Quantum Computing Algorithms

Waqar Hassan, Mujahid Tabassum, Mohammad Asif Nawaz

Vaishali Bhatia, K. R. Ramkumar

Quantum Computing is a prominent word in this era as it allows computation to be performed in no time. The motive of using Quantum Computing (QC) is that even exponentially large number of problems can be solved using it which was earlier difficult with the classical computing. Conventional methods are based on usage of bits which consist of 0's and 1's while QC works with qubits. The main issue is that conventional computing has issue of storage as well as computation even when parallel computation is performed on it. Concept of quantum parallelism allows the computation to be performed in exponentially very low time as compared to conventional method. This paper will discuss about Quantum Computing Algorithms and how Shor's algorithm is able to break RSA algorithms is discussed. Entanglement and superposition of qubits helps fast computation. The demonstration of the applicability has been evaluated based on Computation time, storage capacity, accuracy, confidentiality, efficiency, integrity, and availability. Among various algorithms Shor's technique is able to break various encryption algorithm with more supremacy as compared to conventional computing methods. In nutshell, paper will discuss about various QC algorithms and will illustrate how shor's algorithm is able to crack RSA.

Author 1 - Mr. K. Suresh Babu Author 2 : Dr. T. P. Anish Author 3 : Dr. Cornelius K

N. Pooranam, D. Surendran, N. Karthikeyan +1 more

Quantum computing (QC) is the emerging technology for solving complex problems through the laws of quantum mechanism and optimized algorithms. To examine the possibilities of active cooperation across both disciplines of computer science, this article explains the core components of quantum computing and conveys some of the important features linked by quantum computing and Artificial Intelligence (AI). To make major progress with artificial intelligence, quantum computing is probably necessary. Quantum computing’s training and processing power can be used to improve AI and machine learning (ML) algorithms at a reduced cost. AI can provide quantum computers with crucial error-correcting algorithms. Several AI algorithms have been successfully applied to quantum computers; they are constrained by the computational power of conventional computers despite developing useful applications. Artificial intelligence may benefit from quantum computing’s computational boost in order to handle more challenging issues. This case study explains the importance of quantum computing, the future of QC in AI, and the different applications of quantum computing, such as AI and ML, cybersecurity and cryptography, and weather forecasting.

Mr. K. Suresh Babu Dr. T. P. Anish Dr. Cornelius K

Hira Fatima, Waqar Ahmad

Quantum computing (QC) presents transformative potential for solving complex scientific problems that remain intractable for classical computers. Leveraging quantum superposition, entanglement, and interference, quantum algorithms such as Shor’s factoring algorithm, Grover’s search algorithm, variational quantum eigensolvers (VQE), and quantum approximate optimization algorithms (QAOA) enable exponential or polynomial speedups for selected problem classes. This paper explores recent advancements in quantum computing algorithms, their practical implementations, and emerging applications in fields such as molecular simulations, material science, cryptography, optimization, and machine learning. We highlight the strengths and limitations of current approaches, present performance analyses through graphical comparisons, and discuss prospective directions for integrating quantum algorithms into real-world scientific workflows. Our findings demonstrate that quantum computing is gradually transitioning from theoretical frameworks to experimental platforms capable of addressing highly complex computational challenges.