English

Anderson localization casts clouds over adiabatic quantum optimization

Quantum Physics 2010-12-13 v1 Mesoscale and Nanoscale Physics Computational Complexity

Abstract

Understanding NP-complete problems is a central topic in computer science. This is why adiabatic quantum optimization has attracted so much attention, as it provided a new approach to tackle NP-complete problems using a quantum computer. The efficiency of this approach is limited by small spectral gaps between the ground and excited states of the quantum computer's Hamiltonian. We show that the statistics of the gaps can be analyzed in a novel way, borrowed from the study of quantum disordered systems in statistical mechanics. It turns out that due to a phenomenon similar to Anderson localization, exponentially small gaps appear close to the end of the adiabatic algorithm for large random instances of NP-complete problems. This implies that unfortunately, adiabatic quantum optimization fails: the system gets trapped in one of the numerous local minima.

Keywords

Cite

@article{arxiv.0912.0746,
  title  = {Anderson localization casts clouds over adiabatic quantum optimization},
  author = {Boris Altshuler and Hari Krovi and Jeremie Roland},
  journal= {arXiv preprint arXiv:0912.0746},
  year   = {2010}
}

Comments

14 pages, 4 figures

R2 v1 2026-06-21T14:19:25.964Z