Taming Dissipation in Open Quantum Systems: Applications in Information Processing

The first main aim of DISQINF is to develop a framework for optimal thermodynamic control of composite quantum systems (made up of few or many
particles). The second main aim is to make use of this framework to optimize the energetics of information processing. DISQINF is structured among
three specific objectives:
(A) To develop a framework for optimal thermodynamic control in many-body systems, which will provide new mechanisms to minimize dissipation via
collective effects.
(B) To exploit the previous framework to improve new physics-based models of analog computing and information processing.
(C) To exploit control on interacting composite systems to improve the estimation of free energy, ultra-low temperatures and magnetic fields via quantum
sensors.
These objectives entail the optimization of driven interacting quantum systems open to the environment. To deal with this highly complex problem, we
will combine state-of-the-art techniques from different fields (open quantum systems, quantum statistical mechanics, stochastic and quantum
thermodynamics) with novel methodology including quantum thermodynamic geometry.
Expected outcomes are (i) improved protocols for erasing information in finite-time via collective processes, with direct implications for the reachability of
Landauer bound, (ii) the development and optimization of physics-based computing models based on equilibrium and non-equilibrium steady states,
including a characterization of tradeoffs between dissipation, time and computation accuracy, and (iii) improved protocols for measuring low
temperatures, magnetic fields and free energy via quantum sensors.
Overall, the outcomes of DISQINF will substantially improve the energetics, and contribute to the development, of new nano and quantum devices for
information processing. While this project is of theoretical nature, the expected outcomes are directly relevant for solid-state quantum devices and early
prototypes of thermodynamic computing. The implementations of our results in such systems via already established collaborations will be pursued,
bridging the gap between theoretical fundamental research and applications.