Control of Driven Stochastic Systems: From Shortcuts to Optimality

Dear Colleagues,

In recent years, the study of problems related to the control of stochastic dynamics has seen increasing interest. Control theory aims to identify protocols to steer a system to a desired target state in a given time ("shortcuts") or to complete a pre-assigned transition in an optimal way (minimal time, minimal energetic cost). Due to the relentless refinement of experimental techniques, it is now possible to control physical systems subject to different kinds of fluctuations with unprecedented precision, from the nanoscale level (levitated particles, colloids, nanodevices), where thermal fluctuations are not negligible, to the microscopic realm of bacteria and active matter, up to the macroscopic world (vibrated granular materials, energy harvesters). Therefore, the framework of control theory needs to be extended to the stochastic domain, in order to also be applicable to these systems. Besides its implicit applications, this line of investigation has deep connections with fundamental topics in stochastic thermodynamics (efficiency bounds, fluctuations relations) and information theory (Landauer bound).

The goal of this Special Issue is to gather contributions on the different aspects of the subject. We aim, in particular, to present the wide array of approaches that are adopted in this context, such as the use of novel tools in reinforcement learning, alongside well-established analytical methods from control theory.

Dr. Marco Baldovin
Dr. Alessandro Manacorda
Dr. Dario Lucente
Dr. Andrea Plati
Dr. Alessandro Sarracino
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.

• stochastic processes
• optimal control
• shortcuts to adiabaticity
• nonequilibrium statistical mechanics
• stochastic thermodynamics
• dynamic programming
• reinforcement learning