Accelerating Grover Adaptive Search: Qubit and Gate Count Reduction Strategies With Higher Order Formulations
Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. In this article, we propose higher order binary formulations that can simultaneously reduce the numbers of qubits and gates required for GAS. Specifically, we consider two novel stra...
Saved in:
Main Authors: | Yuki Sano, Kosuke Mitarai, Naoki Yamamoto, Naoki Ishikawa |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Transactions on Quantum Engineering |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10508492/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Incentivizing Demand-Side Response Through Discount Scheduling Using Hybrid Quantum Optimization
by: David Bucher, et al.
Published: (2024-01-01) -
Multidisk Clutch Optimization Using Quantum Annealing
by: D. John Malcolm, et al.
Published: (2024-01-01) -
Research on Three-Dimensional Extension of Barzilai-Borwein-like Method
by: Tianji Wang, et al.
Published: (2025-01-01) -
On a general convergence for Broyden like update method
by: Rabindranath Sen, et al.
Published: (1991-01-01) -
Combining non-Monotone trust rregion method with a new adaptive radius for unconstrained optimization problems
by: Seyed Hamzeh Mirzaei, et al.
Published: (2024-06-01)