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Doping-driven electronic and lattice dynamics in the phase-change material vanadium dioxide

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Physical Review B 2020年第11期102卷 115148-115148页

作者： Kannatassen Appavoo Joyeeta Nag Bin Wang Weidong Luo Gerd Duscher E. Andrew Payzant Matthew Y. Sfeir Sokrates T. Pantelides Richard F. Haglund, Jr. Department of Physics University of Alabama at Birmingham Birmingham Alabama 35294 USA Department of Physics and Astronomy Vanderbilt University Nashville Tennessee 37235 USA School of Chemical Biological and Materials Engineering University of Oklahoma Norman Oklahoma 73019 USA Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Key Laboratory of Artificial Structures and Quantum Control School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Department of Materials Science and Engineering University of Tennessee Knoxville Tennessee 37996 USA Center for Functional Nanomaterials Brookhaven National Laboratory Upton New York 11973 USA Department of Electrical Engineering and Computer Science Vanderbilt University Nashville Tennessee 37235 USA

Doping is generally understood as a strategy for including additional positive or negative charge carriers in a semiconductor, thereby tuning the Fermi level and changing its electronic properties in the equilibrium limit. However, because dopants also couple to all of the microscopic degrees of freedom in the host, they may also alter the nonequilibrium dynamical properties of the parent material, especially at large dopant concentrations. Here, we show how substitutional doping by tungsten at the 1 at. % level modifies the complex electronic and lattice dynamics of the phase-change material vanadium dioxide. Using femtosecond broadband spectroscopy, we compare dynamics in epitaxial thin films of pristine and tungsten-doped VO2 over the broadest wavelength and temporal ranges yet reported. We demonstrate that coupling of tungsten atoms to the host lattice modifies the early electron-phonon dynamics on a femtosecond timescale, altering in a counterintuitive way the ps-to-ns optical signatures of the phase transition. Density functional theory correctly captures the enthalpy difference between pristine and W-doped VO2 and shows how the dopant softens critical V-V phonon modes while introducing new phononic modes due to W-V bonds. While substitutional doping provides a powerful method to control the switching threshold and contrast of phase-change materials, determining how the dopant dynamically changes the broadband optical response is equally important for optoelectronics.

关键词： Electronic structure Lattice dynamics Phase transitions Phonons Photonics Functional materials Thin films Band structure methods Electron microscopy Epitaxy Femtosecond laser spectroscopy Film deposition First-principles calculations Laser techniques Monte Carlo methods Scanning electron microscopy

Quantum neural networks with data re-uploading for urban traffic time series forecasting

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Scientific Reports 2025年第1期15卷 1-21页

作者： Schetakis, Nikolaos Bonfini, Paolo Alisoltani, Negin Blazakis, Konstantinos Tsintzos, Symeon I. Askitopoulos, Alexis Aghamalyan, Davit Fafoutellis, Panagiotis Vlahogianni, Eleni I. Computational Mechanics and Optimization Laboratory School of Production Engineering and Management Technical University of Crete Chania 73100 Greece Quantum Innovation Pc Chania 73100 Greece Alma-Sistemi Srl Guidonia 00012 Italy Univ Gustave Eiffel COSYS GRETTIA Paris F-77454 France Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion 71410 Greece QUBITECH Pc Athens 15231 Greece Institute of High Performance Computing A*STAR (Agency for Science Technology and Research) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Department of Transportation Planning and Engineering School of Civil Engineering National Technical University of Athens 5 Iroon Polytechniou Str Zografou Campus Athens 157 73 Greece

Accurate traffic forecasting plays a crucial role in modern Intelligent Transportation Systems (ITS), as it enables real-time traffic flow management, reduces congestion, and improves the overall efficiency of urban transportation networks. With the rise of Quantum Machine Learning (QML), it has emerged a new paradigm possessing the potential to enhance predictive capabilities beyond what classical machine learning models can achieve. In the present work we pursue a heuristic approach to explore the potential of QML, and focus on a specific transport issue. In particular, as a case study we investigate a traffic forecast task for a major urban area in Athens (Greece), for which we possess high-resolution data. In this endeavor we explore the application of Quantum Neural Networks (QNN), and, notably, we present the first application of quantum data re-uploading in the context of transport forecasting. This technique allows quantum models to better capture complex patterns, such as traffic dynamics, by repeatedly encoding classical data into a quantum state. Aside from providing a prediction model, we spend considerable effort in comparing the performance of our hybrid quantum-classical neural networks with classical deep learning approaches. We observe that, in fully connected network settings, hybrid quantum-classical models consistently underperform, with median scores approximately 10% worse than their purely classical counterparts across different configurations. In contrast, recursive architectures with data re-uploading show the opposite trend: hybrid models achieved up to 5% better median scores under comparable complexity settings. Additionally, these hybrid models converged in fewer training epochs, indicating improved training efficiency. Our results show that hybrid models achieve competitive accuracy with state-of-the-art classical methods, especially when the number of qubits and re-uploading blocks is increased. While the classical models demonstrate l

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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

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arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

Removal notice to "VitSeg: Weakly supervised vitiligo segmentation in skin image" [Comput. Med. Imag. Graph. 85 (2020) 101779]

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computerized medical imaging and graphics : the official journal of the computerized Medical Imaging Society 2021年 91卷 101954页

作者： Zhangxing Bian Siyu Xia Chao Xia Ming Shao Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA. Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China. School of Electronics Information and Electrical Engineering ShangHai Jiao Tong University Shanghai China. Dept. of Computer and Information Science University of Massachusetts Dartmouth Dartmouth MA USA.

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://***/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Authors and Editor-in-Chief because complete consent was not obtained by the authors in accordance with journal policy prior to publication. The authors and the journal sincerely apologize for this oversight.

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Outcomes from a Workshop on a National Center for Quantum Education

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arXiv 2024年

作者： Barnes, Edwin Bennett, Michael B. Boltasseva, Alexandra Borish, Victoria Brown, Bennett Carr, Lincoln D. Ceballos, Russell R. Dukes, Faith Easton, Emily W. Economou, Sophia E. Edwards, E.E. Finkelstein, Noah D. Fracchiolla, C. Franklin, Diana Freericks, J.K. Goss, Valerie Hannum, Mark Holincheck, Nancy Kelly, Angela M. Lanes, Olivia Lewandowski, H.J. Matsler, Karen Jo Mercurio, Emily Montaño, Inès Murdock, Maajida Peltz, Kiera Perron, Justin K. Richardson, Christopher J.K. Rosenberg, Jessica L. Ross, Richard S. Ryu, Minjung Samuel, Raymond E. Schrode, Nicole Schwamberger, Susan Searles, Thomas A. Singh, Chandralekha Tingle, Alexandra Zwickl, Benjamin M. Department of Physics Virginia Tech Center for Quantum Information Science and Engineering Virginia Tech 850 West Campus Drive BlacksburgVA24061 United States Q-SEnSE NSF QLCI University of Colorado 440 UCB BoulderCO80301 United States Elmore Family School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University 610 Purdue Mall West LafayetteIN47907 United States Quantum Science Center A National Quantum Information Science Research Center of The U.S. Department of Energy Oak Ridge National Laboratory 1 Bethel Valley Road Oak RidgeTN37830 United States JILA National Institute of Standards and Technology the University of Colorado BoulderCO80309 United States Department of Physics University of Colorado 390 UCB BoulderCO80309 United States QuSTEAM 510 Ronalds St. Iowa CityIA52245 United States Quantum Engineering Program Department of Physics Colorado School of Mines 1523 Illinois St. GoldenCO80401 United States QuSTEAM Non-Profit Wilbur Wright College City Colleges of Chicago 4300 N Narragansett Ave ChicagoIL60634 United States Government and Community Relations Office - K-12 Programs Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA United States Chicago Quantum Exchange 5235 S. Harper Court ChicagoIL60615 United States Department of Physics Virginia Tech 850 West Campus Drive BlacksburgVA24060 United States Department of Electrical and Computer Engineering Duke Quantum Center Duke University Duke University 130 Hudson Hall DurhamNC27708 United States American Physical Society 555 12th St. NW WashingtonDC20004 United States Computer Science University of Chicago 5730 S. Ellis Ave. ChicagoIL60637 United States Department of Physics Georgetown University 552 Reiss Science Building WashingtonDC20057 United States Chemistry Physics and Engineering Studies Chicago State University 9501 S. King Drive WSC 309 ChicagoIL606

In response to numerous programs seeking to advance quantum education and workforce development in the United States, experts from academia, industry, government, and professional societies convened for a National science Foundation-sponsored workshop in February 2024 to explore the benefits and challenges of establishing a national center for quantum education. Broadly, such a center would foster collaboration and build the infrastructure required to develop a diverse and quantum-ready workforce. The workshop discussions centered around how a center could uniquely address gaps in public, K-12, and undergraduate quantum information science and engineering (QISE) education. Specifically, the community identified activities that, through a center, could lead to an increase in student awareness of quantum careers, boost the number of educators trained in quantum-related subjects, strengthen pathways into quantum careers, enhance the understanding of the U.S. quantum workforce, and elevate public engagement with QISE. Core proposed activities for the center include professional development for educators, coordinated curriculum development and curation, expanded access to educational laboratory equipment, robust evaluation and assessment practices, network building, and enhanced public engagement with quantum science. © 2024, CC BY.

关键词： Students

Distinguishing two-component anomalous Hall effect from topological Hall effect

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arXiv 2021年

作者： Tai, Lixuan Dai, Bingqian Li, Jie Huang, Hanshen Chong, Su Kong Wong, Kin Zhang, Huairuo Zhang, Peng Deng, Peng Eckberg, Christopher Qiu, Gang He, Haoran Wu, Di Xu, Shijie Davydov, Albert V. Wu, Ruqian Wang, Kang L. Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Physics and Astronomy University of California IrvineCA92697 United States Theiss Research Inc. La Jolla CA92037 United States GaithersburgMD20899 United States Fibertek Inc. HerndonVA20171 United States US Army Research Laboratory Adelphi MD20783 United States US Army Research Laboratory Playa Vista CA90094 United States Shanghai Key Laboratory of Special Artificial Microstructure Pohl Institute of Solid State Physics School of Physics Science and Engineering Tongji University Shanghai200092 China

In transport, the topological Hall effect (THE) presents itself as nonmonotonic features (or humps and dips) in the Hall signal and is widely interpreted as a sign of chiral spin textures, like magnetic skyrmions. However, when anomalous Hall effect (AHE) is also present, the co-existence of two AHEs could give rise to similar artifacts, making it difficult to distinguish between genuine THE with AHE and two-component AHE. Here we confirm genuine THE with AHE by means of transport and magneto-optical Kerr effect (MOKE) microscopy, in which magnetic skyrmions are directly observed, and find that genuine THE occurs in the transition region of the AHE. In sharp contrast, the artifact "THE", or two-component AHE occurs well beyond the saturation of the "AHE component" (under the false assumption of THE+AHE). Furthermore, we distinguish artifact "THE" from genuine THE by three methods: 1. Minor loops, 2. Temperature dependence, 3. Gate dependence. Minor loops of genuine THE with AHE are always within the full loop, while minor loops of the artifact "THE" may reveal a single loop that cannot fit into the "AHE component". Besides, the temperature or gate dependence of the artifact "THE" may also be accompanied by a polarity change of the "AHE component", as the non-monotonic features vanish, while the temperature dependence of genuine THE with AHE reveals no such change. Our work may help future researchers to exercise cautions and use these methods to examine carefully in order to ascertain genuine THE. Copyright © 2021, The Authors. All rights reserved.

关键词： Temperature distribution

Towards cardiac intervention assistance: hardware-aware neural architecture exploration for real-time 3D cardiac cine mri segmentation

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arXiv 2020年

作者： Zeng, Dewen Jiang, Weiwen Wang, Tianchen Xu, Xiaowei Yuan, Haiyun Huang, Meiping Zhuang, Jian Hu, Jingtong Shi, Yiyu Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States Guangdong Cardiovascular Institute Guangdong Provincial Key Laboratory of South China Structural Heart Disease Guangdong Provincial People’s Hospital Guangzhou510000 China Department of Cardiology Boston Children’s Hospital Harvard Medical School BostonMA02115 United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States

Real-time cardiac magnetic resonance imaging (MRI) plays an increasingly important role in guiding various cardiac interventions. In order to provide better visual assistance, the cine MRI frames need to be segmented on-the-fly to avoid noticeable visual lag. In addition, considering reliability and patient data privacy, the computation is preferably done on local hardware. State-of-the-art MRI segmentation methods mostly focus on accuracy only, and can hardly be adopted for real-time application or on local hardware. In this work, we present the first hardware-aware multi-scale neural architecture search (NAS) framework for real-time 3D cardiac cine MRI segmentation. The proposed framework incorporates a latency regularization term into the loss function to handle real-time constraints, with the consideration of underlying hardware. In addition, the formulation is fully differentiable with respect to the architecture parameters, so that stochastic gradient descent (SGD) can be used for optimization to reduce the computation cost while maintaining optimization quality. Experimental results on ACDC MICCAI 2017 dataset demonstrate that our hardware-aware multi-scale NAS framework can reduce the latency by up to 3.5× and satisfy the real-time constraints, while still achieving competitive segmentation accuracy, compared with the state-of-the-art NAS segmentation framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

Real-time pixel-level polarization modulation using polarized-spatial light modulator based on phase vectorization

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arXiv 2020年

作者： Weng, Xiaoyu Liu, Liwei Sui, Guorong Song, Qiang Dong, Xiangmei Gao, Xiumin Qu, Junle Zhuang, Songlin Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Engineering Research Center of Optical Instrument and System Ministry of Education Shanghai Key Lab of Modern Optical System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology 516 Jungong Road Shanghai200093 China

Vector polarization induced by the change of scalar phase has been far beyond our understanding about the relationship between polarization and phase in classical optics due to the entanglement of inherent polarized modes of light beam. To overcome this limitation, we establish this miraculous relationship by the principle of phase vectorization that can transform three particular phases into linear, circular and elliptical polarization, respectively. Polarized-spatial light modulator based on the principle of phase vectorization can therefore be realized using a phase-only spatial light modulator, which not only enables pixel-level polarization manipulation of light beam in a real-time dynamic way, but also retains complete phase control simultaneously. This work demonstrates the fundamental phase-to-polarization link and declares the creation of polarized-spatial light modulator, which will facilitate extensive developments in optics and pave ways for the era of vector optics. Copyright © 2020, The Authors. All rights reserved.

关键词： Light modulators

Erratum: “Induced out-of-plane piezoelectricity and giant Rashba spin splitting in Janus WSiZ3H (Z = N, P, As) monolayers toward next-generation electronic devices” [J. Appl. Phys. 135, 074301 (2024)]

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Journal of Applied Physics 2024年第10期135卷

作者： Tuan V. Vu Bui D. Hoi A. I. Kartamyshev Nguyen N. Hieu Laboratory for Computational Physics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City 70000 Vietnam Faculty of Mechanical - Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City 70000 Vietnam Department of Physics University of Education Hue University Hue 530000 Vietnam Institute of Research and Development Duy Tan University Da Nang 550000 Vietnam Faculty of Natural Sciences Duy Tan University Da Nang 550000 Vietnam

The authors regret that one of the affiliations (affiliation 2) was incorrectly shown in the original manuscript. The corrected list of affiliations is as shown

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