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  • Cited by 13
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    • Publisher:
      Cambridge University Press
      Publication date:
      May 2025
      April 2025
      ISBN:
      9781009639651
      9781009639644
      9781009639668
      Creative Commons:
      Creative Common License - CC Creative Common License - BY Creative Common License - NC Creative Common License - ND
      This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY-NC-ND 4.0.
      https://creativecommons.org/creativelicenses
      Dimensions:
      (229 x 152 mm)
      Weight & Pages:
      0.809kg, 433 Pages
      Dimensions:
      (229 x 152 mm)
      Weight & Pages:
      0.64kg, 433 Pages
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    Book description

    The 1994 discovery of Shor's quantum algorithm for integer factorization—an important practical problem in the area of cryptography—demonstrated quantum computing's potential for real-world impact. Since then, researchers have worked intensively to expand the list of practical problems that quantum algorithms can solve effectively. This book surveys the fruits of this effort, covering proposed quantum algorithms for concrete problems in many application areas, including quantum chemistry, optimization, finance, and machine learning. For each quantum algorithm considered, the book clearly states the problem being solved and the full computational complexity of the procedure, making sure to account for the contribution from all the underlying primitive ingredients. Separately, the book provides a detailed, independent summary of the most common algorithmic primitives. It has a modular, encyclopedic format to facilitate navigation of the material and to provide a quick reference for designers of quantum algorithms and quantum computing researchers.

    Reviews

    ‘This timely and forward-looking survey captures the state-of-the-art in quantum computing. Focusing on cutting-edge applications and recent advances in quantum primitives, it serves as an essential resource for understanding the rapidly evolving role of quantum algorithms in scientific discovery.’

    Lin Lin - University of California, Berkeley

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    Contents

    Full book PDF

    Page 1 of 2


    • Frontmatter
      pp i-iv
    • Contents
      pp v-viii
    • Preface
      pp ix-xiv
    • Part I - Areas of application
      pp 1-3
    • 1 - Condensed matter physics
      pp 4-28
    • 2 - Quantum chemistry
      pp 29-50
    • 3 - Nuclear and particle physics
      pp 51-61
    • 4 - Combinatorial optimization
      pp 62-77
    • 5 - Continuous optimization
      pp 78-97
    • 6 - Breaking cryptosystems
      pp 98-110
    • 7 - Solving differential equations
      pp 111-129
    • 8 - Finance
      pp 130-147
    • 9 - Machine learning with classical data
      pp 148-184
    • Part II - Quantum algorithmic primitives
      pp 185-187
    • 10 - Quantum linear algebra
      pp 188-209
    • 11 - Hamiltonian simulation
      pp 210-224
    • 12 - Quantum Fourier transform
      pp 225-227
    • 13 - Quantum phase estimation
      pp 228-234
    • 14 - Amplitude amplification and estimation
      pp 235-242
    • 15 - Gibbs sampling
      pp 243-249
    • 16 - Quantum adiabatic algorithm
      pp 250-254
    • 17 - Loading classical data
      pp 255-269
    • 18 - Quantum linear system solvers
      pp 270-275
    • 19 - Quantum gradient estimation
      pp 276-280
    • 20 - Variational quantum algorithms
      pp 281-285
    • 21 - Quantum tomography
      pp 286-290
    • 22 - Quantum interior point methods
      pp 291-298
    • 23 - Multiplicative weights update method
      pp 299-304
    • 24 - Approximate tensor network contraction
      pp 305-310
    • Part III - Fault-tolerant quantum computing
      pp 311-313

    Page 1 of 2


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