Practical Use Cases of Neutral Atoms Quantum Computers

TL;DR

This paper reviews the current state, hardware advancements, and diverse applications of neutral atom quantum computers, emphasizing their potential in optimization, simulation, chemistry, and machine learning.

Contribution

It provides a comprehensive overview of recent developments, hardware improvements, and practical use cases of neutral atom quantum processors, highlighting their versatility and potential.

Findings

Recent hardware advancements improve circuit fidelity.

Neutral atom quantum computers effectively simulate complex quantum systems.

Applications extend to optimization, chemistry, and machine learning.

Abstract

Quantum computing has quickly emerged as a revolutionary paradigm that holds the potential for greatly enhanced computational capability and algorithmic efficiency, in a wide range of areas. Among the various hardware platforms, neutral atom quantum processors based on Rydberg interactions are gaining increasing interest because of their scalability, qubit-connection flexibility, and intrinsic appropriateness for solving combinatorial optimization challenges. This paper provides an overview of the present capabilities, standards, and applications of neutral atom quantum computers. We first discuss recent hardware advancements and register mapping optimization techniques that enhance circuit fidelity and performance. We next review their uses as quantum simulators, in both classical and quantum hard problems, such as MIS and QUBO problems, quantum many-body models and molecules in chemistry and pharmacology. Applications for enhancing machine learning are also covered.