Machine Learning in Classical and Quantum Photonic Systems

Dear Colleagues,

The last decade has witnessed a considerable burst of experimental and theoretical work combining two seemingly different fields, namely artificial intelligence and photonics. These investigations have shown the potential of machine learning for designing, controlling and interacting with complex photonic systems. More importantly, they have arguably placed machine learning as a new route of innovation, capable of transforming future quantum (and classical) photonic technologies.

Machine-learning-assisted photonics is a timely and exciting research field at the forefront of physics and technology, with much potential to impact many areas of science and engineering, including material science, communications, sensing, imaging and spectroscopy. Motivated by the increasing number of members in this fascinating community, we are happy to announce a Special Issue of Entropy focused on new developments that lie at the interface of machine learning and quantum (and classical) photonics. Through this Special Issue, we intend to advance our understanding of machine-learning-enabled photonics, aiming at developing new technologies that could have a positive impact on our way of life.

This Special Issue will be focused on theoretical and experimental contributions that bring together the fields of quantum and classical optical technologies and machine learning. Topics covered include, but are not limited to:

• Machine learning for optical applications (including advances in quantum metrology, imaging, microscopy, optical coherence tomography, etc.);
• Implementation of intelligent systems using photonic technologies;
• Machine-learning-enabled inverse design of quantum photonic devices;
• Classification of non-classical quantum states using machine learning;
• Machine-learning-assisted holography and data encryption;
• Neural network quantum-state tomography;
• Machine learning for quantum communication.

Dr. Roberto de J. León-Montiel
Dr. Jiří Svozilík
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.