Quantum Information Processing

, Volume 10, Issue 1, pp 33–52

A study of heuristic guesses for adiabatic quantum computation


  • Alejandro Perdomo-Ortiz
    • Department of Chemistry and Chemical BiologyHarvard University
  • Salvador E. Venegas-Andraca
    • Quantum Information Processing GroupTecnológico de Monterrey Campus Estado de México
    • Department of Chemistry and Chemical BiologyHarvard University

DOI: 10.1007/s11128-010-0168-z

Cite this article as:
Perdomo-Ortiz, A., Venegas-Andraca, S.E. & Aspuru-Guzik, A. Quantum Inf Process (2011) 10: 33. doi:10.1007/s11128-010-0168-z


Adiabatic quantum computation (AQC) is a universal model for quantum computation which seeks to transform the initial ground state of a quantum system into a final ground state encoding the answer to a computational problem. AQC initial Hamiltonians conventionally have a uniform superposition as ground state. We diverge from this practice by introducing a simple form of heuristics: the ability to start the quantum evolution with a state which is a guess to the solution of the problem. With this goal in mind, we explain the viability of this approach and the needed modifications to the conventional AQC (CAQC) algorithm. By performing a numerical study on hard-to-satisfy 6 and 7 bit random instances of the satisfiability problem (3-SAT), we show how this heuristic approach is possible and we identify that the performance of the particular algorithm proposed is largely determined by the Hamming distance of the chosen initial guess state with respect to the solution. Besides the possibility of introducing educated guesses as initial states, the new strategy allows for the possibility of restarting a failed adiabatic process from the measured excited state as opposed to restarting from the full superposition of states as in CAQC. The outcome of the measurement can be used as a more refined guess state to restart the adiabatic evolution. This concatenated restart process is another heuristic that the CAQC strategy cannot capture.


Heuristic algorithmsAdiabatic quantum computationAdiabatic preparationQuantum algorithms

Copyright information

© Springer Science+Business Media, LLC 2010