# Quantum Computing: A Taxonomy, Systematic Review and Future Directions

arXiv: https://arxiv.org/abs/2010.15559 · HTML: https://mlsanity.com/paper/2010.15559/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2020.

## Built on by (most cited first, 16 of 16)

- [Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers](https://mlsanity.com/paper/2303.01977/) (2023)
- [Quantum Federated Learning Experiments in the Cloud with Data Encoding](https://mlsanity.com/paper/2405.00909/) (2024)
- [Solving a Real-World Package Delivery Routing Problem Using Quantum Annealers](https://mlsanity.com/paper/2403.15114/) (2024)
- [Optimizing Tensor Network Contraction Using Reinforcement Learning](https://mlsanity.com/paper/2204.09052/) (2022)
- [Shot Optimization in Quantum Machine Learning Architectures to Accelerate Training](https://mlsanity.com/paper/2304.12950/) (2023)
- [Benchmarking Machine Learning Models for Quantum Error Correction](https://mlsanity.com/paper/2311.11167/) (2023)
- [Quantum Artificial Intelligence for the Science of Climate Change](https://mlsanity.com/paper/2108.10855/) (2021)
- [CRUISE on Quantum Computing for Feature Selection in Recommender Systems](https://mlsanity.com/paper/2407.02839/) (2024)
- [Computational Architects of Society: Quantum Machine Learning for Social Rule Genesis](https://mlsanity.com/paper/2506.03503/) (2025)
- [Exploring Quantum Machine Learning for Weather Forecasting](https://mlsanity.com/paper/2509.01422/) (2025)
- [SciDocBench: A Workflow-Centered Benchmark and Data Pipeline for Scientific Document Understanding](https://mlsanity.com/paper/2609.05141/) (2026)
- [Universal replication of chaotic characteristics by classical and quantum machine learning](https://mlsanity.com/paper/2405.08484/) (2024)
- [Quantum-Enhanced Classification of Brain Tumors Using DNA Microarray Gene Expression Profiles](https://mlsanity.com/paper/2505.02033/) (2025)
- [Quantum Observers: A NISQ Hardware Demonstration of Chaotic State Prediction Using Quantum Echo-state Networks](https://mlsanity.com/paper/2505.06799/) (2025)
- [Quantum Neural Network applications to Protein Binding Affinity Predictions](https://mlsanity.com/paper/2508.03446/) (2025)
- [QAISim: A Toolkit for Modeling and Simulation of AI in Quantum Cloud Computing Environments](https://mlsanity.com/paper/2512.17918/) (2025)

## Abstract (arXiv)

Quantum computing is an emerging paradigm with the potential to offer significant computational advantage over conventional classical computing by exploiting quantum-mechanical principles such as entanglement and superposition. It is anticipated that this computational advantage of quantum computing will help to solve many complex and computationally intractable problems in several areas such as drug design, data science, clean energy, finance, industrial chemical development, secure communications, and quantum chemistry. In recent years, tremendous progress in both quantum hardware development and quantum software/algorithm have brought quantum computing much closer to reality. Indeed, the demonstration of quantum supremacy marks a significant milestone in the Noisy Intermediate Scale Quantum (NISQ) era - the next logical step being the quantum advantage whereby quantum computers solve a real-world problem much more efficiently than classical computing. As the quantum devices are expected to steadily scale up in the next few years, quantum decoherence and qubit interconnectivity are two of the major challenges to achieve quantum advantage in the NISQ era. Quantum computing is a highly topical and fast-moving field of research with significant ongoing progress in all facets. This article presents a comprehensive review of quantum computing literature, and taxonomy of quantum computing. Further, the proposed taxonomy is used to map various related studies to identify the research gaps. A detailed overview of quantum software tools and technologies, post-quantum cryptography and quantum computer hardware development to document the current state-of-the-art in the respective areas. We finish the article by highlighting various open challenges and promising future directions for research.