This dataset provides a comprehensive collection of quantum algorithms, covering various aspects of quantum computing. Whether you are a beginner or an expert, this dataset is a valuable resource for exploring the fascinating world of quantum algorithms.

Overview

  • Size: 100+ quantum algorithms
  • Formats: Python, C++, and Q# (Quantum#)
  • Applications: Cryptography, Quantum Simulation, Optimization, and more

Content

Basic Quantum Algorithms

  • Quantum Fourier Transform (QFT): A key algorithm for many quantum computations.
  • Shor's Algorithm: Solves the integer factorization problem in polynomial time on a quantum computer.
  • Grover's Algorithm: Provides a quadratic speedup for unstructured search problems.

Advanced Quantum Algorithms

  • Quantum Phase Estimation: A fundamental algorithm for many quantum algorithms.
  • Quantum Amplitude Amplification: Enhances the probability of finding a solution to a problem.
  • Quantum Machine Learning Algorithms: Explore the intersection of quantum computing and machine learning.

Example: Quantum Phase Estimation

Quantum Phase Estimation is a powerful algorithm used in many other quantum algorithms. It estimates the phase of a quantum state. Here's a brief overview:

  • Input: A quantum state and a unitary operator.
  • Output: An approximation of the phase of the quantum state.

Learn More

For more information on quantum algorithms, check out our Quantum Computing Tutorial or explore the Quantum Algorithms GitHub Repository.

Quantum Phase Estimation Diagram

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