Quantum Approximation Algorithms

Quantum Approximation Algorithms is a class of quantum algorithms designed to efficiently compute approximate solutions to computationally hard optimization problems, distinguished from classical approximation algorithms by leveraging quantum superposition, entanglement, and interference to achieve potential speedups in convergence to near-optimal solutions.

322

Publications

23.1K

Citations

702

Authors

365

Institutions

Publications per year

2017–2026

175

Authors

702

  1. RS
    Ruslan Shaydulin

    Argonne National Laboratory, United States

    7 publications · 323 citations

    7

    h-index

  2. EF
    Edward Farhi

    Massachusetts Institute of Technology, United States

    6 publications · 2.4K citations

    6

    h-index

  3. PW
    Paweł Wocjan

    University of Central Florida, United States

    6 publications · 288 citations

    6

    h-index

  4. RD
    Ronald de Wolf

    Centrum Wiskunde & Informatica, Netherlands

    5 publications · 142 citations

    5

    h-index

  5. IK
    Iordanis Kerenidis

    Université Paris Cité, France

    5 publications · 473 citations

    5

    h-index

1–5 of 702

Venues

  1. arXiv (Cornell University)

    Repository · 45 publications · 3.4K citations

    23

    h-index

  2. Physical Review Letters

    PRL · 18 publications · 6K citations

    17

    h-index

  3. Quantum

    15 publications · 924 citations

    15

    h-index

  4. Physical review. A/Physical review, A

    PRA · 17 publications · 835 citations

    14

    h-index

  5. Physical Review A

    PRA · 12 publications · 509 citations

    12

    h-index

1–5