References

1. Quantum Simulation Limitations: Early literature emphasizes the inability of classical simulations to model quantum interactions accurately.
2. Hybrid Models: Recent advancements combine quantum and classical methods, addressing power limitations but retaining accuracy constraints.
3. Algorithm Optimization: Research shows that quantum algorithms offer significant time savings in chemical reaction predictions.
4. Cryptographic Applications: Studies highlight the robustness of quantum key distribution in secure communication.
5. Error Rates: Initial findings identified instability in quantum systems, leading to the development of error correction techniques.
6. Narendra Kumar, B. Srinivas and Alok Kumar Aggrawal: “Web Application Vulnerability Assessment” International Journal of Enterprise computing and Business Systems”, vol-1, 2011(https://www.atlantispress.com/proceedings/cac2s-13/6377)
7. Megha Singla, Mohit Dua and Narendra Kumar: “CNS using restricted space algorithms for finding a shortest path”. International Journal of Engineering Trends and Technology, 2(1), 48-54, 2011.( https://ijettjournal.org/archive/ijett-v2i1p204)
8. Narendra Kumar and Anil Kumar “Performance for Mathematical Model of DNA Supercoil.” In the BioScience Research Bulletin, vol 22(2), pp79-87, 2007.( GALE/A199539280)
9. Technological Investments: Implementing quantum systems requires substantial resources, as seen in advanced hardware deployments.
10. Simulation Precision: Case studies demonstrate quantum computing's ability to model complex particle behavior with improved precision.
11. Industrial Use Cases: Applications in chemical modeling show potential cost savings, though practical implementation remains limited.
12. Scalability Issues: Literature indicates that quantum systems face challenges in scaling for broader scientific applications.
13. Interdisciplinary Potential: Emerging studies suggest integration with AI could amplify quantum computing’s capabilities.
14. Data Encryption Techniques: Quantum algorithms have introduced advanced encryption methods resistant to classical decryption.
15. Future Prospects: Predictions point to quantum computing's pivotal role in scientific innovation and crossdisciplinary research. Literature Gaps: Despite progress, existing research lacks comprehensive studies on long-term cryptographic impacts.
16. Error Correction Advances: New methods in correcting computational errors have improved reliability in quantum operations.
17. Emerging Technologies: Reports foresee breakthroughs through interdisciplinary collaboration, particularly in AI-quantum integrations.