Authors :
Palaganti Venkata Nagendra Sai Sandeep
Volume/Issue :
Volume 10 - 2025, Issue 7 - July
Google Scholar :
https://tinyurl.com/bda9try5
Scribd :
https://tinyurl.com/54kw3fuk
DOI :
https://doi.org/10.38124/ijisrt/25jul1660
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Grover's algorithm stands as a cornerstone of quantum computing, offering a theoretical quadratic speedup for
unstructured search problems. This allows for finding a target item in an unsorted database of N entries in approximately
the square root of N steps, a significant improvement over classical algorithms which require a number of operations on the
order of N in the worst case. This speedup becomes particularly compelling for very large datasets, where classical exhaustive
search becomes computationally intractable. The algorithm achieves this by leveraging fundamental quantum mechanical
principles, primarily superposition and interference. It operates by preparing qubits in a uniform superposition of all
possible states, then iteratively applying a quantum oracle to mark the desired state by flipping its phase, followed by a
diffusion operator that amplifies the probability of the marked state. Despite its theoretical promise, real-world
implementation faces substantial challenges stemming from Noisy Intermediate-Scale Quantum (NISQ) hardware, which is
characterized by high error rates and short coherence times. Consequently, achieving a true, scalable quantum advantage
remains a future endeavor, contingent on significant hardware advancements. Nevertheless, Grover's algorithm holds
significant potential across diverse fields, including enhancing brute-force attacks on cryptographic systems, accelerating
solutions for optimization problems, and speeding up search processes in machine learning and unstructured database
queries.
Keywords :
Quantum Computing, Grover's Algorithm, Cryptography, Symmetric-Key Ciphers, Dynamic Defense Labyrinth Problem, Noisy Intermediate-Scale Quantum (NISQ) Era.
References :
- S. Lee, "Grover's Algorithm: A Quantum Leap," Number Analytics Blog, Jun. 18, 2025. [Online]. Available: https://www.numberanalytics.com/blog/grovers-algorithm-quantum-computing-philosophy.
- "Grover's Algorithm," Classiq, Feb. 22, 2024. [Online]. Available: https://www.classiq.io/insights/grovers-algorithm.
- "Grover's Algorithm | Quantum Programming 101," The Quantum Insider, Nov. 13, 2019. [Online]. Available: https://thequantuminsider.com/2019/11/13/quantum-programming-101-grovers-algorithm/.
- "Grover's algorithm," Wikipedia, Jul. 17, 2025. [Online]. Available: https://en.wikipedia.org/wiki/Grover%27s_algorithm.
- "Grover's algorithm," IBM Quantum Documentation, 2025. [Online]. Available: https://quantum.cloud.ibm.com/docs/tutorials/grovers-algorithm.
- M. Ivezic, "Grover's Algorithm and Its Impact on Cybersecurity," Post-Quantum, Aug. 14, 2017. [Online]. Available: https://postquantum.com/post-quantum/grovers-algorithm/.
- "Theory of Grover Search Algorithm," Microsoft Learn, Jan. 16, 2025. [Online]. Available: https://learn.microsoft.com/en-us/azure/quantum/concepts-grovers.
- A. Masood, "Quantum Sundays 16 Quadratic Speedup in Unstructured Search: A Detailed Examination of Grover's Algorithm," Medium, May 23, 2025. [Online]. Available: https://medium.com/@adnanmasood/quantum-sundays-6-quadratic-speedup-in-unstructured-search-a-detailed-examination-of-grovers-ca263064e4c7.
- Quantum News, "Understanding Quantum Algorithms: A Beginner's Guide," Quantum Zeitgeist, Sep. 9, 2024. [Online]. Available: https://quantumzeitgeist.com/understanding-quantum-algorithms-a-beginners-guide/.
- H. Gharibyan, "Quantum Programming Languages: A Beginner's Guide for 2025," BlueQubit, Feb. 21, 2025. [Online]. Available: https://www.bluequbit.io/quantum-programming-languages.
- "Microsoft Azure Quantum," Wikipedia, Jun. 12, 2025. [Online]. Available: https://en.wikipedia.org/wiki/Microsoft_Azure_Quantum.
- "IBM Quantum Platform," Wikipedia, Jun. 2, 2025. [Online]. Available:(https://en.wikipedia.org/wiki/IBM_Quantum_Platform).
- "Learn Quantum Computing: 4 Proven Ways for Beginners," SpinQ, Jan. 20, 2025. [Online]. Available: https://www.spinquanta.com/news-detail/learn-quantum-computing-proven-ways-for-beginners20250120032606.
- "Cirq," Wikipedia, May 29, 2025. [Online]. Available: https://en.wikipedia.org/wiki/Cirq.
- V. Kothari, "Quantum Computing: Grover's Algorithm (CIRQ)," Kaggle, 2023. [Online]. Available: https://www.kaggle.com/code/viratkothari/quantum-computing-grover-s-algorithm-cirq.
- "Tutorial: Implement Grover's Algorithm in Q#," Microsoft Learn, Nov. 15, 2024. [Online]. Available: https://learn.microsoft.com/en-us/azure/quantum/tutorial-qdk-grovers-search.
- "2025 - The Neutral Atom SDK," QuEra Computing, 2025. [Online]. Available: https://bloqade.quera.com/v0.26.0/blog/archive/2025/.
- "Quantum programming," Wikipedia, Jul. 27, 2025. [Online]. Available: https://en.wikipedia.org/wiki/Quantum_programming.
- L. Bhatia, V. S. Pandey, and A. K. Sharma, "Evaluating the Practicality of Grover's Algorithm for Large-Scale Data Search via Quantum Simulation," Preprint, May 2025, doi: 10.21203/rs.3.rs-6954705/v1.
- "How Many Quantum Computers Are There in 2025?" SpinQ, 2025. [Online]. Available: https://www.spinquanta.com/news-detail/how-many-quantum-computers-are-there.
- M. Swayne, "Quantum Computing Roadmaps: A Look at The Maps and Predictions of Major Quantum Players," The Quantum Insider, May 16, 2025. [Online]. Available: https://thequantuminsider.com/2025/05/16/quantum-computing-roadmaps-a-look-at-the-maps-and-predictions-of-major-quantum-players/.
- E. M. Stoudenmire and X. Waintal, "Opening the Black Box inside Grover's Algorithm," Phys. Rev. X, vol. 14, no. 4, p. 041029, Nov. 2024.
- S. Aaronson, "Of course Grover's algorithm offers a quantum advantage!" Shtetl-Optimized, Mar. 22, 2023. [Online]. Available: https://scottaaronson.blog/?p=7143.
- V. Sagar, "Safeguarding Communication in the Age of Quantum Computers," swIDch Blog, Mar. 11, 2024. [Online]. Available: https://www.swidch.com/resources/blogs/quantum-proofing-our-secrets-safeguarding-communication-in-the-age-of-quantum-computers.
Grover's algorithm stands as a cornerstone of quantum computing, offering a theoretical quadratic speedup for
unstructured search problems. This allows for finding a target item in an unsorted database of N entries in approximately
the square root of N steps, a significant improvement over classical algorithms which require a number of operations on the
order of N in the worst case. This speedup becomes particularly compelling for very large datasets, where classical exhaustive
search becomes computationally intractable. The algorithm achieves this by leveraging fundamental quantum mechanical
principles, primarily superposition and interference. It operates by preparing qubits in a uniform superposition of all
possible states, then iteratively applying a quantum oracle to mark the desired state by flipping its phase, followed by a
diffusion operator that amplifies the probability of the marked state. Despite its theoretical promise, real-world
implementation faces substantial challenges stemming from Noisy Intermediate-Scale Quantum (NISQ) hardware, which is
characterized by high error rates and short coherence times. Consequently, achieving a true, scalable quantum advantage
remains a future endeavor, contingent on significant hardware advancements. Nevertheless, Grover's algorithm holds
significant potential across diverse fields, including enhancing brute-force attacks on cryptographic systems, accelerating
solutions for optimization problems, and speeding up search processes in machine learning and unstructured database
queries.
Keywords :
Quantum Computing, Grover's Algorithm, Cryptography, Symmetric-Key Ciphers, Dynamic Defense Labyrinth Problem, Noisy Intermediate-Scale Quantum (NISQ) Era.