We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Quantum-Inspired Evolutionary Algorithms on IBM Quantum Experience.
- Authors
Rubio, Yoshio; Olvera, Cynthia; Montiel, Oscar
- Abstract
Quantum computing has been proposed as a possible accelerator for a myriad of complex computational problems. From this, quantum-inspired methodologies have emerged as methods that take the principles and restrictions of quantum theory to solve classical problems on classical computers. Quantum-inspired methodologies have proven advantageous in solving optimization problems and in learning over traditional nature-inspired methods. Since these algorithms operate on classical computers, the next unanswered question is important and valid: Can quantum-inspired evolutionary algorithms take advantage of quantum computers? The present work attempts to shed some light on this question, implementing quantuminspired evolutionary algorithms for numerical optimization on quantum hardware. We present statistical metrics of their performance on the IBM Q quantum computer and compared them to their execution on a GPU-based quantum simulator, and the IBM quantum simulator.
- Publication
Engineering Letters, 2021, Vol 29, Issue 4, p1573
- ISSN
1816-093X
- Publication type
Academic Journal