A survey of important issues in quantum computing and communications
Driven by the rapid progress in quantum hardware, recent years have witnessed a furious
race for quantum technologies in both academia and industry. Universal quantum …
race for quantum technologies in both academia and industry. Universal quantum …
Quantum machine learning: from physics to software engineering
Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …
technology and artificial intelligence. This review provides a two-fold overview of several key …
[HTML][HTML] Experimental quantum speed-up in reinforcement learning agents
As the field of artificial intelligence advances, the demand for algorithms that can learn
quickly and efficiently increases. An important paradigm within artificial intelligence is …
quickly and efficiently increases. An important paradigm within artificial intelligence is …
Quantum state tomography with conditional generative adversarial networks
Quantum state tomography (QST) is a challenging task in intermediate-scale quantum
devices. Here, we apply conditional generative adversarial networks (CGANs) to QST. In the …
devices. Here, we apply conditional generative adversarial networks (CGANs) to QST. In the …
[HTML][HTML] Quantum machine learning: A tutorial
JD Martín-Guerrero, L Lamata - Neurocomputing, 2022 - Elsevier
This tutorial provides an overview of Quantum Machine Learning (QML), a relatively novel
discipline that brings together concepts from Machine Learning (ML), Quantum Computing …
discipline that brings together concepts from Machine Learning (ML), Quantum Computing …
Quantum machine learning applications in the biomedical domain: A systematic review
Quantum technologies have become powerful tools for a wide range of application
disciplines, which tend to range from chemistry to agriculture, natural language processing …
disciplines, which tend to range from chemistry to agriculture, natural language processing …
Machine learning for long-distance quantum communication
Machine learning can help us in solving problems in the context of big-data analysis and
classification, as well as in playing complex games such as Go. But can it also be used to …
classification, as well as in playing complex games such as Go. But can it also be used to …
Deep reinforcement learning for self-tuning laser source of dissipative solitons
Increasing complexity of modern laser systems, mostly originated from the nonlinear
dynamics of radiation, makes control of their operation more and more challenging, calling …
dynamics of radiation, makes control of their operation more and more challenging, calling …
Practical application-specific advantage through hybrid quantum computing
M Perelshtein, A Sagingalieva, K Pinto, V Shete… - arXiv preprint arXiv …, 2022 - arxiv.org
Quantum computing promises to tackle technological and industrial problems
insurmountable for classical computers. However, today's quantum computers still have …
insurmountable for classical computers. However, today's quantum computers still have …
Coherent transport of quantum states by deep reinforcement learning
Some problems in physics can be handled only after a suitable ansatz solution has been
guessed, proving to be resilient to generalization. The coherent transport of a quantum state …
guessed, proving to be resilient to generalization. The coherent transport of a quantum state …