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  • Lingua: Inglese

    Editore: Springer Nature Switzerland AG, Cham, 2026

    3032176344 / 9783032176349

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    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    Condizione: Nuovo

    EUR 107,21

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    Spedito in U.S.A.

    Quantità: 1 disponibili

    Hardcover. Condizione: new. Hardcover. This second edition of the textbook Introduction to Tensor Network Methods contains more advanced and technical parts as new topics related to tensor network algorithms that have been developed in the last few years. The reader finds new chapters dedicated to tree tensor networks for high-dimensional systems as applications to lattice gauge theory. The implementation of tensor networks for machine learning is also presented in detail.This textbook gives an in-depth overview on the numerical simulation technique of tensor networks (TNs) with hands-on technical descriptions, work exercises and computation results. TNs have originally been developed for solving the quantum many-body problem and simulating quantum systems on a classical computer. However, as a mathematical tool, TNs have emerged as powerful theoretical and numerical versatile tools to attack more generally hard mathematical problems. In particular, their range application has expanded to combinatorial optimization and even as an alternative tool for machine learning in the field of artificial intelligence. This textbook introduces the reader to the field, describing the main principles and core mathematical concepts in the light of its application in quantum physics and, along the way, touches on the application of TNs to problems from various fields, ranging from low-energy to high-energy physics up to medical physics and machine learning.It is designed for graduate courses in computational physics, where a student learns how to write a tensor network program and can begin to explore the physics of many-body quantum systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Lingua: Inglese

    Editore: Springer, 2026

    3032176344 / 9783032176349

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    Da: California Books, Miami, FL, U.S.A.California Books

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    Condizione: Nuovo

    EUR 115,16

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    Condizione: New.

  • Lingua: Inglese

    Editore: Springer, 2026

    3032176344 / 9783032176349

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    Da: Books Puddle, Woodside, NY, U.S.A.Books Puddle

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    Condizione: Nuovo

    EUR 152,68

    EUR 3,49 spedizione 
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    Quantità: 4 disponibili

    Condizione: New.

  • Lingua: Inglese

    Editore: Springer Nature Switzerland Ag, 2026

    3032176344 / 9783032176349

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Condizione: Nuovo

    EUR 143,68

    EUR 14,57 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 2 disponibili

    Hardcover. Condizione: Brand New. second edition 2026 edition. 357 pages. 6.14x0.81x9.21 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2026

    3032176344 / 9783032176349

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 137,14

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibili

    Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This second edition of the textbook Introduction to Tensor Network Methods contains more advanced and technical parts as new topics related to tensor network algorithms that have been developed in the last few years. The reader finds new chapters dedicated to tree tensor networks for high-dimensional systems as applications to lattice gauge theory. The implementation of tensor networks for machine learning is also presented in detail.This textbook gives an in-depth overview on the numerical simulation technique of tensor networks (TNs) with hands-on technical descriptions, work exercises and computation results. TNs have originally been developed for solving the quantum many-body problem and simulating quantum systems on a classical computer. However, as a mathematical tool, TNs have emerged as powerful theoretical and numerical versatile tools to attack more generally hard mathematical problems. In particular, their range application has expanded to combinatorial optimization and even as an alternative tool for machine learning in the field of artificial intelligence. This textbook introduces the reader to the field, describing the main principles and core mathematical concepts in the light of its application in quantum physics and, along the way, touches on the application of TNs to problems from various fields, ranging from low-energy to high-energy physics up to medical physics and machine learning.

  • Lingua: Inglese

    Editore: Springer Nature Switzerland AG Aug 2026, 2026

    3032176344 / 9783032176349

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Condizione: Nuovo

    EUR 96,29

    EUR 23,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This second edition of the textbook Introduction to Tensor Network Methods contains more advanced and technical parts as new topics related to tensor network algorithms that have been developed in the last few years. The reader finds new chapters dedicated to tree tensor networks for high-dimensional systems as applications to lattice gauge theory. The implementation of tensor networks for machine learning is also presented in detail.This textbook gives an in-depth overview on the numerical simulation technique of tensor networks (TNs) with hands-on technical descriptions, work exercises and computation results. TNs have originally been developed for solving the quantum many-body problem and simulating quantum systems on a classical computer. However, as a mathematical tool, TNs have emerged as powerful theoretical and numerical versatile tools to attack more generally hard mathematical problems. In particular, their range application has expanded to combinatorial optimization and even as an alternative tool for machine learning in the field of artificial intelligence. This textbook introduces the reader to the field, describing the main principles and core mathematical concepts in the light of its application in quantum physics and, along the way, touches on the application of TNs to problems from various fields, ranging from low-energy to high-energy physics up to medical physics and machine learning. 331 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer Verlag GmbH, 2026

    3032176344 / 9783032176349

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    Da: moluna, Greven, Germaniamoluna

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    Condizione: Nuovo

    EUR 81,44

    EUR 48,99 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

  • Lingua: Inglese

    Editore: Springer Nature Switzerland AG, Cham, 2026

    3032176344 / 9783032176349

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    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Condizione: Nuovo

    EUR 112,24

    EUR 43,13 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibili

    Hardcover. Condizione: new. Hardcover. This second edition of the textbook Introduction to Tensor Network Methods contains more advanced and technical parts as new topics related to tensor network algorithms that have been developed in the last few years. The reader finds new chapters dedicated to tree tensor networks for high-dimensional systems as applications to lattice gauge theory. The implementation of tensor networks for machine learning is also presented in detail.This textbook gives an in-depth overview on the numerical simulation technique of tensor networks (TNs) with hands-on technical descriptions, work exercises and computation results. TNs have originally been developed for solving the quantum many-body problem and simulating quantum systems on a classical computer. However, as a mathematical tool, TNs have emerged as powerful theoretical and numerical versatile tools to attack more generally hard mathematical problems. In particular, their range application has expanded to combinatorial optimization and even as an alternative tool for machine learning in the field of artificial intelligence. This textbook introduces the reader to the field, describing the main principles and core mathematical concepts in the light of its application in quantum physics and, along the way, touches on the application of TNs to problems from various fields, ranging from low-energy to high-energy physics up to medical physics and machine learning.It is designed for graduate courses in computational physics, where a student learns how to write a tensor network program and can begin to explore the physics of many-body quantum systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Lingua: Inglese

    Editore: Palgrave Macmillan Jul 2026, 2026

    3032176344 / 9783032176349

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 96,29

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibili

    Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This second edition of the textbook Introduction to Tensor Network Methods contains more advanced and technical parts as new topics related to tensor network algorithms that have been developed in the last few years. The reader finds new chapters dedicated to tree tensor networks for high-dimensional systems as applications to lattice gauge theory. The implementation of tensor networks for machine learning is also presented in detail.This textbook gives an in-depth overview on the numerical simulation technique of tensor networks (TNs) with hands-on technical descriptions, work exercises and computation results. TNs have originally been developed for solving the quantum many-body problem and simulating quantum systems on a classical computer. However, as a mathematical tool, TNs have emerged as powerful theoretical and numerical versatile tools to attack more generally hard mathematical problems. In particular, their range application has expanded to combinatorial optimization and even as an alternative tool for machine learning in the field of artificial intelligence. This textbook introduces the reader to the field, describing the main principles and core mathematical concepts in the light of its application in quantum physics and, along the way, touches on the application of TNs to problems from various fields, ranging from low-energy to high-energy physics up to medical physics and machine learning.It is designed for graduate courses in computational physics, where a student learns how to write a tensor network program and can begin to explore the physics of many-body quantum systems.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 360 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2026

    3032176344 / 9783032176349

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    Condizione: Nuovo

    EUR 156,84

    EUR 7,58 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 4 disponibili

    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: Springer, 2026

    3032176344 / 9783032176349

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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    Condizione: Nuovo

    EUR 156,70

    EUR 9,95 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 4 disponibili

    Condizione: New. PRINT ON DEMAND.

  • Lingua: Inglese

    Editore: Springer Nature Switzerland AG, Cham, 2026

    3032176344 / 9783032176349

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    Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Condizione: Nuovo

    EUR 142,13

    EUR 32,32 spedizione 
    Spedito da Australia a U.S.A.

    Quantità: 1 disponibili

    Hardcover. Condizione: new. Hardcover. This second edition of the textbook Introduction to Tensor Network Methods contains more advanced and technical parts as new topics related to tensor network algorithms that have been developed in the last few years. The reader finds new chapters dedicated to tree tensor networks for high-dimensional systems as applications to lattice gauge theory. The implementation of tensor networks for machine learning is also presented in detail.This textbook gives an in-depth overview on the numerical simulation technique of tensor networks (TNs) with hands-on technical descriptions, work exercises and computation results. TNs have originally been developed for solving the quantum many-body problem and simulating quantum systems on a classical computer. However, as a mathematical tool, TNs have emerged as powerful theoretical and numerical versatile tools to attack more generally hard mathematical problems. In particular, their range application has expanded to combinatorial optimization and even as an alternative tool for machine learning in the field of artificial intelligence. This textbook introduces the reader to the field, describing the main principles and core mathematical concepts in the light of its application in quantum physics and, along the way, touches on the application of TNs to problems from various fields, ranging from low-energy to high-energy physics up to medical physics and machine learning.It is designed for graduate courses in computational physics, where a student learns how to write a tensor network program and can begin to explore the physics of many-body quantum systems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.