检索结果-内蒙古大学图书馆

Temporal characterization of electron dynamics in attosecond XUV and infrared laser fields

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Guo, Li Jia, Yi Liu, Mingqing Jia, Xinyan Hu, Shilin Lu, Ronghua Han, ShenSheng Chen, Jing Department of Physics Shanghai Normal University Shanghai200234 China Key Laboratory for Quantum Optics Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Quantum Optoelectronics Laboratory Southwest Jiaotong University Chengdu610031 China Institute of Applied Physics and Computational Mathematics P. O. Box 8009 Beijing100088 China Zhuhai519082 China Center for Advanced Material Diagnostic Technology College of Engineering Physics Shenzhen Technology University Shenzhen518118 China

We use a Wigner distribution-like function based on the strong field approximation theory to obtain the time-energy distributions and the ionization time distributions of electrons ionized by an XUV pulse alone and in the presence of an infrared (IR) pulse. In the case of a single XUV pulse, although the overall shape of the ionization time distribution resembles the XUV-envelope, its detail shows dependence on the emission direction of the electron and the carrier-envelope phase of the pulse, which mainly results from the low-energy interference structure. It is further found that the electron from the counter-rotating term plays an important role in the interference. In the case of the two-color pulse, both the time-energy distributions and the ionization time distributions change with varying IR field. Our analysis demonstrates that the IR field not only modifies the final electron kinetic energy but also changes the electron's emission time, which results from the change of the electric field induced by the IR pulse. Moreover, the ionization time distributions of the photoelectrons emitted from atoms with higher ionization energy are also given, which show less impact of the IR field on the electron dynamics. © 2021, CC BY.

关键词： Electrons

Long term study of the blazar S5 0716+714: investigating a turbulent jet at all wavelengths 38

学校读者我要写书评

暂无评论

Long term study of the blazar S5 0716+714: investigating a t...

38th International Cosmic Ray Conference, ICRC 2023

作者： Podobnik, F. Manganaro, M. Jormanainen, J. Lindfors, E. Bonnoli, G. Paoletti, R. Jorstad, S. Kiehlmann, S. Agudo, I. Elsasser, D. Lorey, C. Raiteri, C. Villata, M. Redhead, A.C. Marscher, A. Abe, H. Abe, S. Abhir, J. Acciari, V.A. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bošnjak, Ž. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, R. Carretero-Castrillo, M. Castro-Tirado, A.J. Ceribella, G. Chai, Y. Chilingarian, A. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Grau, R. Green, D. Green, J.G. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Iotov, R. Ishio, K. Jiménez Martínez, I. Kerszberg, D. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. Láinez Lezáun, M. Lamastra, A. Lelas, D. Leone, F. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Università di Siena INFN Pisa Via Roma 56 SienaI-53100 Italy Faculty of Physics University of Rijeka Radmile Matječić 2 Rijeka51000 Croatia Finnish MAGIC Group Finnish Centre for Astronomy with ESO University of Turku TurkuFI-20014 Finland RomeI-00136 Italy Institute of Astrophysics Foundation for Research and Technology-Hellas HeraklionGR-71110 Greece Instituto de Astrofisica de Andalucia-CSIC Glorieta de la Astronomía Granada18008 Spain Department of Physics Otto-Hahn-Str. 4a Dortmund44227 Germany Hans-Haffner-Sternwarte Naturwissenschaftliches Labor für Schüler am FKG Friedrich-Koenig-Gymnasium WürzburgD-97082 Germany INAF Osservatorio Astrofisico di Torino via Osservatorio 20 Pino TorineseI-10025 Italy Caltech The Division of Physics Mathematics and Astronomy 1200 E California Blvd PasadenaCA91125 United States Institute for Astrophysical Research Boston University 725 Commonwealth Avenue BostonMA02215 United States The University of Tokyo Kashiwa Chiba 277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 S

The blazar S5 0716+714 is an intermediate BL Lacertae object remarkable for its variability in many energy bands. It was discovered by MAGIC in the very-high-energy (VHE) gamma-ray range in 2008. Later in 2015 an impressive electric vector polarization angle (EVPA) swing was detected in connection with a multiwavelength flaring event including the VHE gamma-ray band. This generated interest in further studies of the jet of this source and its electromagnetic emission at all wavelengths. Since then, MAGIC has monitored the source in coordination with other observatories and here we present the long-term study using data from 2015 to 2022 in a MWL context. The data set also includes the extraordinary flaring activity of 2017, so far the historical maximum detected for this source in the optical and VHE gamma-ray band. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

A Comparative Analysis of Optimization and Generalization Properties of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Weinan, E. Ma, Chao Wu, Lei Department of Mathematics Princeton University Program in Applied and Computational Mathematics Princeton University Beijing Institute of Big Data Research

A fairly comprehensive analysis is presented for the gradient descent dynamics for training two-layer neural network models in the situation when the parameters in both layers are updated. General initialization schemes as well as general regimes for the network width and training data size are considered. In the over-parametrized regime, it is shown that gradient descent dynamics can achieve zero training loss exponentially fast regardless of the quality of the labels. In addition, it is proved that throughout the training process the functions represented by the neural network model are uniformly close to that of a kernel method. For general values of the network width and training data size, sharp estimates of the generalization error is established for target functions in the appropriate reproducing kernel Hilbert *** Codes 41A99, 49M99 Copyright © 2019, The Authors. All rights reserved.

关键词： Gradient methods

Navigating the challenges in creating complex data systems: a development philosophy

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Dittmer, Sören Roberts, Michael Gilbey, Julian Biguri, Ander Preller, Jacobus Rudd, James H.F. Aston, John A.D. Schönlieb, Carola-Bibiane Selby, Ian Breger, Anna Thorpe, Matthew Weir-McCall, Jonathan R. Gkrania-Klotsas, Effrossyni Korhonen, Anna Jefferson, Emily Langs, Georg Yang, Guang Prosch, Helmut Stanczuk, Jan Tang, Jing Babar, Judith Sánchez, Lorena Escudero Teare, Philip Patel, Mishal Wassin, Marcel Holzer, Markus Walton, Nicholas Lió, Pietro Shadbahr, Tolou Sala, Evis Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom Addenbrooke’s Hospital Cambridge University Hospitals NHS Trust Cambridge United Kingdom Department of Medicine University of Cambridge Cambridge United Kingdom Department of Pure Mathematics and Mathematical Statistics University of Cambridge Cambridge United Kingdom ZeTeM University of Bremen Bremen Germany Department of Radiology University of Cambridge Cambridge United Kingdom Faculty of Mathematics University of Vienna Austria Department of Mathematics University of Manchester Manchester United Kingdom Royal Papworth Hospital Cambridge Royal Papworth Hospital NHS Foundation Trust Cambridge United Kingdom Language Technology Laboratory University of Cambridge Cambridge United Kingdom Population Health and Genomics School of Medicine University of Dundee Dundee United Kingdom Department of Biomedical Imaging and Image-guided Therapy Computational Imaging Research Lab Medical University of Vienna Vienna Austria National Heart and Lung Institute Imperial College London London United Kingdom Research Program in Systems Oncology Faculty of Medicine University of Helsinki Helsinki Finland Data Science & Artificial Intelligence AstraZeneca Cambridge United Kingdom Clinical Pharmacology & Safety Sciences AstraZeneca Cambridge United Kingdom Contextflow GmbH Vienna Austria Institute of Astronomy University of Cambridge Cambridge United Kingdom Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom

In this perspective, we argue that despite the democratization of powerful tools for data science and machine learning over the last decade, developing the code for a trustworthy and effective data science system (DSS) is getting harder. Perverse incentives and a lack of widespread software engineering (SE) skills are among many root causes we identify that naturally give rise to the current systemic crisis in reproducibility of DSSs. We analyze why SE and building large complex systems is, in general, hard. Based on these insights, we identify how SE addresses those difficulties and how we can apply and generalize SE methods to construct DSSs that are fit for purpose. We advocate two key development philosophies, namely that one should incrementally grow – not biphasically plan and build – DSSs, and one should always employ two types of feedback loops during development: one which tests the code’s correctness and another that evaluates the code’s efficacy. Copyright © 2022, The Authors. All rights reserved.

关键词： Software engineering

A Priori Estimates of the Population Risk for Residual Networks

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Weinan, E. Ma, Chao Wang, Qingcan Department of Mathematics Princeton University Program in Applied and Computational Mathematics Princeton University Beijing Institute of Big Data Research

Optimal a priori estimates are derived for the population risk, also known as the generalization error, of a regularized residual network model. An important part of the regularized model is the usage of a new path norm, called the weighted path norm, as the regularization term. The weighted path norm treats the skip connections and the nonlinearities differently so that paths with more nonlinearities are regularized by larger weights. The error estimates are a priori in the sense that the estimates depend only on the target function, not on the parameters obtained in the training process. The estimates are optimal, in a high dimensional setting, in the sense that both the bound for the approximation and estimation errors are comparable to the Monte Carlo error rates. A crucial step in the proof is to establish an optimal bound for the Rademacher complexity of the residual networks. Comparisons are made with existing norm-based generalization error bounds. Copyright © 2019, The Authors. All rights reserved.

关键词： Error analysis

Machine learning from a continuous viewpoint

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Weinan, E. Ma, Chao Wu, Lei Department of Mathematics Princeton University Program in Applied and Computational Mathematics Princeton University Beijing Institute of Big Data Research

We present a continuous formulation of machine learning, as a problem in the calculus of variations and differential-integral equations, very much in the spirit of classical numerical analysis and statistical physics. We demonstrate that conventional machine learning models and algorithms, such as the random feature model, the shallow neural network model and the residual neural network model, can all be recovered as particular discretizations of different continuous formulations. We also present examples of new models, such as the ow-based random feature model, and new algorithms, such as the smoothed particle method and spectral method, that arise naturally from this continuous formulation. We discuss how the issues of generalization error and implicit regularization can be studied under this framework. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Analysis of the gradient descent algorithm for a deep neural network model with skip-connections

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Weinan, E. Ma, Chao Wang, Qingcan Wu, Lei Department of Mathematics Princeton University Program in Applied and Computational Mathematics Princeton University Beijing Institute of Big Data Research

The behavior of the gradient descent (GD) algorithm is analyzed for a deep neural network model with skip-connections. It is proved that in the over-parametrized regime, for a suitable initialization, with high probability GD can find a global minimum exponentially fast. Generalization error estimates along the GD path are also established. As a consequence, it is shown that when the target function is in the reproducing kernel Hilbert space (RKHS) with a kernel defined by the initialization, there exist generalizable earlystopping solutions along the GD path. In addition, it is also shown that the GD path is uniformly close to the functions given by the related random feature model. Consequently, in this \implicit regularization" setting, the deep neural network model deteriorates to a random feature model. Our results hold for neural networks of any width larger than the input dimension. Copyright © 2019, The Authors. All rights reserved.

关键词： Gradient methods

Moosinesq Convection in the Cores of Moosive Stars

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Anders, Evan H. Bauer, Evan B. Jermyn, Adam S. Van Kooten, Samuel J. Brown, Benjamin P. Hester, Eric W. Wilkinson, Mindy Goldberg, Jared A. Varesano, Tania Lecoanet, Daniel CIERA Northwestern University EvanstonIL60201 United States Center for Astrophysics | Harvard & Smithsonian 60 Garden St. CambridgeMA02138 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Southwest Research Institute BoulderCO80302 United States Department Astrophysical and Planetary Sciences LASP University of Colorado BoulderCO80309 United States Department of Mathematics The University of California Los Angeles 520 Portola Plaza CA90024 United States Primum Terrae LLC BoulderCO80302 United States Department of Physics University of California Santa BarbaraCA93106 United States Grenoble Institute of Technology Grenoble France Department of Engineering Sciences and Applied Mathematics Northwestern University EvanstonIL60208 United States

Stars with masses 4 × 1027Mmoose ≈ 1.1Mo have core convection zones during their time on the main sequence. In these moosive stars, convection introduces many uncertainties in stellar modeling. In this Letter, we build upon the Boussinesq approximation to present the first-ever simulations of Moosinesq convection, which captures the complex geometric structure of the convection zones of these stars. These flows are bounded in a manner informed by the majestic terrestrial Alces alces (moose) and could have important consequences for the evolution of these stars. We find that Moosinesq convection results in very interesting flow morphologies and rapid heat transfer, and posit this as a mechanism of biomechanical thermoregulation. Copyright © 2022, The Authors. All rights reserved.

关键词： Uncertainty analysis

Multi-hump Collapsing Solutions in the Nonlinear Schrödinger Problem: Existence, Stability and Dynamics

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Chapman, S. Jon Kavousanakis, Mihalis Charalampidis, Efstathios G. Kevrekidis, Ioannis G. Kevrekidis, Panayotis G. Mathematical Institute University of Oxford AWB ROQ Woodstock Road OxfordOX2 6GG United Kingdom School of Chemical Engineering National Technical University of Athens Athens15780 Greece Department of Mathematics and Statistics Computational Science Research Center San Diego State University San DiegoCA92182-7720 United States Department of Chemical and Biomolecular Engineering Department of Applied Mathematics and Statistics Johns Hopkins University BaltimoreMD21218 United States Department of Mathematics and Statistics University of Massachusetts AmherstMA01003-4515 United States Department of Physics University of Massachusetts AmherstMA01003 United States

In the present work we examine multi-hump solutions of the nonlinear Schrödinger equation in the blowup regime of the one-dimensional model with power law nonlinearity, bearing a suitable exponent of σ > 2. We find that families of such solutions exist for arbitrary pulse numbers, with all of them bifurcating from the critical case of σ = 2. Remarkably, all of them involve "bifurcations from infinity", i.e., the pulses come inward from an infinite distance as the exponent σ increases past the critical point. The position of the pulses is quantified and the stability of the waveforms is also systematically examined in the so-called "co-exploding frame". Both the equilibrium distance between the pulse peaks and the point spectrum eigenvalues associated with the multi-hump configurations are obtained as a function of the blowup rate G theoretically, and these findings are supported by detailed numerical computations. Finally, some prototypical dynamical scenarios are explored, and an outlook towards such multi-hump solutions in higher dimensions is provided. Copyright © 2025, The Authors. All rights reserved.

关键词： Schrodinger equation