Towards Quantum-Enhanced Cloud Platforms: Bridging Classical and Quantum Computing for Future Workloads

Main Article Content

Lakshminarayana Reddy Kothapalli Sondinti
Srinivas Kalisetty
Tulasi Naga Subhash Polineni
Nareddy abhireddy

Abstract

The rapid advancement of quantum computing technology presents an opportunity to revolutionize cloud computing platforms, enabling the execution of complex workloads that are beyond the reach of classical systems. This paper explores the potential of quantum-enhanced cloud platforms, focusing on bridging classical and quantum computing to support future workloads. We examine the integration of quantum processors with classical cloud infrastructure, highlighting the challenges and benefits of hybrid architectures that combine the strengths of both paradigms. Key topics include quantum resource management, quantum programming models, and the development of algorithms that leverage quantum speedup for optimization, machine learning, and data analysis. Additionally, we address the scalability, security, and interoperability concerns that must be overcome for effective deployment in real-world cloud environments. By offering insights into the convergence of classical and quantum computing, this paper provides a roadmap for the evolution of cloud platforms capable of supporting next-generation applications and workloads.

Article Details

How to Cite
Lakshminarayana Reddy Kothapalli Sondinti, Srinivas Kalisetty, Tulasi Naga Subhash Polineni, & Nareddy abhireddy. (2023). Towards Quantum-Enhanced Cloud Platforms: Bridging Classical and Quantum Computing for Future Workloads. Journal for ReAttach Therapy and Developmental Diversities, 6(10s(2), 492–504. https://doi.org/10.53555/jrtdd.v6i10s(2).3347
Section
Articles
Author Biographies

Lakshminarayana Reddy Kothapalli Sondinti

Sr software engineer, bank, Dallas

Srinivas Kalisetty

Integration and AI lead, Miracle Software Systems

Tulasi Naga Subhash Polineni

Sr Data Engineer, Exelon, Baltimore MD

Nareddy abhireddy

Research assistant