A brief introduction to quantum algorithms

Abstract

Quantum algorithms are demonstrated to outperform classical algorithms for certain problems and thus are promising candidates for efficient information processing. Herein we aim to provide a brief and popular introduction to quantum algorithms for both the academic community and the general public with interest. We start from elucidating quantum parallelism, the basic framework of quantum algorithms and the difficulty of quantum algorithm design. Then we mainly focus on a historical overview of progress in quantum algorithm research over the past three to four decades. Finally, we clarify two common questions about the study of quantum algorithms, hoping to stimulate readers for further exploration.

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• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Quantum algorithm for solving linear systems of equations
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• An introduction to quantum machine learning
• Exponential algorithmic speedup by quantum walk
• Quantum Data Fitting
• Hybrid quantum-classical algorithms and quantum error mitigation
• Experimental Comparison of Two Quantum Computing Architectures
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Cited by in corpus (6)

• Quantum algorithms for anomaly detection using amplitude estimation
• Deterministic quantum search with adjustable parameters: implementations and applications
• Complementarity between Success Probability and Coherence in Grover Search Algorithm
• Quantum Algorithms for Identifying Hidden Strings with Applications to Matroid Problems
• Succinct quantum testers for closeness and $k$-wise uniformity of probability distributions
• Efficient explicit circuit for quantum state preparation of piecewise continuous functions