Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

Quantum algorithms

Bilha Segev

Published Jul 31, 2002• 0 citations
Publisher

Abstract

I review a few of the most famous quantum algorithms, and discuss them from a practical perspective. What should a quantum system be able to do, in principle, to qualify as a quantum computer for which these algorithms work? The role of superposition, parallelism, and entanglement is discussed.
DOI
10.1117/12.477420

Related papers

Quantum Algorithms and Applications

Dhairyya Agarwal, D Shalini, Srinjoy Ganguly

In the previous chapter, we discussed the basics of quantum computing and some essential properties such as superposition, entanglement, and the Uncertainty Principle. In this chapter, we will discuss a few prominent quantum algorithms and their applications.

Apress eBooks•Jan 1, 2023•1 citation

A Review On Quantum Technologies: From Fundamentals To Applications

Sudheshwar Singh

In this section we provide a broad overview of the basic principles of quantum mechanics and how they enable modern quantum technologies. The starting point is the concept of superposition, which allows quantum systems to be in multiple states at the same time and forms the basis of quantum computation using qubits and parallel processing of information. The conversation then turns to quantum entanglement, a non-classical effect that creates strong correlations between particles, and has applications in secure communication and quantum teleportation. Also mentioned is the quantum coherence, which preserves phase relations between quantum states and makes it possible for quantum systems to function correctly. But it is also emphasized that quantum coherence is fragile to environmental perturbations. This chapter also covers quantum measurement, taking into account the probabilistic nature of quantum mechanics, and how the act of observation results in the collapse of a quantum state to a definite outcome. These principles together constitute the theoretical basis of quantum computing, where quantum gates and algorithms and qubits take advantage of superposition, entanglement and interference to offer computational benefits over classical systems. The most important algorithms like Shor’s and Grover’s algorithms that demonstrate a considerable speed-up in solving the problem are discussed along with different models of quantum computing, such as gate, adiabatic and measurement-based models. Furthermore, the section reviews some physical realizations of quantum systems, such as superconducting qubits, trapped ions, photonic systems and topological qubits, with their advantages and difficulties. Overall, this discussion shows how the basic principles of quantum mechanics are the foundation for the development of advanced quantum technologies, while also dealing with the practical difficulties that arise in their implementation.

Nanotechnology Perceptions•Nov 10, 2014•0 citations

Quantum Algorithms

Seyed Massoud Amini

We give a short overview of quantum algorithms. Some famous algorithms such as Deutsch-Jozsa and Simon are covered with more details. The directions for further development are addressed,

•Jun 1, 2009•0 citations

Quantum Computing Algorithms for Large-Scale Data Analysis and Optimization

Saima Parveen, Waqar Ahmad

The exponential growth of data across various domains has necessitated novel computational paradigms capable of processing and optimizing large-scale datasets efficiently. Quantum computing offers a promising solution by leveraging principles such as superposition, entanglement, and quantum parallelism. This paper reviews quantum algorithms applicable to data analysis and optimization, including quantum approximate optimization algorithms (QAOA), Grover’s search, and quantum machine learning techniques. We explore their potential advantages over classical approaches in solving combinatorial optimization problems, big data analytics, and high-dimensional pattern recognition. Graphical analyses illustrate computational efficiency and accuracy improvements of quantum algorithms on benchmark datasets. Challenges in scalability, error correction, and algorithmic implementation are discussed, along with potential future directions for integrating quantum computing into practical large-scale data applications

International Research Journal of Advanced Science•Oct 20, 2025•0 citations

Quantum-Powered Diagnostics: Speed and Accuracy in Disease Detection

Aumansh Vijayendra Gupta, Aditi Kohli, Deepak Kumar Verma +2 more

Quantum computing and diagnostic technologies are two fields that are being integrated to redefine the possibilities of modern medicine, especially the speed and accuracy with which the disease can be identified. In this chapter, the authors are talking about the quantum computing revolution, along with its other applications in advanced algorithms, diagnostic sensors, and machine learning, to change the way we detect and respond to illnesses. Having on advanced quantum concepts, like superposition, entanglement, and/or quantum parallelism, diagnostic computing is able to receive, process, and clear of enormous amounts of data in record time; therefore, it can be able to detect diseases in advance and correctly detect diseases. Diagnostics based on quantum allow empowering the change of healthcare systems, both assessment and identification of specific cancer-related molecules in body fluids and tissues, as well as predicting adverse infectious diseases, including COVID 19. The chapter outlines the use of real-time applications, the prevailing obstacles, and opportunities along with the principles and required technology infrastructure to incorporate the innovative and leading edge technologies into the clinical practices. With the current fast development of these technologies, the perspective of faster, more accurate, and more customized diagnostics has a potential to save countless lives and redefine the health of populations across the globe.

CRC Press eBooks•Oct 7, 2026•0 citations

Quantum Algorithms

Ted G. Lewis

This essay was written for computer scientists seeking to understand quantum computing from an algorithmic point of view. It sacrifices rigorous physics so anyone with a computer science background can understand it. Note that it is about algorithms, not machines. This is intentional.

Ubiquity•Mar 1, 2024•0 citations
In this section we provide a broad overview of the basic principles of quantum mechanics and how they enable modern quantum technologies. The starting point is the concept of superposition, which allows quantum systems to be in multiple states at the same time and forms the basis of quantum computation using qubits and parallel processing of information. The conversation then turns to quantum entanglement, a non-classical effect that creates strong correlations between particles, and has applications in secure communication and quantum teleportation. Also mentioned is the quantum coherence, which preserves phase relations between quantum states and makes it possible for quantum systems to function correctly. But it is also emphasized that quantum coherence is fragile to environmental perturbations. This chapter also covers quantum measurement, taking into account the probabilistic nature of quantum mechanics, and how the act of observation results in the collapse of a quantum state to a definite outcome. These principles together constitute the theoretical basis of quantum computing, where quantum gates and algorithms and qubits take advantage of superposition, entanglement and interference to offer computational benefits over classical systems. The most important algorithms like Shor’s and Grover’s algorithms that demonstrate a considerable speed-up in solving the problem are discussed along with different models of quantum computing, such as gate, adiabatic and measurement-based models. Furthermore, the section reviews some physical realizations of quantum systems, such as superconducting qubits, trapped ions, photonic systems and topological qubits, with their advantages and difficulties. Overall, this discussion shows how the basic principles of quantum mechanics are the foundation for the development of advanced quantum technologies, while also dealing with the practical difficulties that arise in their implementation.
The exponential growth of data across various domains has necessitated novel computational paradigms capable of processing and optimizing large-scale datasets efficiently. Quantum computing offers a promising solution by leveraging principles such as superposition, entanglement, and quantum parallelism. This paper reviews quantum algorithms applicable to data analysis and optimization, including quantum approximate optimization algorithms (QAOA), Grover’s search, and quantum machine learning techniques. We explore their potential advantages over classical approaches in solving combinatorial optimization problems, big data analytics, and high-dimensional pattern recognition. Graphical analyses illustrate computational efficiency and accuracy improvements of quantum algorithms on benchmark datasets. Challenges in scalability, error correction, and algorithmic implementation are discussed, along with potential future directions for integrating quantum computing into practical large-scale data applications
Quantum computing and diagnostic technologies are two fields that are being integrated to redefine the possibilities of modern medicine, especially the speed and accuracy with which the disease can be identified. In this chapter, the authors are talking about the quantum computing revolution, along with its other applications in advanced algorithms, diagnostic sensors, and machine learning, to change the way we detect and respond to illnesses. Having on advanced quantum concepts, like superposition, entanglement, and/or quantum parallelism, diagnostic computing is able to receive, process, and clear of enormous amounts of data in record time; therefore, it can be able to detect diseases in advance and correctly detect diseases. Diagnostics based on quantum allow empowering the change of healthcare systems, both assessment and identification of specific cancer-related molecules in body fluids and tissues, as well as predicting adverse infectious diseases, including COVID 19. The chapter outlines the use of real-time applications, the prevailing obstacles, and opportunities along with the principles and required technology infrastructure to incorporate the innovative and leading edge technologies into the clinical practices. With the current fast development of these technologies, the perspective of faster, more accurate, and more customized diagnostics has a potential to save countless lives and redefine the health of populations across the globe.