Hardware-Efficient Rydberg Atomic Quantum Solvers for NP Problems

TL;DR

This paper presents a hardware-efficient quantum solver for NP problems using Rydberg-atom systems, achieving quadratic speedup with linear resource scaling, and offering a practical pathway for demonstrating quantum advantage.

Contribution

It introduces a novel Rydberg-atom-based quantum solver for NP problems with a unified framework and linear resource scaling, improving over previous approaches.

Findings

Quantum oracles designed with parallelizable gates enable broad NP problem solving.

Qubit number scales linearly with problem size, reducing resource overhead.

Atomic qubits offer favorable circuit depth scaling compared to fixed connectivity processors.

Abstract

Developing hardware-efficient implementations of quantum algorithms is crucial in the NISQ era to achieve practical quantum advantage. Here, we construct a generic quantum solver for NP problems based on Grover's search algorithm, specifically tailored for Rydberg-atom quantum computing platforms. We design the quantum oracles in the search algorithm using parallelizable single-qubit and multi-qubit entangling gates in the Rydberg atom system, yielding a unified framework for solving a broad class of NP problems with provable quadratic quantum speedup. We analyze the experimental resource requirements considering the unique qubit connectivity of the dynamically reconfigurable qubits in the optical tweezer array. The required qubit number scales linearly with the problem size, representing a significant improvement over existing Rydberg-based quantum annealing approaches that incur quadratic overhead. These results provide a concrete roadmap for future experimental efforts towards demonstrating quantum advantage in NP problem solving using Rydberg atomic systems. Our construction indicates that atomic qubits offer favorable circuit depth scaling compared to quantum processors with fixed local connectivity.