Trade-off between Cooling-Step Count and Geometric Implementation Cost in Non-Markovian Algorithmic Cooling

Abstract

Quantum cooling is important for reliable quantum computation but involves a trade-off between cooling performance and implementation resources. Although reservoir memory can improve particular aspects of cooling performance, the associated resource cost, particularly for circuit implementation, remains insufficiently understood. Here, we investigate how reservoir memory affects the trade-off between cooling performance quantified by the cooling-step count and geometric implementation cost in single-qubit heat-bath algorithmic cooling. Using a pseudomode mapping, we represent the non-Markovian damped Jaynes--Cummings dynamics by a repeated collision circuit and evaluate its geometric implementation cost. Using matrix-based simulations and an implementation on the ibm_kawasaki Heron r2 processor, we identify a trade-off: suppressing reservoir memory reduces the cooling-step count but generally increases the geometric protocol cost. Our work provides a resource-based perspective on reservoir engineering for algorithmic cooling.