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Terahertz spin dynamics in rare-earth orthoferrites

Photonics Insights 2022年第2期1卷 1-56页

作者： Xinwei Li Dasom Kim Yincheng Liu Junichiro Kono Department of Physics California Institute of TechnologyPasadenaUSA Department of Electrical and Computer Engineering Rice UniversityHoustonUSA Applied Physics Graduate Program Smalley-Curl InstituteRice UniversityHoustonUSA Department of Physics and Astronomy Rice UniversityHoustonUSA Department of Materials Science and NanoEngineering Rice UniversityHoustonUSA

Recent interest in developing fast spintronic devices and laser-controllable magnetic solids has sparked tremendous experimental and theoretical efforts to understand and manipulate ultrafast dynamics in *** of spin dynamics in the terahertz(THz)frequency range are particularly important for elucidating microscopic pathways toward novel device ***,we review THz phenomena related to spin dynamics in rare-earth orthoferrites,a class of materials promising for antiferromagnetic *** expand this topic into a description of four key elements.(1)We start by describing THz spectroscopy of spin excitations for probing magnetic phase transitions in thermal *** acoustic magnons are useful indicators of spin reorientation transitions,electromagnons that arise from dynamic magnetoelectric couplings serve as a signature of inversion-symmetry-breaking phases at low temperatures.(2)We then review the strong laser driving scenario,where the system is excited far from equilibrium and thereby subject to modifications to the free-energy *** pathways for ultrafast laser manipulation of magnetic order are discussed.(3)Furthermore,we review a variety of protocols to manipulate coherent THz magnons in time and space,which are useful capabilities for antiferromagnetic spintronic applications.(4)Finally,new insights into the connection between dynamic magnetic coupling in condensed matter and the Dicke superradiant phase transition in quantum optics are *** presenting a review on an array of THz spin phenomena occurring in a single class of materials,we hope to trigger interdisciplinary efforts that actively seek connections between subfields of spintronics,which will facilitate the invention of new protocols of active spin control and quantum phase engineering.

关键词： terahertz spin dynamics magnetism orthoferrite ultrafast spectroscopy magneto-optics

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Investigation of Novel Preclinical Total Body PET Designed With J-PET Technology: A Simulation Study

arXiv

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arXiv 2024年

作者： Dadgar, M. Parzych, S. Ardebili, F. Tayefi Baran, J. Chug, N. Curceanu, C. Czerwiński, E. Dulski, K. Eliyan, K. Gajos, A. Hiesmayr, B.C. Kacprzak, K. Kaplon, L. Klimaszewski, K. Konieczka, P. Korcyl, G. Kozik, T. Krzemien, W. Kumar, D. Niedzwiecki, S. Panek, D. del Rio, E. Perez Raczynski, L. Sharma, S. Shivani Shopa, R.Y. Skurzok, M. Ardebili, K. Tayefi Vandenberghe, S. Wislicki, W. Stepien, E.L. Moskal, P. The Faculty of Physics Astronomy and Applied Computer Science Total Body Jagiellonian-PET Laboratory Jagiellonian University Kraków31-007 Poland The Faculty of Physics Astronomy and Applied Computer Science Total Body Jagiellonian-PET Laboratory Jagiellonian University Kraków31-007 Poland INFN Laboratori Nazionali di Frascati Frascati00044 Italy The Faculty of Physics University of Vienna Vienna1010 Austria The Department of Complex Systems National Centre for Nuclear Research Otwock-Świerk 05-400 Poland High Energy Physics Division National Centre for Nuclear Research Otwock-Świerk 05-400 Poland The Department of Electronics and Information Systems MEDISIP Ghent University-IBiTech Ghent9000 Belgium

The growing interest in human-grade total body positron emission tomography (PET) systems has also application in small animal research. Due to the existing limitations in human-based studies involving drug development and novel treatment monitoring, animal-based research became a necessary step for testing and protocol preparation. In this simulation-based study two unconventional, cost-effective small animal total body PET scanners (for mouse and rat studies) have been investigated in order to inspect their feasibility for preclinical research. They were designed with the novel technology explored by the Jagiellonian-PET (J-PET) Collaboration. Two main PET characteristics: sensitivity and spatial resolution were mainly inspected to evaluate their performance. Moreover, the impact of the scintillator dimension and time-of-flight on the latter parameter was examined in order to design the most efficient tomographs. The presented results show that for mouse TB J-PET the achievable system sensitivity is equal to 2.35% and volumetric spatial resolution to 9.46 ± 0.54 mm3, while for rat TB J-PET they are equal to 2.6% and 14.11 ± 0.80 mm3, respectively. Furthermore, it was shown that the designed tomographs are almost parallax-free systems, hence, they resolve the problem of the acceptance criterion tradeoff between enhancing spatial resolution and reducing sensitivity. © 2024, CC BY.

关键词： Positrons

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Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng Wang Chaojun Ouyang Min Chen Chenying Liu Jin Zhang Long Yu Fei Wang Yong Xie Jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu Chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao Chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of Geographical Sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

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Product states optimize quantum p-spin models for large p

arXiv

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arXiv 2023年

作者： Anschuetz, Eric R. Gamarnik, David Kiani, Bobak T. Institute for Quantum Information and Matter Caltech Walter Burke Institute for Theoretical Physics Caltech MIT Center for Theoretical Physics MIT United States Operations Research Center Statistics and Data Science Center Sloan School of Management MIT United States John A. Paulson School of Engineering and Applied Sciences Harvard Department of Electrical Engineering and Computer Science MIT United States

We consider the problem of estimating the maximal energy of quantum p-local spin glass random Hamiltonians, the quantum analogues of widely studied classical spin glass models. Denoting by E∗(p) the (appropriately normalized) maximal energy in the limit of a large number of qubits n, we show that E∗(p) approaches √2 log 6 as p increases. This value is interpreted as the maximal energy of a much simpler so-called Random Energy Model, widely studied in the setting of classical spin glasses. Our most notable and (arguably) surprising result proves the existence of near-maximal energy states which are product states, and thus not entangled. Specifically, we prove that with high probability as n → ∞, for any E ∗(p) there exists a product state with energy ≥ E at sufficiently large constant p. Even more surprisingly, this remains true even when restricting to tensor products of Pauli eigenstates. Our approximations go beyond what is known from monogamy-of-entanglement style arguments—the best of which, in this normalization, achieve approximation error growing with n. Our results not only challenge prevailing beliefs in physics that extremely low-temperature states of random local Hamiltonians should exhibit non-negligible entanglement, but they also imply that classical algorithms can be just as effective as quantum algorithms in optimizing Hamiltonians with large locality—though performing such optimization is still likely a hard problem. Our results are robust with respect to the choice of the randomness (disorder) and apply to the case of sparse random Hamiltonian using Lindeberg’s interpolation method. The proof of the main result is obtained by estimating the expected trace of the associated partition function, and then matching its asymptotics with the extremal energy of product states using the second moment method. Copyright © 2023, The Authors. All rights reserved.

关键词： Hamiltonians

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Comparison of the Effectiveness of Machine Learning Techniques for the Number of Road Traffic Injuries

Comparison of the Effectiveness of Machine Learning Techniqu...

引用

International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Wirawan Puttamat Wikanda Phaphan Anuchit Jitpattanakul Chainarong Pianpailoon Sakorn Mekruksavanich Department of Mathematics Faculty of Education Chaiyaphum Rajabhat University Chaiyaphum Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Research Group in Statistical Learning and Inference Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Curriculum and Teaching Program (Mathematics) Faculty of Education Sakon Nakhon Rajabhat University Sakon Nakhon Thailand Department of Computer Engineering School of Information and Communication University of Phayao Phayao Thailand

This article aims to compare forecasting techniques with machine learning techniques for predicting the number of people injured in road accidents using data from the Injury information Collaboration Center, department of Disease Control, Ministry of Public Health Outpatient Files (OPD) spanning the years 2018 to 2022. The four machine-learning techniques examined in this study include Decision Tree Regression, Random Forest Regression, Support Vector Regression, and Multiple Linear Regression. The data analysis was performed using the R programming language. The results revealed that the Decision Tree Regression technique yielded the most accurate predictions for the number of road traffic injuries, as evidenced by its lowest values of MAE, MSE, and RMSE.

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Raman Signatures of Single Point Defects in Hexagonal Boron Nitride Quantum Emitters

arXiv

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arXiv 2025年

作者： Cholsuk, Chanaprom Çakan, Aslı Deckert, Volker Suwanna, Sujin Vogl, Tobias Department of Computer Engineering TUM School of Computation Information and Technology Technical University of Munich Munich80333 Germany Munich80799 Germany Institute of Physical Chemistry Friedrich-Schiller University Jena07743 Germany Leibniz Institute of Photonic Technology Jena07745 Germany Abbe Center of Photonics Institute of Applied Physics Friedrich Schiller University Jena Jena07745 Germany Optical and Quantum Physics Laboratory Department of Physics Faculty of Science Mahidol University Bangkok10400 Thailand

Point defects in solid-state quantum systems are vital for enabling single-photon emission at specific wavelengths, making their precise identification essential for advancing applications in quantum technologies. However, pinpointing the microscopic origins of these defects remains a challenge. In this work, we propose Raman spectroscopy as a robust strategy for defect identification. Using density functional theory, we systematically characterize the Raman signatures of 100 defects in hexagonal boron nitride (hBN) spanning periodic groups III to VI, encompassing around 30,000 phonon modes. Our findings reveal that the local atomic environment plays a pivotal role in shaping the Raman lineshape, enabling the narrowing of potential defect candidates. Furthermore, we demonstrate that Raman spectroscopy can differentiate defects based on their spin and charge states as well as strain-induced variations, implying the versatility of this approach. Therefore, this study not only provides a comprehensive theoretical database of Raman spectra for hBN defects but also establishes a novel experiment framework for using tip-enhanced Raman spectroscopy to identify point defects. More broadly, our approach offers a universal method for defect identification in any quantum materials. Copyright © 2025, The Authors. All rights reserved.

关键词： Point defects

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Non-Plasmon Resonances in the E-polarized Plane Wave Scattering and Absorption by a Circular Dielectric Wire with Partial Graphene Cover 41

Non-Plasmon Resonances in the E-polarized Plane Wave Scatter...

引用

41st IEEE International Conference on Electronics and Nanotechnology, ELNANO 2022

作者： Mikhailikova, Iryna Dukhopelnykov, Sergii V. Sauleau, Ronan V. N. Karazin Kharkiv National University Department of Applied Mathematics Kharkiv Ukraine Computer Science and Mathematics University of l'Aquila Department of Information Engineering L'Aquila Italy Institute of Radio-Physics and Electronics NASU Laboratory of Micro and Nano Optics L'Institut d'Electronique et des Technologies du NuméRique Universite de Rennes 1 Rennes France

ISBN: (数字)9781665469227

ISBN: (纸本)9781665469234

We analyze how the total scattering cross-section (TSCS) and absorption cross-section (ACS) of a circular dielectric rod, illuminated with the E-polarized plane wave, is modified by a conformal graphene strip of arbitrary angular width and chemical potential. In the core of our treatment, there is a dual series equation where the unknown are the field angular Fourier harmonics. We subject this equation to the Inverse Discrete Fourier Transform (IDFT) that yields a Fredholm second kind matrix equation. Such a procedure guarantees the convergence of the obtained numerical results. We present the normalized TSCS and ACS versus the angular width of graphene strip and the frequency in the range from the statics to 1 THz. These plots convincingly demonstrate that the resonances on the lowest non-plasmon natural modes of the considered scatterer are still tunable due to the tunability of graphene's conductivity. © 2022 IEEE.

关键词： Graphene

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Nanoslot-Induced Ultrastrong Phonon-Photon and Phonon-Phonon Coupling in Hybrid Organic-Inorganic Perovskites

Nanoslot-Induced Ultrastrong Phonon-Photon and Phonon-Phonon...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Dasom Kim Jin Hou Geon Lee Ayush Agrawal Sunghwan Kim Hao Zhang Di Bao Andrey Baydin Wenjing WU Fuyang Tay Shengxi Huang Daivd Hagenmüller Elbert E. M. Chia Dai-Sik Kim Minah Seo Aditya D. Mohite Junichiro Kono Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Electrical and Computer Engineering Rice University Houston TX USA Department of Materials Science and NanoEngineering Rice University Houston TX USA Sensor System Research Center Korea Institute of Science and Technology Seoul Republic of Korea Department of Physics and Astronomy Seoul National University Seoul Republic of Korea Department of Chemical and Biomolecular Engineering Rice University Houston TX USA Department of Physics Long-wavelength Nanotechnology Laboratory Quantum Photonics Institute Ulsan National Institute of Science and Technology (UNIST) Ulsan Republic of Korea Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore Smalley-Curl institute Rice University Houston TX USA CESQ-ISIS (UMR 7006) Universite de Strasbourg and CNRS Strasbourg France KU-KIST Graduate School of Converging Science and Technology Korea University Seoul Republic of Korea Department of Physics and Astronomy Rice University Houston TX USA

Methods for harnessing vibrational states are desired for phonon-based technologies. We realized ultrastrong coupling of two phonon modes in perovskite materials induced by ultrastrong coupling with a common photonic ... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Couplings Phonons Laser modes Perovskites Electro-optical waveguides Photonics

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Ultra-Low-Loss Silicon Nitride Photonics Based on Deposited Films Compatible with Foundries

arXiv

引用

arXiv 2023年

作者： Ji, Xingchen Okawachi, Yoshitomo Gil-Molina, Andres Corato-Zanarella, Mateus Roberts, Samantha Gaeta, Alexander L. Lipson, Michal Department of Electrical Engineering Columbia University New YorkNY10027 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States Currently at John Hopcroft Center for Computer Science School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

The fabrication processes of silicon nitride (Si3N4) photonic devices used in foundries require low temperature deposition, which typically leads to high propagation losses. Here, we show that propagation loss as low as 0.42 dB/cm can be achieved using foundry compatible processes by solely reducing waveguide surface roughness. By post-processing the fabricated devices using rapid thermal anneal (RTA) and furnace anneal, we achieve propagation losses down to 0.28 dB/cm and 0.06 dB/cm, respectively. These low losses are comparable to the conventional devices using high temperature, high-stress LPCVD films. We also tune the dispersion of the devices, and proved that these devices can be used for linear and nonlinear applications. Low threshold parametric oscillation, broadband frequency combs and narrow-linewidth laser are demonstrated. Our work demonstrates the feasibility of scalable photonic systems based on foundries. Copyright © 2023, The Authors. All rights reserved.

关键词： Silicon nitride

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Broadband Sheet Parametric Oscillator for x^((2)) Optical Frequency Comb Generation via Cavity Phase Matching

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Chinese physics Letters 2021年第6期38卷 35-39页

作者： Xin Ni Kunpeng Jia Xiaohan Wang Huaying Liu Jian Guo Shu-Wei Huang Baicheng Yao Nicolo Sernicola Zhenlin Wang Xinjie Lv Gang Zhao Zhenda Xie Shi-Ning Zhu National Laboratory of Solid State Microstructures School of Electronic Science and EngineeringSchool of Physicsand College of Engineering and Applied SciencesNanjing UniversityNanjing 210093China Department of Electrical Computerand Energy EngineeringUniversity of Colorado BoulderBoulderCO 80301USA Key Laboratory of Optical Fiber Sensing and Communications(Ministry of Education) University of Electronic Science and Technology of ChinaChengdu 611731China Institute for Optics Information and PhotonicsFriedrich-Alexander-Universitat Erlangen-NürnbergSchloßplatz 4Erlangen 91054Germany

We demonstrate a broadband optical parametric oscillation,using a sheet cavity,via cavity phase-matching.A21.2 THz broad comb-like spectrum is achieved,with a uniform line spacing of 133.0 GHz,despite a relatively large dispersion of 275.4 fs^(2)/mm around 1064 *** 22.6% high slope efficiency,and 14.9 kW peak power handling,this sheet optical parametric oscillator can be further developed for x^((2)) comb.

关键词： cavity parametric oscillator

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