.png){kind=icon}
.png){kind=icon}
Return
Fixed-point quantum continuous search algorithm with optimal query complexity
.png){kind=icon}
PRE
AI
DOI：10.1007/s11433-024-2629-1.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Continuous search problems (CSPs), which involve finding solutions within a continuous domain, frequently arise in fields such as optimization, physics, and engineering. Unlike discrete search problems, CSPs require navigating an uncountably infinite space, presenting unique computational challenges. In this work, we propose a fixed-point quantum search algorithm that leverages continuous variables to address these challenges, achieving a quadratic speedup. Inspired by the discrete search results, we manage to establish a lower bound on the query complexity of arbitrary quantum search for CSPs, demonstrating the optimality of our approach. In addition, we demonstrate how to design the internal structure of the quantum search oracle for specific problems. Furthermore, we develop a general framework to apply this algorithm to a range of problem types, including optimization and eigenvalue problems involving continuous variables.
Keywords:
quantum search
quantum algorithm
quantum computation
optimization
spectral problems
Journal
S
IF:
7.5
Papers:
3.9K
Citations:
7.4K
Organization
No organization information available