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Review of Distributed Quantum Computing: From single QPU to High Performance Quantum Computing

David Barral, F. Javier Cardama, Guillermo Díaz-Camacho, Daniel Faílde et al. • Computer Science Review (2025)

The emerging field of quantum computing has shown it might change how we process information by using the unique principles of quantum mechanics . As researchers continue to push the boundaries of quantum technologies to unprecedented level...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.cosrev.2025.100747

The engineering challenges in quantum computing

Carmen G. Almudéver, Lingling Lao, Xiang Fu, Nader Khammassi et al. • Design, Automation, and Test in Europe (2017)

Quantum computers may revolutionize the field of computation by solving some complex problems that are intractable even for the most powerful current supercomputers. This paper first introduces the basic concepts of quantum computing and de...

OPENALEX DOI: https://doi.org/10.23919/date.2017.7927104

Quantum Computing 40 Years Later

John P. Preskill • CRC Press eBooks (2023)

This chapter sketches the foundations of the subject, discussing salient features of quantum information, formulates a mathematical model of quantum computation and highlights some implications of the model. It reviews two particularly prom...

OPENALEX Open Access DOI: https://doi.org/10.1201/9781003358817-7

An Introduction to Quantum Computing Algorithms

A. O. Pittenger • Birkhäuser Boston eBooks (2000)

In 1994 Peter Shor [65] published a factoring algorithm for a quantum computer that finds the prime factors of a composite integer N more efficiently than is possible with the known algorithms for a classical com­ puter. Since the difficult...

OPENALEX DOI: https://doi.org/10.1007/978-1-4612-1390-1

Quantum Entanglement in Neural Network States

Dong-Ling Deng, Xiaopeng Li, S. Das Sarma • Physical Review X (2017)

Machine learning has recently gained attention as a possible way to understand phase transitions in many-body quantum systems. A new entanglement analysis reveals crucial properties of the data structures that encode quantum states in a neu...

OPENALEX cc-by DOI: https://doi.org/10.1103/physrevx.7.021021

Expressibility and trainability of parametrized analog quantum systems for machine learning applications

Jirawat Tangpanitanon, Supanut Thanasilp, Ninnat Dangniam, Marc-Antoine Lemonde et al. • Physical Review Research (2020)

Parametrized quantum evolution is the main ingredient in variational quantum algorithms for near-term quantum devices. In digital quantum computing, it has been shown that random parametrized quantum circuits are able to express complex dis...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.2.043364

Multi-target quantum compilation algorithm

Vu Tuan Hai, Nguyen Tan Viet, Jesus Urbaneja, Nguyen Vu Linh et al. • Machine Learning: Science and Technology (2024)

Quantum compilation is the process of converting a target unitary operation into a trainable unitary represented by a quantum circuit. It has a wide range of applications, including gate optimization, quantum-assisted compiling, quantum sta...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/ad9705

Quantum computing and the entanglement frontier

John P. Preskill • arXiv (Cornell University) (2012)

Quantum information science explores the frontier of highly complex quantum states, the "entanglement frontier." This study is motivated by the observation (widely believed but unproven) that classical systems cannot simulate highly entangl...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1203.5813

Quantum computing with neutral atoms

Loïc Henriet, Lucas Béguin, Adrien Signoles, Thierry Lahaye et al. • Quantum (2020)

The manipulation of neutral atoms by light is at the heart of countless scientific discoveries in the field of quantum physics in the last three decades. The level of control that has been achieved at the single particle level within arrays...

OPENALEX cc-by DOI: https://doi.org/10.22331/q-2020-09-21-327

Quantum Chemistry in the Age of Quantum Computing

Yudong Cao, Jonathan Romero, Jonathan P. Olson, Matthias Degroote et al. • Chemical Reviews (2019)

Practical challenges in simulating quantum systems on classical computers have been widely recognized in the quantum physics and quantum chemistry communities over the past century. Although many approximation methods have been introduced, ...

OPENALEX Open Access DOI: https://doi.org/10.1021/acs.chemrev.8b00803

Quantum Leap in Healthcare: A Comparative Analysis of AI/ML and Quantum Computing for Healthcare opportunities of the new era

salma mostafa ahmed helmy, Salsabil Amin, Abeer mahmoud, El-Sayed El-Horabty • International Journal of Intelligent Computing and Information Sciences (2026)

The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...

DOAJ Open Access (DOAJ) DOI: 10.21608/ijicis.2026.442636.1439

Machine learning for quantum matter

Juan Carrasquilla • Advances in Physics X (2020)

Quantum matter, the research field studying phases of matter whose properties are intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter physics, materials science, statistical mechanics, quantum information,...

OPENALEX cc-by DOI: https://doi.org/10.1080/23746149.2020.1797528

Inferring Markovian quantum master equations of few-body observables in interacting spin chains

Francesco Carnazza, Federico Carollo, Dominik Zietlow, Sabine Andergassen et al. • New Journal of Physics (2022)

Full information about a many-body quantum system is usually out-of-reach due to the exponential growth—with the size of the system—of the number of parameters needed to encode its state. Nonetheless, in order to understand the complex phen...

DOAJ Open Access (DOAJ) DOI: 10.1088/1367-2630/ac7df6