An almost deterministic cooling by measurements

TL;DR

This paper presents a near-deterministic protocol for cooling a quantum resonator to its ground state using a two-step measurement-assisted process, significantly reducing thermal occupation with high success probability.

Contribution

It introduces a novel two-step measurement protocol utilizing reinforcement learning and conditional measurements to achieve near-unit success in quantum cooling.

Findings

Resonator thermal occupation reduced by five orders of magnitude.

Success probability exceeds 95%.

Protocol effectively inhibits nondeterminacy of measurements.

Abstract

Nondeterministic measurement-based techniques are efficient in reshaping the population distribution of a quantum system but suffer from a limited success probability of holding the system in the target state. To reduce the experimental cost, we exploit the state-engineering mechanisms of both conditional and unconditional measurements and propose a two-step protocol assisted by a qubit to cool a resonator down to the ground state with a near-unit probability. In the first step, the unconditional measurements on the ancillary qubit are applied to reshape the target resonator from a thermal state to a reserved Fock state. The measurement sequence is optimized by reinforcement learning for a maximum fidelity. In the second step, the population on the reserved state can be faithfully transferred in a stepwise way to the resonator's ground state with a near-unit fidelity by the conditional measurements on the qubit. Intrinsic nondeterminacy of the projection-based conditional measurement is effectively inhibited by properly spacing the measurement sequence, which makes the Kraus operator act as a lowering operator for neighboring Fock states. Through dozens of measurements, the initial thermal average occupation of the resonator can be reduced by five orders in magnitude with a success probability over $95\%$.