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- Many-Sorted Algebras for Deep Learning and Quantum Technology

Charles R. Giardina
Many-Sorted Algebras for Deep Learning and Quantum Technology
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ISBN: 9780443136979
Autorius : Charles R. Giardina
Leidimo metai: 2024
Leidėjas: Morgan Kaufmann
Leidinio kalba: Anglų
Formatas: Minkšti viršeliai
Formatas: 9.21×7.5
Autorius : Charles R. Giardina
Leidimo metai: 2024
Leidėjas: Morgan Kaufmann
Leidinio kalba: Anglų
Formatas: Minkšti viršeliai
Formatas: 9.21×7.5
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<i>Many-Sorted Algebras for Deep Learning and Quantum Technology</i> presents a precise and rigorous<br>description of basic concepts in quantum technologies and how they relate to deep learning and quantum theory. Current merging of quantum theory and deep learning techniques provides the need for a source that gives readers insights into the algebraic underpinnings of these disciplines. Although analytical, topological, probabilistic, as well as geometrical concepts are employed in many of these areas, algebra exhibits the principal thread; hence, this thread is exposed using many-sorted algebras. This book includes hundreds of well-designed examples that illustrate the intriguing concepts in quantum systems. Along with these examples are numerous visual displays. In particular, the polyadic graph shows the types or sorts of objects used in quantum or deep learning. It also illustrates all the inter and intra-sort operations needed in describing algebras. In brief, it provides the closure conditions. Throughout the book, all laws or equational identities needed in specifying an algebraic structure are precisely described.
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