exhibit a poor performance. Turbulent channel flows are simulated by direct numerical simulation using fine grids at friction Reynolds numbers <i>Re</i><sub><i>τ</i></sub> ≈ 180, 395, 590, and filtered to coarse grids for training neural operator. The neural operator takes the current flow field as input and predicts the flow field at the next time step, and long-term prediction is achieved in the posterior through an autoregressive approach. The results show that IFactFormer-m, compared with other neural operators and the traditional large eddy simulation (LES) methods, including the dynamic Smagorinsky model (DSM) and the wall-adapted local eddy-viscosity (WALE) model, reduces prediction errors in the short term, and achieves stable and accurate long-term prediction of various statistical properties and flow structures, including the energy spectrum, mean streamwise velocity, root mean square (RMS) values of fluctuating velocities, Reynolds shear stress, and spatial structures of instantaneous velocity. Moreover, the trained IFactFormer-m is much faster than traditional LES methods. By analyzing the attention kernels, we elucidate why IFactFormer-m converges faster and achieves a stable and accurate long-term prediction compared with IFactFormer-o. Code and data are available at: https://github.com/huiyu-2002/IFactFormer-m.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"69 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A fast transonic airfoil flow field prediction model based on a modified Fourier neural operator 基于改进傅里叶神经算子的快速跨声速翼型流场预测模型

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-08-29 DOI: 10.1007/s11433-024-2659-1

Weishao Tang, Chenyu Wu, Yunjia Yang, Yufei Zhang

{"title":"A fast transonic airfoil flow field prediction model based on a modified Fourier neural operator","authors":"Weishao Tang, Chenyu Wu, Yunjia Yang, Yufei Zhang","doi":"10.1007/s11433-024-2659-1","DOIUrl":"10.1007/s11433-024-2659-1","url":null,"abstract":"<div><p>Traditional aerodynamic optimization coupled with computational fluid dynamics is associated with a high computational cost. Surrogate models based on deep learning methods can rapidly predict flow fields from the grid input but often suffer from poor accuracy and generalizability. This study introduces a modified Fourier neural operator for flow field prediction. Unlike most convolution-based models, the Fourier neural operator learns the solution operator directly in the function space, enhancing predictive accuracy and generalizability. The proposed model incorporates a shallow feature extractor, a boundary variable fine-tuner, and several physical priors, including the initial flow field and boundary conditions. The model is trained on uniformly parameterized algebraic grids to accelerate grid generation in aerodynamic optimization. The prediction error for the flow field and force coefficients on the validation and test sets is reduced by 70% to 90% compared with that of the previous convolutional model. The proposed model can make precise predictions for supercritical airfoils under typical working conditions, with a drag coefficient error of approximately 1 drag count on the validation set, and generalizes better than previous convolution-based methods do on extrapolative inflow conditions and airfoils.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"69 1","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145248238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Symbolic learning of material constitutive laws 物质本构规律的符号化学习

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-08-29 DOI: 10.1007/s11433-025-2627-2

Yang Liu, Jingdi Wan

引用次数: 0

A new strategy for exploring room-temperature superconductivity in hydrides at ambient pressure 探索室温下氢化物超导性的新策略

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-08-26 DOI: 10.1007/s11433-025-2750-1

X. C. Xie

引用次数: 0

The theory of “electride-carrier” precompression “电极-载流子”预压缩理论

IF 7.5 1区物理与天体物理

Science China Physics, Mechanics & Astronomy Pub Date : 2025-08-19 DOI: 10.1007/s11433-025-2745-4

Zhongyu Wan, Guo-Hua Zhong, Ruiqin Zhang, Hai-Qing Lin

{"title":"The theory of “electride-carrier” precompression","authors":"Zhongyu Wan, Guo-Hua Zhong, Ruiqin Zhang, Hai-Qing Lin","doi":"10.1007/s11433-025-2745-4","DOIUrl":"10.1007/s11433-025-2745-4","url":null,"abstract":"<div><p>Room-temperature superconductivity is predominantly observed in high-pressure hydrides, but faces a formidable hurdle: the tendency of these materials to decompose and forfeit their superconducting prowess upon pressure release. Consequently, stabilizing room-temperature superconductivity under ambient conditions has emerged as a pressing concern in solid-state physics. Electrides are unique compounds, possessing exceptional properties attributed to the clustering of high-energy excess electrons within the interstices of their lattices. Our theory outlines a general blueprint for achieving ambient superconductivity through the strategic insertion of hydrogen into the interstitial spaces of electride materials. This ingenious approach harnesses quasimolecular H<sub>2</sub> to sequester high-energy electrons, resulting in a substantial density of electronic states at the Fermi level and fostering robust electron-phonon coupling. We implemented this strategy within the realm of alkali metal electrides, fine-tuning their stability via carrier doping effects, grounded in rigorous quantum chemical analyses of pressure-induced chemical bonds. As a result, the KH<sub>6</sub> compound exhibits an exceptional superconducting transition temperature of 222 K at a modest 10 GPa, outperforming previously reported high-pressure superconductors like H<sub>3</sub>S (203 K at 155 GPa) and LaH<sub>10</sub> (250 K at 170 GPa). Furthermore, the hole-doped NaH<sub>6</sub> compound demonstrates superconductivity at ambient pressure with a remarkable <i>T</i><sub>c</sub> of 167 K, surpassing the previous record-holder HgBa<sub>2</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>8</sub> with 134 K.</p></div>","PeriodicalId":774,"journal":{"name":"Science China Physics, Mechanics & Astronomy","volume":"68 10","pages":""},"PeriodicalIF":7.5,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0