2026-07-14 15:01
[PUBDB-2026-02112]
Book
DiMauro, L. F. ; Perrin, H. ; Yelin, S.
Advances in atomic, molecular, and optical physics: volume 74
London : Academic Press, Advances in atomic, molecular, and optical physics 74 , VIII, 241 pages : graphs (2025 ) 2025
Advances in Atomic, Molecular, and Optical Physics, Volume 74 gives an overview on the latest evolutions in atomic, molecular, and optical physics, specifically promoting two important aspects of the field of ultrafast optics and strong fields. In particular, the book consists of a review over high harmonic generation (HHG) from thin-film samples, featuring experimental and theoretical studies of HHG from thin films in comparison to bulk crystals of the same materials and the specific interest in HHG from van der Waals materials and HHG studies at the 2D limit. [...]
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2026-07-14 14:51
[PUBDB-2026-02111]
Book
DiMauro, L. F. ; Perrin, H. ; Yelin, S.
Advances in atomic, molecular, and optical physics: volume 73
London : Academic Press, Advances in atomic, molecular, and optical physics 73 , VII, 74 pages : graphs (2024 ) 2024
The Advances series highlights recent developments in atomic, molecular and optical physics. Readers can learn about recent advances from articles that are comprehensive in nature. [...]
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2026-07-14 14:20
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2026-07-02 10:56
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2026-07-02 10:55
[PUBDB-2026-01978]
Book
Davidov, J.
Vector bundles and connections: an introduction
This textbook offers a self-contained introduction to the theory of connections on vector bundles that is accessible to both advanced undergraduate students and graduate students. Constructions and proofs of key results are presented in detail in order to be easily understandable and instructive, and each chapter concludes with a set of interesting exercises. [...]
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2026-07-02 10:54
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2026-07-02 10:54
[PUBDB-2026-01976]
Book
Wang, X.-S. ; Wang, C.
Machine learning in data processing
Cham : Springer Nature Switzerland, Forum for Interdisciplinary Mathematics XIII, 119 pages : graphs (2026 ) [10.1007/978-3-032-20855-2 ] 2026
Machine learning has become a cornerstone of modern data-driven science and technology. For mathematics students and researchers, understanding the mathematical foundations behind machine learning is essential, even if they never work directly with real-world datasets. [...]
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2026-07-02 10:53
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