Heat-Bath Algorithmic Cooling with optimal thermalization strategies
\'Alvaro M. Alhambra, Matteo Lostaglio, Christopher Perry

TL;DR
This paper extends Heat-Bath Algorithmic Cooling protocols by optimizing thermalization strategies, achieving exponential convergence to the ground state with fewer resources and demonstrating robustness and experimental feasibility.
Contribution
It introduces optimal thermalization protocols for HBAC, including new states and processes, and links theoretical optimization with practical implementation using Jaynes-Cummings interactions.
Findings
Optimal protocols achieve exponential cooling convergence.
Protocols can be implemented with Jaynes-Cummings interactions.
Enhanced cooling with fewer ancillas and memory effects.
Abstract
Heat-Bath Algorithmic Cooling is a set of techniques for producing highly pure quantum systems by utilizing a surrounding heat-bath and unitary interactions. These techniques originally used the thermal environment only to fully thermalize ancillas at the environment temperature. Here we extend HBAC protocols by optimizing over the thermalization strategy. We find, for any -dimensional system in an arbitrary initial state, provably optimal cooling protocols with surprisingly simple structure and exponential convergence to the ground state. Compared to the standard ones, these schemes can use fewer or no ancillas and exploit memory effects to enhance cooling. We verify that the optimal protocols are robusts to various deviations from the ideal scenario. For a single target qubit, the optimal protocol can be well approximated with a Jaynes-Cummings interaction between the system and a…
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